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[null,"RESILIENT FOOD SYSTEMS INDEX"]
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[null,"Contents"]
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[null,"About","Introduction to this index"]
[null,"Pillars","Comparison of pillar performance across countries"]
[null,"Indicators","Comparison across countries for a single selected indicator/pillar"]
[null,"Countries","Country-level scorecard"]
[null,"Data table","Entire dataset, in table format"]
[null,"Scores","Entire scorecard, in table format"]
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[null,null,null,"Supported by:"]
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[null,"Project director: Pratima Singh, pratimasingh@economist.com"]
[null,"Project manager: Apurva Kothari, apurvakothari@economist.com"]

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[null,null,{"$f":"HOME!B7","v":"RESILIENT FOOD SYSTEMS INDEX"}]
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[null,"About the index"]
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[null,"The RFSI serves as a comprehensive, forward-looking benchmark to assess countries’ capacity to sustainably produce and deliver sufficient, affordable and nutritious food to all, amid an increasingly frequent, severe and interconnected risk landscape.\n \nDeveloped by Economist Impact and supported by Cargill, the RFSI aims to evaluate the resilience of food systems in 60 countries, assessed across four key pillars of progress: availability; affordability; quality and safety; and climate risk responsiveness. \n\nThe RFSI is based on a dynamic benchmarking model constructed from 25 qualitative and 46 quantitative drivers of food system resilience. The 60 countries included in the RFSI are spread across six regions: Sub-Saharan Africa; Asia-Pacific; Europe; Latin America and the Caribbean; Middle East and North Africa; and North America.\n     \n     \n     \n     \n     \n     \n     \n     \n     \n     \n\n\n\n"]

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[null,null,{"$f":"HOME!B7","v":"RESILIENT FOOD SYSTEMS INDEX"}]
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[null,"SELECT GROUP",null,null,null,"SELECT SORT ORDER"]
[null,"Global",null,null,null,"Best response to worst"]
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[null,"Scores 80-100 - Areas of strength",null,null,null,80]
[null,"Scores 60-79",null,null,null,60]
[null,"Scores 40-59",null,null,null,40]
[null,"Scores 20-39",null,null,null,20]
[null,"Scores 0-19 - Areas of development",null,null,null,0]
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[null,"Score: 0-100, where 100 = strongest performance"]
[null,"'=' denotes tied rank"]
[null,"Average = mean score for all countries shown in table"]
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[null,"OVERALL ",null,null,null,null,"1) AFFORDABILITY",null,null,null,null,"2) AVAILABILITY",null,null,null,null,"3) QUALITY AND SAFETY",null,null,null,null,"4) CLIMATE RISK RESPONSIVENESS"]
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[{"$f":"IF($F$7=Lists_indicators!$I$4, A82-1,A82+1)","v":61},null,{"$f":"INDEX('Selected values_pillars'!$J$7:$J$159,MATCH(D83,'Selected values_pillars'!$H$7:$H$159,0))","v":60},{"$f":"IFERROR(IF($F$7=Lists_indicators!$I$2, INDEX('Selected values_pillars'!$B$7:$B$159, MATCH($A83,'Selected values_pillars'!$D$7:$D$159,0)), INDEX('Selected values_pillars'!$B$7:$B$159,MATCH($A83,'Selected values_pillars'!$E$7:$E$159,0))),\"\")","v":"Congo (Democratic Republic)"},{"$f":"IF(D83=\"\",\"\",ROUND(INDEX('Selected values_pillars'!$C$7:$C$159, MATCH(D83,'Selected values_pillars'!$B$7:$B$159,0)),2))","v":34.86},null,null,{"$f":"INDEX('Selected values_pillars'!$V$7:$V$159,MATCH(I83,'Selected values_pillars'!$T$7:$T$159,0))","v":60},{"$f":"IFERROR(IF($F$7=Lists_indicators!$I$2, INDEX('Selected values_pillars'!$N$7:$N$159, MATCH($A83,'Selected values_pillars'!$P$7:$P$159,0)), INDEX('Selected values_pillars'!$N$7:$N$159,MATCH($A83,'Selected values_pillars'!$Q$7:$Q$159,0))),\"\")","v":"Congo (Democratic Republic)"},{"$f":"IF(I83=\"\",\"\",ROUND(INDEX('Selected values_pillars'!$O$7:$O$159, MATCH(I83,'Selected values_pillars'!$N$7:$N$159,0)),2))","v":20.74},null,null,{"$f":"INDEX('Selected values_pillars'!$AH$7:$AH$159,MATCH(N83,'Selected values_pillars'!$AF$7:$AF$159,0))","v":60},{"$f":"IFERROR(IF($F$7=Lists_indicators!$I$2, INDEX('Selected values_pillars'!$Z$7:$Z$159, MATCH($A83,'Selected values_pillars'!$AB$7:$AB$159,0)), INDEX('Selected values_pillars'!$Z$7:$Z$159,MATCH($A83,'Selected values_pillars'!$AC$7:$AC$159,0))),\"\")","v":"Congo (Democratic Republic)"},{"$f":"IF(N83=\"\",\"\",ROUND(INDEX('Selected values_pillars'!$AA$7:$AA$159, MATCH(N83,'Selected values_pillars'!$Z$7:$Z$159,0)),2))","v":43},null,null,{"$f":"INDEX('Selected values_pillars'!$AT$7:$AT$159,MATCH(S83,'Selected values_pillars'!$AR$7:$AR$159,0))","v":60},{"$f":"IFERROR(IF($F$7=Lists_indicators!$I$2, INDEX('Selected values_pillars'!$AL$7:$AL$159, MATCH($A83,'Selected values_pillars'!$AN$7:$AN$159,0)), INDEX('Selected values_pillars'!$AL$7:$AL$159,MATCH($A83,'Selected values_pillars'!$AO$7:$AO$159,0))),\"\")","v":"Congo (Democratic Republic)"},{"$f":"IF(S83=\"\",\"\",ROUND(INDEX('Selected values_pillars'!$AM$7:$AM$159, MATCH(S83,'Selected values_pillars'!$AL$7:$AL$159,0)),2))","v":37.340000000000003},null,null,{"$f":"INDEX('Selected values_pillars'!$BF$7:$BF$159,MATCH(X83,'Selected values_pillars'!$BD$7:$BD$159,0))","v":60},{"$f":"IFERROR(IF($F$7=Lists_indicators!$I$2, INDEX('Selected values_pillars'!$AX$7:$AX$159, MATCH($A83,'Selected values_pillars'!$AZ$7:$AZ$159,0)), INDEX('Selected values_pillars'!$AX$7:$AX$159,MATCH($A83,'Selected values_pillars'!$BA$7:$BA$159,0))),\"\")","v":"Romania"},{"$f":"IF(X83=\"\",\"\",ROUND(INDEX('Selected values_pillars'!$AY$7:$AY$159, MATCH(X83,'Selected values_pillars'!$AX$7:$AX$159,0)),2))","v":25.66}]

{"sheet":"INDICATORS","index":3,"n_rows":273,"n_cols":11,"rows_kept":273,"cut":false,"hidden":false,"merged":[[19,4,22,10],[13,4,13,10],[15,4,15,10],[17,4,17,10],[24,4,24,10]]}
[null,null,{"$f":"HOME!B7","v":"RESILIENT FOOD SYSTEMS INDEX"}]
[]
[]
[]
[]
[null,null,"SELECT PILLAR",null,"SELECT INDICATOR",null,"SELECT GROUP",null,"SELECT SORT ORDER"]
[null,null,"1) Affordability",null,"1.2) Affordability of a healthy diet",null,"Sub-Saharan Africa",null,"Best response to worst"]
[null,null,{"$f":"INDEX(Lists_indicators!B2:B7, MATCH(C7,Lists_indicators!A2:A7,0))","v":"_1Affordability"}]
[null,{"$f":"INDEX(Lists_indicators!$D$2:$D$106, MATCH($E7,Lists_indicators!$F$2:$F$106,0))","v":1.2}]
[null,{"$f":"INDEX(Lists_indicators!G2:G105, MATCH(B11,Lists_indicators!F2:F105,0))","v":"Affordability >> Affordability of a healthy diet"}]
[null,{"$f":"E7","v":"1.2) Affordability of a healthy diet"}]
[]
[]
[null,null,"Description: ",null,{"$f":"INDEX('DATA TABLE'!F10:F117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":"The cost of a healthy diet indicator records the cost of purchasing the least expensive locally available foods to meet requirements for energy and food-based dietary guidelines for a representative person within energy balance at 2,330 kcal/day. We calculate this cost as a share of the average daily GDP per head to measure the affordability of accessing a healthy diet."}]
[]
[null,null,"Rationale: ",null,{"$f":"IF(INDEX('DATA TABLE'!L10:L117, MATCH(B9,'DATA TABLE'!B10:B117,0))=\"\",\"\",INDEX('DATA TABLE'!L10:L117, MATCH(B9,'DATA TABLE'!B10:B117,0)))","v":"In addition to low cost food staples, affordable nutritious food for end consumers is essential to maintaining resilience of the food systems. If a larger share of GDP per head is spent on accessing a healthy diet, it can indicate a decline in affordability."}]
[]
[null,null,"Unit:",null,{"$f":"INDEX('DATA TABLE'!D10:D117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":"Cost of a healthy diet as a % of daily mean GDP per head"}]
[]
[null,null,"Scoring guidance:",null,{"$f":"INDEX('DATA TABLE'!H10:H117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."}]
[]
[]
[]
[]
[null,null,"Source:",null,{"$f":"IF(INDEX('DATA TABLE'!E10:E117, MATCH(B9,'DATA TABLE'!B10:B117,0))=\"\",\"\",INDEX('DATA TABLE'!E10:E117, MATCH(B9,'DATA TABLE'!B10:B117,0)))","v":"FAO Cost and Affordability of a Healthy Diet database: https://www.fao.org/faostat/en/#data/CAHD\nWorld Bank GDP per capita: https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD"}]
[]
[null,null,"Direction:",null,{"$f":"INDEX('DATA TABLE'!J10:J117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":"Low = good"}]
[null,null,"Type of data (quant/qual)",null,{"$f":"INDEX('DATA TABLE'!I10:I117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":"Quant"}]
[null,null,"Indicator level:",null,{"$f":"INDEX('DATA TABLE'!K10:K117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":2}]
[null,null,"Year:",null,{"$f":"INDEX('DATA TABLE'!G10:G117, MATCH(B9,'DATA TABLE'!B10:B117,0))","v":"2022-2024"}]
[]
[null,null,"Scores 80-100 - Areas of strength"]
[null,null,"Scores 60-79"]
[null,null,"Scores 40-59"]
[null,null,"Scores 20-39"]
[null,null,"Scores 0-19 - Areas of development"]
[null,"'=' denotes tied rank"]
[null,"Average = mean score for all countries shown in table"]
[]
[null,null,{"$f":"CONCATENATE(\"Rank - \"&G7)","v":"Rank - Sub-Saharan Africa"},null,"Country",null,"Score",null,"Data",null,{"$f":"IF($C$7=\"Background indicators\",\"\",IF(G7=\"Global\",\"\", \"(Rank - global)\"))","v":"(Rank - global)"}]
[null,null,{"$f":"IF($C$7=\"Background indicators\",\"\",CONCATENATE(\"Out of \"&(INDEX(Lists_countries!R1:AB1,MATCH(G7,Lists_countries!R2:AB2,0))-1)&\" countries\"))","v":"Out of 10 countries"},null,null,null," 0-100, where 100 = strongest performance",null,{"$f":"IF(INDEX('DATA TABLE'!$G$10:$G$117, MATCH($B$9,'DATA TABLE'!$B$10:$B$117,0))=\"\",\"\",INDEX('DATA TABLE'!$G$10:$G$117, MATCH($B$9,'DATA TABLE'!$B$10:$B$117,0)))","v":"2022-2024"},null,{"$f":"IF($C$7=\"Background indicators\",\"\",IF(K40=\"\",\"\",\"(Out of 60 countries)\"))","v":"(Out of 60 countries)"}]
[{"$f":"IF($C$7=\"Background indicators\",1,IF($I$7=Lists_indicators!$I$4,INDEX(Lists_countries!$R$1:$AB$1, MATCH($G$7,Lists_countries!$R$2:$AB$2,0)),1))","v":1},null,{"$f":"IF(G42=\"Not scored\",\"\",INDEX('Selected values_indicators'!$J$7:$J$159,MATCH($E42,'Selected values_indicators'!$H$7:$H$159,0)))","v":1},null,{"$f":"IFERROR(IF($I$7=Lists_indicators!$I$2, INDEX('Selected values_indicators'!$B$7:$B$159, MATCH($A42,'Selected values_indicators'!$D$7:$D$159,0)), INDEX('Selected values_indicators'!$B$7:$B$159,MATCH($A42,'Selected values_indicators'!$E$7:$E$159,0))),\"\")","v":"South Africa"},null,{"$f":"IF(E42=\"\",\"\",IFERROR(ROUND(INDEX('Selected values_indicators'!$C$7:$C$159, MATCH($E42,'Selected values_indicators'!$B$7:$B$159,0)),2),\"Not scored\"))","v":88.49},null,{"$f":"IFERROR(IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B$9,'DATA TABLE'!$B$10:$B$117,0), MATCH($E42,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B$9,'DATA TABLE'!$B$10:$B$117,0), MATCH($E42,'DATA TABLE'!$M$9:$BT$9,0))),\"\")","v":9.1859999999999999},null,{"$f":"IF(G42=\"Not scored\",\"\",\nIF($K$40=\"\",\"\",\nIF($A42=\"\",\"\",\nIF($A42=\"AVERAGE\",\"\",\nINDEX('Selected values_indicators'!$T$7:$T$159,\nMATCH($E42,'Selected values_indicators'!$B$7:$B$159,0))\n)\n)\n))","v":36}]
[{"$f":"IF($C$7=\"Background indicators\",A42+1,IF($I$7=Lists_indicators!$I$4, A42-1,A42+1))","v":2},null,{"$f":"IF(G43=\"Not scored\",\"\",INDEX('Selected values_indicators'!$J$7:$J$159,MATCH($E43,'Selected values_indicators'!$H$7:$H$159,0)))","v":2},null,{"$f":"IFERROR(IF($I$7=Lists_indicators!$I$2, INDEX('Selected values_indicators'!$B$7:$B$159, MATCH($A43,'Selected values_indicators'!$D$7:$D$159,0)), INDEX('Selected values_indicators'!$B$7:$B$159,MATCH($A43,'Selected values_indicators'!$E$7:$E$159,0))),\"\")","v":"Namibia"},null,{"$f":"IF(E43=\"\",\"\",IFERROR(ROUND(INDEX('Selected values_indicators'!$C$7:$C$159, MATCH($E43,'Selected values_indicators'!$B$7:$B$159,0)),2),\"Not scored\"))","v":81.099999999999994},null,{"$f":"IFERROR(IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B$9,'DATA TABLE'!$B$10:$B$117,0), MATCH($E43,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B$9,'DATA TABLE'!$B$10:$B$117,0), MATCH($E43,'DATA TABLE'!$M$9:$BT$9,0))),\"\")","v":14.586},null,{"$f":"IF(G43=\"Not scored\",\"\",\nIF($K$40=\"\",\"\",\nIF($A43=\"\",\"\",\nIF($A43=\"AVERAGE\",\"\",\nINDEX('Selected values_indicators'!$T$7:$T$159,\nMATCH($E43,'Selected values_indicators'!$B$7:$B$159,0))\n)\n)\n))","v":47}]
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[null,null,"SELECT REGION"]
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[null,null,"SELECT COUNTRY"]
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[null,null,"Scores 60-79",null,60]
[null,null,"Scores 40-59",null,40]
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[null,null,"Scores 0-19 - Areas of development",null,0]
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[null,1.4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B30,Lists_indicators!$D$2:$D$106,0))","v":"1.4) Agricultural trade"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B30,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":51.8}]
[null,1.5,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B31,Lists_indicators!$D$2:$D$106,0))","v":"1.5) Food safety net programmes"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B31,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":12.5}]
[null,2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B32,Lists_indicators!$D$2:$D$106,0))","v":"2) AVAILABILITY"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B32,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":43}]
[null,2.1,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B33,Lists_indicators!$D$2:$D$106,0))","v":"2.1) Access to agricultural inputs"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B33,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":39.1}]
[null,2.2000000000000002,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B34,Lists_indicators!$D$2:$D$106,0))","v":"2.2) Inclusive and skilled agricultural workforce"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B34,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":58.6}]
[null,2.2999999999999998,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B35,Lists_indicators!$D$2:$D$106,0))","v":"2.3) Public expenditure on agricultural research and development"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B35,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":4.8}]
[null,2.4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B36,Lists_indicators!$D$2:$D$106,0))","v":"2.4) Volatility of agricultural production"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B36,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":95}]
[null,2.5,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B37,Lists_indicators!$D$2:$D$106,0))","v":"2.5) Growth in productivity of the agricultural sector"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B37,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":52.7}]
[null,2.6,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B38,Lists_indicators!$D$2:$D$106,0))","v":"2.6) Efficient agrifood supply chains"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B38,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":55.2}]
[null,2.7,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B39,Lists_indicators!$D$2:$D$106,0))","v":"2.7) Sufficiency of supply"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B39,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":4.2}]
[null,2.8,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B40,Lists_indicators!$D$2:$D$106,0))","v":"2.8) Food security and access policy commitments"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B40,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":50}]
[null,2.9,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B41,Lists_indicators!$D$2:$D$106,0))","v":"2.9) Socio-political risk outlook"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B41,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":23.3}]
[null,3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B42,Lists_indicators!$D$2:$D$106,0))","v":"3) QUALITY AND SAFETY"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B42,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":37.299999999999997}]
[null,3.1,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B43,Lists_indicators!$D$2:$D$106,0))","v":"3.1) Dietary diversity"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B43,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":58.4}]
[null,3.2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B44,Lists_indicators!$D$2:$D$106,0))","v":"3.2) Nutritional standards"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B44,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":42}]
[null,3.3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B45,Lists_indicators!$D$2:$D$106,0))","v":"3.3) Protein quality"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B45,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":0}]
[null,3.4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B46,Lists_indicators!$D$2:$D$106,0))","v":"3.4) Food safety"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B46,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":32.5}]
[null,4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B47,Lists_indicators!$D$2:$D$106,0))","v":"4) CLIMATE RISK RESPONSIVENESS"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B47,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":40}]
[null,4.0999999999999996,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B48,Lists_indicators!$D$2:$D$106,0))","v":"4.1) Physical risk exposure"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B48,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":55.5}]
[null,4.2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B49,Lists_indicators!$D$2:$D$106,0))","v":"4.2) Disaster management"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B49,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":26.2}]
[null,4.3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106, MATCH($B50,Lists_indicators!$D$2:$D$106,0))","v":"4.3) Mitigation and adaptation"},null,{"$f":"ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B50,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1)","v":37.299999999999997}]
[]
[]
[null,null,"Detailed scorecard"]
[]
[null,null,null,null,"Score",null,"Data","Notes","Unit","Source","Description","Year/s","Scoring guidelines","Direction","Indicator level","Indicator/sub-indicator rationale"]
[null,null,null,null," 0-100, where 100 = strongest performance"]
[null,1,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B57,Lists_indicators!$D$2:$D$106,0))","v":"1) AFFORDABILITY"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B57,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":20.7},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B57,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B57,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B57,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B57,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""}]
[null,1.1000000000000001,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B58,Lists_indicators!$D$2:$D$106,0))","v":"1.1) Change in average food costs"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B58,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":31.3},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B58,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B58,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":13.739000000000001},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B58,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B58,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"General consumer price index (CPI) from EIU was used as the FAO food CPI dataset for Congo (Democratic Republic) was only available up to 2017. \nhttps://viewpoint.eiu.com/data/results?searchId=140b5b6c-771e-436a-8dc7-333e87ac9b0b#"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Food and Agriculture Organisation (FAO): \nhttps://www.fao.org/faostat/en/#data/CP\nEIU General CPI:\nhttps://viewpoint.eiu.com/data/results?searchId=140b5b6c-771e-436a-8dc7-333e87ac9b0b#"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of change in average food costs over time. To assess the structural change in prices of the average basket of food goods across countries, we take an average across the most recent five years of data available for the annual change in the FAO's food consumer price index."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2018-2025"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 or below scores 100; a value of 20 or above scores 0. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B58,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Sharp increases in the cost of the average basket of food goods can indicate a decline in affordability."}]
[null,1.2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B59,Lists_indicators!$D$2:$D$106,0))","v":"1.2) Affordability of a healthy diet"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B59,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B59,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B59,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":73.864999999999995},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B59,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B59,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Cost of a healthy diet as a % of daily mean GDP per head"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO Cost and Affordability of a Healthy Diet database: https://www.fao.org/faostat/en/#data/CAHD\nWorld Bank GDP per capita: https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The cost of a healthy diet indicator records the cost of purchasing the least expensive locally available foods to meet requirements for energy and food-based dietary guidelines for a representative person within energy balance at 2,330 kcal/day. We calculate this cost as a share of the average daily GDP per head to measure the affordability of accessing a healthy diet."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2022-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B59,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"In addition to low cost food staples, affordable nutritious food for end consumers is essential to maintaining resilience of the food systems. If a larger share of GDP per head is spent on accessing a healthy diet, it can indicate a decline in affordability."}]
[null,1.3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B60,Lists_indicators!$D$2:$D$106,0))","v":"1.3) Affordability of a healthy diet to bottom 40%"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B60,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B60,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B60,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":392.54599999999999},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B60,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B60,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Cost of a heathy diet as a % of daily mean GDP per head for quintiles 1 and 2 of the population"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Mean income of bottom 40%: https://www4.wider.unu.edu/?ind=50,67,68&type=table&year=72&byCountry=false&slider=buttons&avg=precomputed&yearRange=0,72 \nFAO Cost and Affordability of a Healthy Diet database: https://www.fao.org/faostat/en/#data/CAHD"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The cost of a healthy diet indicator records the cost of purchasing the least expensive locally available foods to meet requirements for energy and food-based dietary guidelines for a representative person within energy balance at 2,330 kcal/day. We calculate this cost as a share of the mean daily GDP per head for income quintiles 1 and 2, or the bottom 40% of the population of a country by income."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2022},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B60,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"In both emerging and advanced economies, households in the lowest income quintiles tend to spend a significantly larger share of their disposable income on food. A higher share of household disposal spending on food by the bottom 40% (quintiles 1 and 2), compared with the overall population, can indicate a decline in affordability for vulnerable groups. \nThe Food Foundation: https://foodfoundation.org.uk/press-release/dietary-inequalities-worsened-last-two-years-healthier-foods-grew-more-expensive\nFAO: https://openknowledge.fao.org/server/api/core/bitstreams/67b1e9c7-1a7f-4dc6-a19e-f6472a4ea83a/content"}]
[null,1.4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B61,Lists_indicators!$D$2:$D$106,0))","v":"1.4) Agricultural trade"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B61,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":51.8},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B61,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B61,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B61,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B61,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B61,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B61,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Economist Impact (EI) calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B61,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator measuring the tariff and non-tariff trade barriers and trading partner diversification"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B61,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B61,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B61,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"1.4.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B62,Lists_indicators!$D$2:$D$106,0))","v":"1.4.1) Agricultural import tariffs"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B62,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":72.599999999999994},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B62,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B62,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":11.037000000000001},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B62,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B62,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"Latest year of data available"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Agricultural import tariffs, %"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Trade Organisation (WTO):\nhttps://ttd.wto.org/en"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the average most-favoured nation tariff applied on all agricultural imports"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2022-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0.1 or below scores 100; a value of 40 or above scores 0. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B62,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Agricultural tariffs can increase the cost of food imports, and therefore food costs for consumers."}]
[null,"1.4.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B63,Lists_indicators!$D$2:$D$106,0))","v":"1.4.2) Agricultural and food products import non-tariff measures (NTMs)"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B63,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":99.9},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B63,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B63,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B63,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B63,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Number of non-tariff measures imposed"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"WTO:\nhttps://i-tip.wto.org/goods/Forms/TableView.aspx"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The total number of non-tariff measures (NTMs) imposed by an importing country on agricultural and food products (HS codes 1-24). These measures include: anti-dumping; countervailing; quantitative restriction; safeguards; sanitary and phytosanitary [ordinaire, urgence, problèmes commerciaux spécifiques]; special safeguards; technical barriers to trade) [mesures ordinaires]; tariff-rate quotas; and export subsidies."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B63,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"NTMs are all policy interventions other than tariffs that can potentially affect the quantities and prices of internationally traded goods. Not all NTMs are imposed with a primary objective of affecting imports or exports, and different types of NTMs carry more burden than others for different countries; however, importing countries imposing a greater number of NTMs may experience higher domestic food prices, impacting affordability. \nhttps://www.wto.org/english/res_e/booksp_e/non_tariff_measures_e.pdf"}]
[null,"1.4.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B64,Lists_indicators!$D$2:$D$106,0))","v":"1.4.3) Import partner diversification"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B64,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":28.7},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B64,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B64,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":5.1449999999999996},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B64,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B64,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Index score"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"UN Trade & Development (UNCTAD) Theil concentration indices of exports and imports:\nhttps://unctadstat.unctad.org/datacentre/dataviewer/US.MerchTheilIndices; https://unctadstat.unctad.org/datacentre/reportInfo/US.MerchTheilIndices"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of how concentrated a country's imports are across their import partner countries for different products. The Theil import indices measure import concentration in the basket of imported products (excluding services) and in the set of import markets of an individual economy or a group of economies. They are derived from all bilateral import flows of all individual products (at the SITC, Rev.3, 3-dig level) from the UNCTAD Merchandise Trade Matrix and are further decomposed additively into two sub-indices: one to measure product concentration and another to measure market (per product) concentration; that is, the two components add up to the overall Theil import concentration index.\nHigher values on the overall Theil import index represent a higher degree of import concentration or a lower import diversification. \n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B64,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Less concentrated or more diversified sources of food imports build redundancy in a country's domestic agrifood supply chain, allowing it to withstand supply shocks from a few import partner countries and maintain food price levels domestically."}]
[null,"1.4.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B65,Lists_indicators!$D$2:$D$106,0))","v":"1.4.4) Export partner diversification"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B65,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B65,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B65,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":8.2070000000000007},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B65,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B65,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Index score"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"UNCTAD Theil concentration indices of exports and imports:\nhttps://unctadstat.unctad.org/datacentre/dataviewer/US.MerchTheilIndices;\nhttps://unctadstat.unctad.org/datacentre/reportInfo/US.MerchTheilIndices"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of how concentrated a country's exports are across their export partner countries for different products. The Theil export indices measure export concentration in the basket of exported products (excluding services) and in the set of export markets of an individual economy or a group of economies. They are derived from all bilateral export flows of all individual products (at the SITC, Rev.3, 3-dig level) from the UNCTAD Merchandise Trade Matrix and are further decomposed additively into two sub-indices: one to measure product concentration and another to measure market (per product) concentration; that is, the two components add up to the overall Theil export concentration index.\nHigher values on the overall Theil export index represent a higher degree of export concentration or a lower import diversification. \n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B65,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A less concentrated or more diversified pool of export partners strengthens market resilience for the agrifood sector in a country, as it allows countries to better manage fluctuations in global demand (due to a variety of drivers, including geopolitical tensions, trade policy changes and economic downturns in partner countries), building the long-term capacity of the food system to consistently provide affordable food. \nhttps://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/CDP-bp-2023-59.pdf"}]
[null,1.5,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B66,Lists_indicators!$D$2:$D$106,0))","v":"1.5) Food safety net programmes"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B66,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":12.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B66,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B66,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B66,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B66,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B66,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B66,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B66,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator assessing the presence and nature of food safety net programmes"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B66,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B66,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B66,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"1.5.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B67,Lists_indicators!$D$2:$D$106,0))","v":"1.5.1) Presence of food safety net programmes"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B67,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":50},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B67,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B67,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B67,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B67,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Are food safety net programmes present in the country and able to reach the populations who need support? Do these food safety net programmes have specific objectives to deliver a healthy diet to populations in need?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2 = Programmes are present and have objectives to deliver a healthy diet (adequate, balanced, moderate and diverse) \n1 = Programmes are present\n0 = Programmes are not present"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B67,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Food safety net programmes help to provide consistent food access for food-insecure populations. Having specific objectives in the food safety net programmes to deliver a healthy diet can ensure all populations in need can access affordable and nutritious meals. The FAO and WHO define a healthy diet as one that is adequate in essential nutrient supply, balanced in energy sources, includes a wide variety of nutritious foods and is moderate in consumption. \nhttps://iris.who.int/bitstream/handle/10665/379324/9789240101876-eng.pdf?sequence=5"}]
[null,"1.5.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B68,Lists_indicators!$D$2:$D$106,0))","v":"1.5.2) Funding for food safety net programmes"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B68,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B68,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B68,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B68,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B68,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there evidence that the food safety net programmes have sufficient funding?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"1 = Food safety nets have consistent, dedicated funding that is adjusted to meet national needs.\n0 = Funding for food safety nets is inconsistent or facing reductions."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B68,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Food safety net programmes with dedicated funding are better able to serve their target populations."}]
[null,"1.5.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B69,Lists_indicators!$D$2:$D$106,0))","v":"1.5.3) Coverage of food safety net programmes"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B69,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B69,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B69,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B69,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B69,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Do the food safety net programmes have national coverage and cover all populations in need?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each:\n- Food safety net programmes have national coverage. (There is strong evidence that the food safety net programme reaches all geographies of the country.)\n- Food safety net programmes cover all populations who need assistance. (There is strong evidence that the food safety net programme covers a variety of different population groups in the lowest income quintiles of the country, notably historically underserved populations such as ethnic and gender minorities, rural population and indigenous groups.)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B69,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A nationwide coverage with focus on targeting all populations in need ensures coverage of all food-insecure people in the country."}]
[null,"1.5.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B70,Lists_indicators!$D$2:$D$106,0))","v":"1.5.4) Operation of food safety net programmes"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B70,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B70,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B70,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B70,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B70,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Are the food safety net programmes operated by the government and not dependent on external operational or funding support?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"1 = Food safety net programmes are operated by the national government.\n0 = Food safety net programmes depend on donor or non-governmental support."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B70,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Food safety net programmes operated by the national government are more sustainable."}]
[null,"1.5.5",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B71,Lists_indicators!$D$2:$D$106,0))","v":"1.5.5) End-to-end monitoring of food safety net programmes"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B71,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B71,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B71,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B71,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B71,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-5; 5 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Does the country monitor the delivery of its food safety net programmes from point of disbursement to point of final use?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each:\n- Mechanisms for identifying and targeting beneficiaries\n- Mechanisms for monitoring delivery of food safety net assistance from point of disbursement to point of service/beneficiaries (ie digital payments of cash-based assistance or tracking of in-kind assistance)\n- Mechanisms for tracking utilisation of food safety net assistance at point of service (such as public schools/ration shops/food banks)\n- Mechanisms for sharing utilisation data (ie quantities and type of food consumed/purchased at point of service) with health and nutrition agencies\n- Dedicated beneficiary feedback/grievance channels"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B71,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"End-to-end monitoring of food safety net programmes can help policymakers ensure timely, accurate, transparent and accountable delivery of nutrition-sensitive food or cash benefits from point of disbursement to populations in need. Additionally, it can allow policymakers to better predict and manage food supply shortages at the points of service (such as public schools/ration shops/food banks). Collecting data on quantity and types of food consumed/purchased at point of service and sharing this with health and nutrition agencies can allow them to gauge if the nutritional needs of the population are sufficiently met. \nhttps://www.codevelop.fund/insights-1/addressing-food-security-with-digital-public-infrastructure;\nhttps://www.sciencedirect.com/science/article/pii/S2212420923003072"}]
[null,2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B72,Lists_indicators!$D$2:$D$106,0))","v":"2) AVAILABILITY"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B72,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":43},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B72,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B72,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B72,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B72,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B72,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B72,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B72,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Measures access to agricultural inputs and markets for farmers, the efficiency of agrifood supply chains and the presence of public, private and blended actor mechanisms to deliver sufficient food to all"}]
[null,2.1,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B73,Lists_indicators!$D$2:$D$106,0))","v":"2.1) Access to agricultural inputs"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B73,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":39.1},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B73,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B73,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B73,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B73,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B73,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B73,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B73,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures access to resources and inputs for farmers"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B73,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B73,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B73,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"2.1.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B74,Lists_indicators!$D$2:$D$106,0))","v":"2.1.1) Irrigation infrastructure"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B74,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0.1},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B74,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B74,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":7.0000000000000007E-2},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B74,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B74,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Land area equipped for irrigation, %"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/faostat/en/#data/RL"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the percentage of cropland area that is equipped for irrigation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 or below scores 0; a value of 50 or above scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B74,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Irrigation infrastructure enables more consistent and productive crop yields, even with unreliable rainfall. This capacity is fundamental for resilience, as it critically reduces a food system's vulnerability to drought and climate variability, thereby securing the food supply against environmental shocks."}]
[null,"2.1.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B75,Lists_indicators!$D$2:$D$106,0))","v":"2.1.2) Reliable access to electricity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B75,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":8.6999999999999993},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B75,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B75,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B75,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B75,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Bank, EIU"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite sub-indicator that tracks access to electricity among the rural population and the reliability of electricity supply"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B75,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Expanding electricity access and enhancing its quality are vital for boosting agricultural productivity and food availability."}]
[null,"2.1.2.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B76,Lists_indicators!$D$2:$D$106,0))","v":"2.1.2.1) Access to electricity, rural (% of rural population)"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B76,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":1},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B76,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B76,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B76,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B76,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Bank:\nhttps://data.worldbank.org/indicator/EG.ELC.ACCS.RU.ZS"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Percentage of rural population with access to electricity"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0. A value of 100 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":4},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B76,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to electricity among the rural population serves as a proxy to track access to electricity for farmers. This access enables the use of agricultural technologies, irrigation systems and cold storage, all of which are essential for increasing and stabilising food production. Additionally, improved energy access enhances the reliability and efficiency of food supply chains, directly contributing to the availability of food in rural and surrounding regions."}]
[null,"2.1.2.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B77,Lists_indicators!$D$2:$D$106,0))","v":"2.1.2.2) Reliability of electricity supply"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B77,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":16.399999999999999},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B77,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B77,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1.655},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B77,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B77,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"Regional average"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 1-5; 5 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EIU"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The reliability of electricity supply indicator scores countries on the annual production of energy per head (kWh per head) between the range of 1 and 5, with 1 being very low and 5 being very high.\n5: Very high: if more than 7,000 kWh per head\n4: High: if between 4,501 and 7,000 kWh per head\n3: Moderate: if between 2,501 and 4,500 kWh per head\n2: Low: if between 750 and 2,500 kWh per head\n1: Very low: if less than 750 kWh per head"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 1 scores 0. A value of 5 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":4},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B77,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Continuous and reliable electricity supply serves as a critical input to agricultural production and improving access to food. \nhttps://www.sciencedirect.com/science/article/abs/pii/S0140988325006395"}]
[null,"2.1.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B78,Lists_indicators!$D$2:$D$106,0))","v":"2.1.3) Nutrient use efficiency"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B78,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":68.8},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B78,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B78,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":137.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B78,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B78,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-200"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Yale Environmental Performance Index (EPI): \nhttps://epi.yale.edu/measure/2024/SNM\nhttps://epi.yale.edu/measure/2024/PSU"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite measure of the efficiency of nitrogen and phosphorus use (as nutrients) in agriculture. Scores on the indicators Sustainable Nitrogen Management Index (SNMI) and Phosphorus Surplus from the Yale EPI are aggregated. \nThe SNMI seeks to balance efficient application of nitrogen fertiliser with maximum crop yields as a measure of the environmental performance of agricultural production. The 2024 EPI uses the SNMI as a proxy for agricultural drivers of environmental damage. A score of 100 indicates that a country is optimising both crop yields and fertiliser application; a score of 0 indicates a country is among the worst performers on the SNMI. Data supporting this metric come from the FAO STAT crop nutrient budget database.\nPhosphorus Surplus is the difference between phosphorus inputs (as fertiliser) and outputs (as harvested crops), as a proxy of excessive phosphorus fertiliser use that can contribute to the eutrophication of water bodies. A score of 100 indicates no surplus, while a score of 0 indicates worst performance."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0. A value of 200 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B78,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Nutrient use efficiency (NUE) enhances food availability by increasing crop yields using fewer inputs, ensuring that plants absorb more of the nutrients applied. This reduces waste, lowers production costs and maintains soil health, allowing farmers to produce more food sustainably. Improved NUE is especially vital in regions with limited access to fertilisers, helping maximise output from existing farmland while minimising environmental degradation."}]
[null,"2.1.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B79,Lists_indicators!$D$2:$D$106,0))","v":"2.1.4) Adoption of agritech solutions"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B79,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B79,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B79,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":3},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B79,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B79,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3=best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there a national policy/action plan to promote adoption of mature agritech solutions? Is there evidence of public, private, multilateral or blended funding mechanisms to promote adoption of mature agritech solutions? Does the national policy/action plan or the targeted funding mechanism focus on disadvantaged groups of farmers?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award 1 point for each element: \n- There exists a national policy/action plan to promote adoption of agritech solutions (such as farm equipment and high-quality seeds)\n- There is evidence of a current targeted funding mechanism (not a one-off programme/pilot) supported by the public, private, multilateral or blended sectors to promote adoption of agritech solutions. \n- The existing national policy/action plan or targeted funding mechanism promoting the adoption of agritech solutions has a special focus on disadvantaged groups of farmers (smallholders, subsistence, youth, women and/or other minorities)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B79,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Widespread adoption of mature agritech solutions such as but not limited to high-quality seeds and farm equipment such as tractors, power tillers, combine harvesters, seeders, sprayers is fundamental to increasing crop yields and improving the reliability of agricultural production. Policies and funding mechanisms that focus on making these solutions accessible to farmers, particularly disadvantaged groups such as ie, smallholders, subsistence, youth, women and other country-specific underserved minorities, contribute to increasing the availability of nutritious food and raise incomes of workers in the agriculture sector. "}]
[null,"2.1.5",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B80,Lists_indicators!$D$2:$D$106,0))","v":"2.1.5) Access to internet at home"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B80,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":38.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B80,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B80,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":38.494},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B80,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B80,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"ITU DataHub\n \nhttps://datahub.itu.int/data/?i=12047"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Refers to the proportion of households with internet access at home. Access can be via a fixed or mobile network. If one member of the household has a mobile phone with connection to the internet and makes it available for all members, it should be considered that the household has access to the internet."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0. A value of 100 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B80,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to the internet is critical for farmers to access up-to-date market information and agricultural extension services disseminated digitally. Furthermore, farmers and food-insecure populations benefit from access to inclusive financial services, such as internet banking."}]
[null,"2.1.6",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B81,Lists_indicators!$D$2:$D$106,0))","v":"2.1.6) Basic financial services"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B81,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":24.1},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B81,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B81,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B81,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B81,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The Global Findex Database, World Bank: https://databank.worldbank.org/source/global-findex-database National sources"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite sub-indicator that tracks access to basic financial services (ie savings and credit from formal financial institutions)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B81,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to savings and credit improves farmer productivity and the ability of farmers to provide for their own families."}]
[null,"2.1.6.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B82,Lists_indicators!$D$2:$D$106,0))","v":"2.1.6.1) Access to formal savings account"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B82,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":39.200000000000003},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B82,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B82,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":39.213999999999999},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B82,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B82,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The Global Findex Database, World Bank:\nhttps://databank.worldbank.org/source/global-findex-database\n\nhttps://thedocs.worldbank.org/en/doc/fe026d04da1eb78f5ce8bb5e1529d60b-0430062023/original/Findex2021-22-Methodology.pdf"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Share of population (%, age 15+) having an account (by themselves or jointly with someone else) at a bank or another type of financial institution, or who report personally using a mobile money service \n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0. A value of 100 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":4},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B82,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to savings and credit improves farmer productivity and the ability of farmers to provide for their own families."}]
[null,"2.1.6.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B83,Lists_indicators!$D$2:$D$106,0))","v":"2.1.6.2) Access to formal sources of credit"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B83,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":9},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B83,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B83,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":9},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B83,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B83,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The Global Findex Database, World Bank:\nhttps://databank.worldbank.org/source/global-findex-database"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Share of population (%, age 15+) with access to formal sources of credit via borrowing from a bank or similar financial institution or via a mobile money service"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0. A value of 100 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":4},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B83,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to savings and credit improves farmer productivity and the ability of farmers to provide for their own families."}]
[null,"2.1.7",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B84,Lists_indicators!$D$2:$D$106,0))","v":"2.1.7) Diversified financial services for agrifood value chain"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B84,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":33.299999999999997},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B84,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B84,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B84,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B84,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"This indicator assesses the availability of specialised financial products, beyond basic credit and savings, for actors across the agrifood value chain, including smallholders, small and medium-sized enterprises (SMEs), processors and traders."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"0 - Financial services are limited to credit/savings. There is no evidence of diversified financing and risk management products tailored to different actors in the agrifood sector. \n1 - There is evidence of a few diversified financing and risk management products but these are tailored to meet the needs of only a few value chain actors in the agrifood sector. (Only a few specialised financial products exist targeting large-scale actors. Most value chain participants rely on basic or informal finance.)\n2 - There is evidence of a wide range of diversified financing and risk management products but these are tailored to meet the needs of only a few value chain actors in the agrifood sector. (Only a few specialised financial products exist targeting large-scale actors. Most value chain participants rely on basic or informal finance.)\n3 - There is evidence of a wide range of diversified financing and risk management products and these are tailored to meet the needs of different-sized value chain actors in the agrifood sector. (Products are available to, and cater to the specific needs of, disadvantaged actors in the value chain, including smallholders, subsistence farmers, SMEs, women and other minorities)."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B84,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Diversified financial services such as insurance, leasing and input financing help value chain actors manage risk, invest in productivity and maintain stable food supply, directly supporting the availability of food system resilience."}]
[null,2.2000000000000002,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B85,Lists_indicators!$D$2:$D$106,0))","v":"2.2) Inclusive and skilled agricultural workforce"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B85,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":58.6},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B85,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B85,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B85,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B85,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B85,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B85,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B85,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that tracks inputs to building an inclusive and skilled agricultural workforce for the future. This includes: gender parity in incomes; higher participation rate of youth in the sector; access to agricultural knowledge and skill transfer mechanisms; and a public-sector commitment to ensure that an economy-wide green transition does not leave disadvantaged stakeholder groups within the farming workforce behind."},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B85,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score scale 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B85,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B85,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"2.2.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B86,Lists_indicators!$D$2:$D$106,0))","v":"2.2.1) Employment in agriculture: youth vs total population"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B86,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B86,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B86,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":4.8},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B86,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B86,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Percentage points (pp)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"ILOSTAT, World Bank, National sources:\n\nhttps://rshiny.ilo.org/dataexplorer05/?lang=en&segment=indicator&id=EMP_3EMP_SEX_AGE_OCU_NB_A\n\nhttps://data.worldbank.org/indicator/SL.AGR.EMPL.ZS"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of youth employed (aged 15-29) in agricultural sector compared to the overall population. A percentage point difference is calculated between the share of working-age youth (aged 15-29) employed as “market-oriented skilled agricultural workers\" and the share of total working population employed as “market-oriented skilled agricultural workers\". Values less than 0 indicate that youth workers are underrepresented compared to the overall working population in the agricultural sector."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2020-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. Higher data values produce higher scores upto 0. A value of 0 or above scores 100."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B86,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A higher participation rate of youth in farming is crucial for resilient food systems because it ensures the continuation of agricultural knowledge and practices, introduces innovation and technological advancements and addresses the challenges of an ageing farming population. Young people are essential for the long-term sustainability and adaptability of food production, especially as the world faces increasing demands and climate change impacts."}]
[null,"2.2.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B87,Lists_indicators!$D$2:$D$106,0))","v":"2.2.2) Wage gap: Agriculture sector vs national average"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B87,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":45.9},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B87,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B87,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":-43.938000000000002},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B87,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B87,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"Estimate. Average percentage difference between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors in Ethiopia, Rwanda and Uganda."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Percentage change (%)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"ILOSTAT, national sources:\nhttps://rshiny.ilo.org/dataexplorer05/?lang=en&segment=indicator&id=EMP_3EMP_SEX_AGE_OCU_NB_A"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the gap between the income of agriculture workers and the average income of the entire working population. Percentage change between the average monthly wages in the agricultural sector (defined in the source as: \"Major Group 6 - skilled agricultural, forestry and fishery workers\") and the national average monthly wages of the total working population (defined in the source as \"skills level: total\"). Negative values indicate that agricultural income is below the average income of the entire population."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B87,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Monitoring the gap between wages of agricultural workers (ISCO Major Group 6) and the national average wage helps assess whether the food system provides fair and decent livelihoods for its producers. Exceptionally low earnings in the agricultural sector compared to the national average can act as a disincentive for future generations of workforce for entering or remaining in the sector."}]
[null,"2.2.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B88,Lists_indicators!$D$2:$D$106,0))","v":"2.2.3) Access to extension and information dissemination"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B88,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":37.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B88,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B88,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B88,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B88,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-4; 4 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Do farmers have access to agricultural extension/advisory and information services?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award 0.5 point for each element:\n- National coverage of: \n--- extension services through training institutes/universities/online platforms [0.5]\n--- information dissemination through more than one channel (short message service (SMS), app, interactive voice response (IVR)/radio) [0.5]\n- Covers a variety of topics: \n--- extension services: agronomics, seed usage, on-the-farm automation, integrated pest management [0.5]\n--- information dissemination on: market prices, agronomic information, timely weather forecasts and pest alerts [0.5]\n- Inclusive: specialised services for vulnerable groups of farmers (smallholders, subsistence, women, indigenous and other minorities):\n--- extension services [0.5]\n--- information dissemination [0.5]\n- Available in several local languages/the major language:\n--- extension services [0.5]\n--- information dissemination [0.5]"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B88,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Agricultural extension plays an important role in boosting agricultural productivity, increasing food security and improving rural livelihoods, and helps rural producers meet new challenges confronting agriculture.This indicator assesses the type, reach, inclusivity and collaboration model of agricultural extension services in a country. It rewards blended public-private approaches and inclusive delivery models that ensure access across different population groups and geographies."}]
[null,"2.2.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B89,Lists_indicators!$D$2:$D$106,0))","v":"2.2.4) Community organisations"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B89,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B89,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B89,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B89,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B89,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Do farmers have access to community organisations (eg producers' associations, co-operatives, unions and federations)?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2 = Access to community organisations available for all farmers\n1 = Access to community organisations available to some, but not all (eg exclusive of smallholder farmers or certain regions)\n0 = Access to community organisations limited or unavailable for most farmers"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B89,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Producer organisations, co-operatives and farmer unions pool resources, strengthen bargaining power and connect smallholders to inputs, credit, extension and markets. Tracking the presence of active community organisations therefore signals whether farmers have the collective capacity and support networks needed to secure decent livelihoods and sustain reliable food production."}]
[null,"2.2.5",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B90,Lists_indicators!$D$2:$D$106,0))","v":"2.2.5) Political commitment to just transition"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B90,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B90,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B90,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B90,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B90,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3=best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Does the country’s Nationally Determined Contributions (NDC)/National Adaptation Plan (NAP)/Biennial Update Report (BUR) address supporting a just transition for the agrifood sector? Does the NDC/NAP/BUR specifically address ensuring a just transition for vulnerable groups of farmers such as smallholders or subsistence farmers, women, indigenous people and traditional land users/informal workers in the agrifood supply chain?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"0 - No mention of just transition in NDC/NAP/BUR\n1 - The NDC/NAP/BUR addresses supporting a just transition but there is no focus on the agrifood sector. \n2 - The NDC/NAP/BUR addresses supporting a just transition with a focus on the agrifood sector.\n3 - The NDC/NAP/BUR specifically addresses ensuring a just transition for vulnerable groups of farmers such as smallholder or subsistence farmers, women, indigenous people and traditional land users/informal workers in the agrifood supply."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B90,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A just transition framework within national climate strategies reflects a government’s recognition of the social and economic dimensions of agrifood system transformation. When such frameworks explicitly address vulnerable groups, they help mitigate the risks of production disruptions and labour displacement during periods of climate and structural change. This support enhances the continuity and equity of food production, making political commitment to the just transition a critical enabler of sustained and inclusive food availability."}]
[null,2.2999999999999998,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B91,Lists_indicators!$D$2:$D$106,0))","v":"2.3) Public expenditure on agricultural research and development"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B91,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":4.8},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B91,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B91,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0.51700000000000002},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B91,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B91,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Public agricultural R&D expenditure as a share of agricultural GDP"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Michiel van Dijk et al (2025):\nhttps://www.nature.com/articles/s41597-025-05331-y \nWorld Bank:\nhttps://data.worldbank.org/indicator/NV.AGR.TOTL.CD"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of public-sector support for agriculture-focused R&D"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2021-2023"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B91,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A high ratio indicates a strong public-sector commitment to building a more innovative, productive and shock-resilient supply base, which ensures sufficient, reliable food production."}]
[null,2.4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B92,Lists_indicators!$D$2:$D$106,0))","v":"2.4) Volatility of agricultural production"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B92,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":95},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B92,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B92,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2.1999999999999999E-2},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B92,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B92,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Standard deviation of annual agricultural production growth rates"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/faostat/en/#data/QCL"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the fluctuation in agricultural production, as captured by the standard deviation of the annual growth rates of agricultural production over the most recent five-year period."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2018-2023"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0.006 or below scores 100; a value of 0.3 or above scores 0. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B92,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Fluctuations in agricultural productivity can create difficulty in predicting and planning for a consistent food supply."}]
[null,2.5,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B93,Lists_indicators!$D$2:$D$106,0))","v":"2.5) Growth in productivity of the agricultural sector"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B93,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":52.7},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B93,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B93,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1.06},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B93,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B93,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Five-year average of annual growth in agricultural productivity (%)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"US Department of Agriculture (USDA):\nhttps://www.ers.usda.gov/data-products/international-agricultural-productivity"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of growth in productivity of the agricultural sector. The total factor productivity (TFP), computed by the USDA, takes into account all of the land, labour, capital and material resources employed in farm production, and compares them with the total gross output of crop, animal and aquaculture products. If total output is growing faster than total inputs, this is called an improvement in total factor productivity (\"factor\" = input). To understand the overall trend of year-on-year change in productivity of the agricultural sector, we take a five-year average of the year-on-year change in the TFP of each country between 2017 and 2022."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2017-22"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of -20 or below scores 0; a value of 20 or above scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B93,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"By 2050 the global food system needs to serve an additional 2bn people while utilising the same amount of agricultural inputs. Increasing the efficiency of agricultural input use, as captured through TFP, is therefore critical to improving the availability of food. \nhttps://www.wri.org/insights/how-sustainably-feed-10-billion-people-2050-21-charts"}]
[null,2.6,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B94,Lists_indicators!$D$2:$D$106,0))","v":"2.6) Efficient agrifood supply chains"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B94,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":55.2},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B94,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B94,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B94,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B94,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B94,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B94,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B94,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator tracking the ability of markets, public sector and agrifood supply chain actors beyond the farmgate in delivering sufficient food to the end consumer and fair compensation to all farmers for their output"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B94,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B94,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B94,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"2.6.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B95,Lists_indicators!$D$2:$D$106,0))","v":"2.6.1) Agriculture producer prices"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B95,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":47.9},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B95,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B95,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":9.3780000000000001},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B95,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B95,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"Sub-Saharan Africa regional average"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%, average annual change in the selling prices received by farmers in 2019-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/faostat/en/#data/PP"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of compensation received by farmers for their output. FAO's Producer Price Index (PPI) tracks the selling prices received by farmers (prices at the farmgate or at the first point of sale). To understand the trend in producer prices over time, we calculate the average of annual change in PPI between 2019-2024."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2019-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 20 scores 100. For values up to 20, higher data values produce higher scores. For values of 20 or above, higher data values produce lower scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B95,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Higher agriculture producer prices, measured by the PPI, can indicate that producers are getting more money for the crops they produce. Rising real producer prices signal that farmers are retaining a larger share of value, which in turn improves their ability to cover input costs, adopt new technologies and maintain production levels when shocks occur. Monitoring the PPI therefore captures a core dimension of the Availability pillar: whether price transmission along the supply chain sustains producers and supports reliable food output."}]
[null,"2.6.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B96,Lists_indicators!$D$2:$D$106,0))","v":"2.6.2) Blended market access support for smaller-scale farmers"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B96,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B96,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B96,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B96,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B96,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there evidence of government, multilateral/donor or private sector support to improve market access for smaller-scale farmers or vulnerable groups in the agricultural sector such as smallholder or subsistence farmers, women, indigenous people and other minorities employed in farming?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each element:\n- Evidence of public-sector support. (This could be in the form of preferential public procurement from disadvantaged groups of farmers or quality certification for agricultural outputs.)\n- Evidence of private sector or multilateral/donor support. (This could be in the form of support on processing and packaging of agricultural outputs or contract farming arrangements with downstream value chain actors, such as food manufacturers and supermarkets.)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B96,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Enabling policy mechanisms, multilateral/donor assistance and support from downstream actors in the agrifood sector can level the playing field for disadvantaged groups of farmers, allowing them to have equal opportunities of access to the domestic and international food markets and get a fair price for their farm output. \nhttps://documents1.worldbank.org/curated/en/851711521095180329/pdf/124304-WP-PUBLIC-AgriBookMar.pdf; \nhttps://www.povertyactionlab.org/policy-insight/increasing-small-scale-farmers-access-agricultural-markets"}]
[null,"2.6.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B97,Lists_indicators!$D$2:$D$106,0))","v":"2.6.3) Policy interventions to tackle food loss and waste"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B97,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B97,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B97,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B97,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B97,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Does the country have a dedicated food loss and waste policy/strategy/action plan? Does the country use any regulatory or market-based instruments to address food loss and waste at different levels of the agrifood value chain?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each element:\n- The country has a dedicated food loss and waste policy/strategy/action plan. \n- The country uses regulatory or market-based instruments to address food loss at different levels of the agrifood value chain (ie production, processing and/or distribution). \n- The country uses regulatory or market-based instruments to address food waste at different levels of the agrifood value chain (ie retail, food services and end-user)."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B97,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Policy interventions to tackle food loss improve resource efficiency across the agrifood value chain and food security. Food loss and waste combined account for 8-10% of annual global greenhouse gas (GHG) emissions; therefore, reducing food loss also serves as an emission reduction lever for the agrifood sector. \nhttps://unfccc.int/news/food-loss-and-waste-account-for-8-10-of-annual-global-greenhouse-gas-emissions-cost-usd-1-trillion"}]
[null,"2.6.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B98,Lists_indicators!$D$2:$D$106,0))","v":"2.6.4) Crop storage facilities"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B98,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B98,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B98,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B98,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B98,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there evidence of government, multilateral/donor or private-sector funding to improve crop storage in the past five years?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"1 = Yes\n0 = No\nNote: Investment towards improving crop storage can include active public grain stocks that serve as a strategic grain reserve for countries. \nhttps://documents1.worldbank.org/curated/en/099042625211562573/pdf/P504545-488431b2-0565-40f9-852c-e8db32d22559.pdf"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B98,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Investments to improve or expand crop storage facilities are critical for ensuring there is a sufficient food supply."}]
[null,"2.6.5",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B99,Lists_indicators!$D$2:$D$106,0))","v":"2.6.5) Distribution infrastructure and logistics"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B99,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":37.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B99,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B99,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B99,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B99,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Index score 1-5, where 5 = global best practice"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of national transport and logistics performance using six indicators related to main inputs to the supply chain and supply chain performance outcomes"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. A value of 1 scores 0; a value of 5 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B99,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Strong transport and logistics performance is key to efficiently delivering agricultural and food outputs from the point of procurement to the point of consumption in the agrifood supply chain, while minimising food loss."}]
[null,"2.6.6",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B100,Lists_indicators!$D$2:$D$106,0))","v":"2.6.6) End-to-end cold chain capacity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B100,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B100,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B100,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B100,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B100,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there a dedicated national policy or action plan to improve the country's end-to-end cold chain capacity with a holistic focus on the agrifood sector: primary production; food and drink processing; bulk cold storage; refrigerated transport; food and drink retail; and food service? Is there evidence of public and multilateral/donor or private-sector funding to improve the agrifood sector's end-to-end cold chain capacity in the past five years? \n(Examples of funding can include: development of cold-chain-focused think-tanks at the national level; national cold chain standard-setting body; investment in R&D or scaling of cold chain technology solutions; training institutions; and interventions to improve household refrigeration capacity.)\nhttp://www.foodcoldchain.org/wp-content/uploads/2021/07/GFCCC-UNEP-Cold-Chain-Database-Methodology-Final.pdf"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each of the following cold chain capacity building interventions:\n- Dedicated national policy or action plan to improve the country's end-to-end cold chain capacity with a focus on the agrifood value chain.\n- Evidence of public-sector funding to improve the agrifood sector's end-to-end cold chain capacity in the past five years.\n- Evidence of multilateral/donor or private-sector funding to improve the agrifood sector's end-to-end cold chain capacity in the past five years."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B100,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Investments to understand gaps in the agrifood cold chain and improve national cold chain capacity are critical for ensuring there is a sufficient food supply and minimising food loss from point of procurement to point of consumption."}]
[null,2.7,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B101,Lists_indicators!$D$2:$D$106,0))","v":"2.7) Sufficiency of supply"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B101,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":4.2},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B101,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B101,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B101,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B101,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B101,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B101,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B101,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures the availability of food"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B101,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B101,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B101,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"2.7.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B102,Lists_indicators!$D$2:$D$106,0))","v":"2.7.1) Food supply adequacy"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B102,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":8},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B102,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B102,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":98},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B102,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B102,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%, dietary energy supply as a percentage of the average dietary energy requirement (three-year average)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/faostat/en/#data/FS"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the adequacy of food available for human consumption as captured by average dietary energy supply adequacy (ADESA). To assess ADESA, the FAO calculates dietary energy supply (DES) as a percentage of the average dietary energy requirement for each country. ADESA is calculated as a three-year average to reduce the impact of possible errors in estimated DES, due to the difficulties in properly accounting for stock variations in major foods and to provide a more structural gauge of food supply adequacy."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2021-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B102,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A sufficient supply of available food is essential for ensuring food security. DES as a share of a country’s average dietary energy requirement indicates whether the national food supply provides enough calories to meet population needs. Tracking this ratio therefore captures a core dimension of the Availability pillar: sufficient, reliable calorie availability, as well as signalling how resilient the food system is to supply disruptions."}]
[null,"2.7.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B103,Lists_indicators!$D$2:$D$106,0))","v":"2.7.2) Dependency on chronic food aid"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B103,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B103,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B103,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B103,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B103,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"OECD: \nhttps://data-explorer.oecd.org/vis?fs[0]=Topic%2C0%7CDevelopment%23DEV%23&pg=0&fc=Frequency%20of%20observation&bp=true&snb=87&df[ds]=dsDisseminateFinalCloud&df[id]=DSD_CRS%40DF_CRS&df[ag]=OECD.DCD.FSD&df[vs]=1.4&dq=DAC..1000.100._T._T.D.Q._T..&lom=LASTNPERIODS&lo=5&to[TIME_PERIOD]=false"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of whether a country is a recipient of chronic food aid by assessing the change in average emergency food aid per head received over the past five years"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"1 = Food aid dependency has decreased or remained the same\n0 = Food aid dependency has increased"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B103,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A country that receives large, sustained volumes of emergency food aid signals chronic shortfalls in its domestic food supply. Tracking the five-year trend in per-head food-aid receipts therefore reveals whether the national system can reliably meet caloric needs without external relief—an essential test of supply sufficiency and food-system resilience"}]
[null,2.8,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B104,Lists_indicators!$D$2:$D$106,0))","v":"2.8) Food security and access policy commitments"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B104,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":50},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B104,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B104,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B104,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B104,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-4; 4 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Assesses whether the country has a formal food-security strategy, a dedicated implementing agency, clear implementation arrangements and coverage for vulnerable population groups"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each element:\n- A national food security strategy\n- Inclusion of provisions or considerations for vulnerable groups such as the rural low-income population, young children and indigenous people in the national food security strategy\n- A dedicated agency to implement the national food security strategy\n- An annual budget earmarked for the dedicated agency to implement the national food security strategy"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B104,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A formal, well-resourced national food-security strategy, implemented by a dedicated agency and explicitly covering vulnerable groups, signals that a country can co-ordinate policies, budgets and emergency responses to keep food affordable and accessible, especially during shocks. Tracking the existence and operational strength of these policy commitments therefore reveals whether the food system has the governance capacity to sustain adequate access for all populations."}]
[null,2.9,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B105,Lists_indicators!$D$2:$D$106,0))","v":"2.9) Socio-political risk outlook"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B105,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":23.3},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B105,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B105,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B105,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B105,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator measuring the operational risk environment for the agrifood value chain"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B105,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Security and political stability risks and inherent inefficiencies in governance can lead to ineffective implementation of policies that improve the availability of inputs for the agricultural sector and access to food for consumers. A perception of such socio-political risks can also deter investment from private sector actors in the agrifood sector."}]
[null,"2.9.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B106,Lists_indicators!$D$2:$D$106,0))","v":"2.9.1) Security risk"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B106,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":20.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B106,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B106,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":79.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B106,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B106,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Risk rating 0-100; 100 = highest risk"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EIU Operational Risk (Proprietary EIU research that assesses and quantifies the risks in countries for the next two years. The analysis is based on 70 risk indicators that cover ten separate criteria, including economic, political and regulatory risks. These criteria forecast future risks and consider both qualitative and quantitative factors.) \nhttps://viewpoint.eiu.com/analysis/risk/operational-risk#no-highlight"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"An aggregate security risk rating calculated based on the following underlying risks: armed conflict; cyber security (likelihood of attacks); hostility to foreigners/private property; kidnapping/extortion; organised crime; terrorism; violent crime; and violent demonstrations."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 100 scores 0. A value of 0 scores 100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B106,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Security risks are critical drivers of food insecurity because they disrupt food production, access to markets and livelihoods."}]
[null,"2.9.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B107,Lists_indicators!$D$2:$D$106,0))","v":"2.9.2) Political stability risk"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B107,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":35},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B107,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B107,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":65},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B107,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B107,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Risk rating 0-100; 100 = highest risk"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EIU Operational Risk \nhttps://viewpoint.eiu.com/analysis/risk/operational-risk#no-highlight"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"An aggregate political stability risk rating calculated based on the risk outlook for the following parameters: excessive executive authority; international tensions; opposition stance; orderly transfers; and social unrest"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 100 scores 0. A value of 0 scores 100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B107,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Political instability has the potential to disrupt access to food, eg through transport blockages or reduced food aid commitments."}]
[null,"2.9.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B108,Lists_indicators!$D$2:$D$106,0))","v":"2.9.3) Government effectiveness"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B108,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":12},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B108,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B108,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":88},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B108,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B108,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Risk rating 0-100; 100 = highest risk"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EIU Operational Risk \nhttps://viewpoint.eiu.com/analysis/risk/operational-risk#no-highlight"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"An aggregate rating of government effectiveness based on the following parameters: accountability of public officials; corruption; excessive bureaucracy/red tape; human rights; policy formulation; quality of bureaucracy; and vested interests/cronyism."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 100 scores 0. A value of 0 scores 100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B108,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Government ineffectiveness can impact food availability through distortions and inefficiencies in the use of natural resources, as well as bottleneck inefficiencies in food distribution."}]
[null,3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B109,Lists_indicators!$D$2:$D$106,0))","v":"3) QUALITY AND SAFETY"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B109,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":37.299999999999997},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B109,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B109,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B109,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B109,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B109,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B109,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B109,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Measures the variety and nutritional quality of average diets, as well as the safety of food"}]
[null,3.1,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B110,Lists_indicators!$D$2:$D$106,0))","v":"3.1) Dietary diversity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B110,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":58.4},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B110,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B110,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B110,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B110,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures dietary diversity"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B110,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures dietary diversity"}]
[null,"3.1.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B111,Lists_indicators!$D$2:$D$106,0))","v":"3.1.1) Dietary diversity score (DDS): total"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B111,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":44},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B111,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B111,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":4.4000000000000004},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B111,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B111,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-10; the score ranges from 0-10, expressed as an average score for the population with a higher score indicating the inclusion of more food groups in the diet"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Global Diet Quality Project: https://www.dietquality.org/indicators/dietary-diversity-score-dds/map;\nEFSA Food Consumption Survey: https://www.efsa.europa.eu/en/microstrategy/food-consumption-survey"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The Dietary Diversity Score is the number of food groups consumed in the previous day or night of the following ten food groups: grains, white roots and tubers, and plantains; pulses (beans, peas and lentils); nuts and seeds; dairy; meat, poultry and fish; eggs; dark green leafy vegetables; other vitamin A-rich fruits and vegetables; other vegetables; and other fruits."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2021-23"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. Higher data values produce higher scores. A value of 0 scores 0. A value of 10 scores 100. "},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B111,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Dietary Diversity Score reflects the range of food groups consumed and serves as a proxy for the nutritional adequacy of an individual’s diet. Higher dietary diversity improves resilience by ensuring better overall health, reducing vulnerability to nutrient deficiencies and supporting long-term food system sustainability through diverse food production and consumption. Tracking this score therefore reveals whether populations can reliably access a varied, nutrient-rich diet."}]
[null,"3.1.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B112,Lists_indicators!$D$2:$D$106,0))","v":"3.1.2) Gap in DDS: male vs female"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B112,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":80},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B112,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B112,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0.1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B112,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B112,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Absolute difference in score"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Global Diet Quality Project: https://www.dietquality.org/indicators/dietary-diversity-score-dds/map"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Absolute difference in the total Dietary Diversity Score between men and women from the Global Diet Quality Project"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2021-23"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 or below scores 100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B112,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Globally, chronic malnutrition is more prevalent among women compared with men. The gender gap in Dietary Diversity Score highlights disparities in access to diverse, nutritious foods between men and women. Addressing this gap is essential for building an equitable and resilient food system.\nhttps://scalingupnutrition.org/about/what-we-do/priorities/gender-and-nutrition"}]
[null,"3.1.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B113,Lists_indicators!$D$2:$D$106,0))","v":"3.1.3) Sugary and ultra-processed food consumption: total"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B113,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":49.6},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B113,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B113,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":45},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B113,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B113,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Global Diet Quality Project:\nhttps://www.dietquality.org/indicators/unhealthy-food-consumption/map;\nEUROSTAT: https://ec.europa.eu/eurostat/databrowser/bookmark/48b70c2f-ede8-470d-9af3-89f0438a445d?lang=en&createdAt=2025-09-12T07:45:57Z; https://ec.europa.eu/eurostat/databrowser/view/hlth_ehis_fv7e/default/table?lang=en"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Proportion of the population who consumed either of the following: a) more than one sugary food or beverage or any soft drinks (including baked or grain-based sweets, other sweets, sweetened tea, coffee or milk drinks, fruit juice or fruit drinks, or soft drinks); or b) more than one ultra-processed salty food (including packaged ultra-processed salty snacks, instant noodles, fast food, processed meat or deep-fried food)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2019-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B113,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Higher intake of sugary food or beverages, any soft drinks and/or ultra-processed salty food within the population can indicate higher consumption of non-essential energy-dense foods that are low in nutritional value and increase the risk of negative health outcomes. Systematic reviews show consistent associations between higher ultra-processed food consumption and adverse health outcomes, underscoring the need to monitor these products as a marker of diet quality and safety within resilient food systems.\nhttps://www.bmj.com/content/384/bmj-2023-077310"}]
[null,"3.1.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B114,Lists_indicators!$D$2:$D$106,0))","v":"3.1.4) Sugary and ultra-processed food consumption: male vs female"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B114,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":71.400000000000006},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B114,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B114,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":4},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B114,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B114,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Percentage points (pp)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Global Diet Quality Project:\nhttps://www.dietquality.org/indicators/unhealthy-food-consumption/map;\nEUROSTAT: https://ec.europa.eu/eurostat/databrowser/bookmark/48b70c2f-ede8-470d-9af3-89f0438a445d?lang=en&createdAt=2025-09-12T07:45:57Z; https://ec.europa.eu/eurostat/databrowser/view/hlth_ehis_fv7e/default/table?lang=en"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Absolute difference between the proportion of males and females who consumed either of the following: a) more than one sugary food or beverage or any soft drinks (including baked or grain-based sweets, other sweets, sweetened tea, coffee or milk drinks, fruit juice or fruit drinks, or soft drinks); or b) more than one ultra-processed salty food (including packaged ultra-processed salty snacks, instant noodles, fast food, processed meat or deep-fried food)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2019-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B114,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Tracking the male/female gap in the consumption of sugary and ultra-processed foods highlights unequal exposure to nutrient-poor, energy-dense diets that raise risks of obesity, diabetes and other non-communicable diseases. Including this indicator helps identify where targeted nutrition and education policies are needed to ensure both men and women benefit equally from a safe and healthy food environment."}]
[null,3.2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B115,Lists_indicators!$D$2:$D$106,0))","v":"3.2) Nutritional standards"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B115,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":42},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B115,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B115,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B115,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B115,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures government commitment to increasing nutritional standards"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B115,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures government commitment to increasing nutritional standards"}]
[null,"3.2.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B116,Lists_indicators!$D$2:$D$106,0))","v":"3.2.1) National dietary guidelines"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B116,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B116,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B116,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B116,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B116,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Has the government published and implemented dietary guidelines? Does it have plans in place for their timely re-evaluation? Is there evidence of government engagement to evaluate and revise dietary guidelines based on FAO's food systems-based dietary guidelines methodology?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"3 = The government has published and implemented national dietary guidelines, and has a plan to monitor and evaluate the guidelines/has updated the guidelines in the last five years. Additionally, there is evidence of government engagement to revise national dietary guidelines based on FAO's food systems-based dietary guidelines methodology/The government has revised its dietary guidelines in the last five years based on a food systems-based methodology. \n2 = The government has published and implemented national dietary guidelines, and has a plan to monitor and evaluate the guidelines/has updated the guidelines in the last five years.\n1 = The government has published national dietary guidelines and has implemented them within the last 1-2 years by, for instance, disseminating messages on a balanced and nutritious diet through educational campaigns on TV/radio/internet.\n0 = The government has not published national dietary guidelines."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B116,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Dietary guidelines help to share messaging on balanced and nutritious diets. A food systems-based approach to revising dietary guidelines goes beyond achieving nutritional outcomes. Through a multidisciplinary lens and multisectoral engagement process, it supports populations in adopting a healthier and more sustainable diet and practices that favour, among other outcomes, environmental sustainability and socioeconomic equity. \nhttps://www.unnutrition.org/news/dietary-guidelines-next-generation-takes-sustainability\nhttps://openknowledge.fao.org/server/api/core/bitstreams/20b9fd77-47f5-46f0-bdd9-94f798620368/content (published 2024)"}]
[null,"3.2.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B117,Lists_indicators!$D$2:$D$106,0))","v":"3.2.2) National nutrition plan or strategy"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B117,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B117,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B117,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":3},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B117,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B117,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research based on WHO, FAO and national health ministry documents"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"An assessment of whether the government has a current, published national strategy to identify and meet the different nutritional needs of different population groups in addition to adults: ie children, adults, women and girls, older adults and other disadvantaged communities"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award the following points for each element:\n- Current national nutritional strategy. [1]\n- Current strategy addresses different nutritional needs of:\n--- children [0.5]\n---women and girls [0.5]\n---older adults [0.5]\n---disadvantaged communities [0.5]\nIf a national nutritional strategy is not current but mentions any of the four listed population groups, it gets no points on the indicator. However, the population groups addressed in the outdated nutritional strategy should be mentioned in the justification."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B117,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A comprehensive national nutrition plan or strategy will holistically identify and address different nutritional needs of different population groups in addition to adults: ie children, women and girls, older adults and other disadvantaged communities."}]
[null,"3.2.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B118,Lists_indicators!$D$2:$D$106,0))","v":"3.2.3) Nutrition labelling"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B118,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B118,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B118,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B118,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B118,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research based on WHO, FAO and national health ministry documents"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"An assessment of whether the government requires packaged foods to include nutrition labelling information (nutrient declarations) in accordance with Codex recommendations (calories, protein, carbohydrates, fats, sodium and sugar)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"1 = Yes\n0 = No"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B118,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"In combination with education campaigns and initiatives on nutrition, mandatory nutrition labelling equips consumers with transparent information to make healthier and nutritious food choices, contributing to improving their overall dietary quality."}]
[null,"3.2.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B119,Lists_indicators!$D$2:$D$106,0))","v":"3.2.4) Nutrition monitoring and surveillance"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B119,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":50},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B119,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B119,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B119,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B119,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research based on WHO, FAO and national health ministry documents"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Has the government conducted a study to assess the nutritional status of the general population within the past five years (eg through a survey or ongoing monitoring system)? Is there evidence of public/private/multilateral/donor/blended investment in R&D/pilots/scaling of technology solutions to improve monitoring and surveillance?\n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2 = Yes and there is evidence of public/private/multilateral/donor/blended investment in R&D/pilots/scaling of technology solutions to improve monitoring and surveillance\n1 = Yes\n0 = No"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B119,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Regular nutrition monitoring and surveillance allow governments to pinpoint micronutrient gaps, track emerging diet-related risks and evaluate the impact of interventions. Countries with recent, population-wide nutrition surveys adjust fortification, supplementation and social-protection programmes more effectively."}]
[null,3.3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B120,Lists_indicators!$D$2:$D$106,0))","v":"3.3) Protein quality"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B120,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B120,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B120,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":21.77},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B120,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B120,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Grams of high-quality protein in diet"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation based on data from FAO, WHO and USDA Nutrient Database\nhttps://data360.worldbank.org/en/indicator/FAO_FS_21013?view=datatable"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the amount of high-quality protein in the diet using the methodology of the Protein Digestibility Corrected Amino Acid Score (PDCAAS). This methodology assesses the presence of nine essential amino acids in the average national diet. The inputs for this calculation include: the amino acid profile; protein digestibility value; and the average amount (in grams) consumed of each food item that contributes a minimum of 2% to total protein consumption."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2020-2022"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 or below scores 0; a value of 100 or above scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B120,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Protein supply alone is an insufficient assessment of nutrition; there are nine essential amino acids that humans cannot synthesise and must consume through dietary sources. High-quality protein, measured via the PDCAAS, indicates whether national diets supply the nine indispensable amino acids in forms the body can absorb and utilise. Tracking PDCAAS-based protein quality therefore aligns directly with the pillar’s focus on nutrient adequacy and food safety, signalling whether a food system delivers biologically usable protein essential for resilient, healthy populations."}]
[null,3.4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B121,Lists_indicators!$D$2:$D$106,0))","v":"3.4) Food safety"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B121,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":32.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B121,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B121,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B121,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B121,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures the enabling environment for food safety"},null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100 calculated as the weighted average of the scores of the underlying sub-indicators for this indicator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B121,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures the enabling environment for food safety"}]
[null,"3.4.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B122,Lists_indicators!$D$2:$D$106,0))","v":"3.4.1) Relevant food safety legislation"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B122,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B122,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B122,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B122,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B122,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Has the country enacted food safety legislation? Has this legislation been updated in the past 5-10 years?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2 = Evidence of food safety legislation that has been updated in the past five years\n1 = Evidence of food safety legislation that has been updated within the past ten years\n0 = No evidence of food safety legislation or it has not been updated within the past ten years"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B122,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Timely updates to food safety legislation ensures that food safety mechanisms remain responsive to current and future-facing food safety issues."}]
[null,"3.4.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B123,Lists_indicators!$D$2:$D$106,0))","v":"3.4.2) Food safety mechanisms"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B123,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":20},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B123,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B123,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":20},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B123,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B123,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100; 100 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"WHO, country-reported data:\nhttps://extranet.who.int/e-spar/"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the efficacy of a country's multisectoral collaboration mechanism to manage food safety events and emergencies at national and international scale. According to the WHO, a multisectoral collaboration mechanism for food safety should include all sectors relevant to food safety across national, regional and local government as applicable, and industry, with clearly defined roles and responsibilities, hierarchies and channels of communication between the stakeholders documented. Documented procedures for the detection of, and response to, food safety emergencies should also be specified. These can include: national standards; legislation; guidelines; laboratory capacity assessments; and food recall and tracing plans. \nThis is captured in the country score for Capacity 13 (C13): Food Safety on the WHO's International Health Regulations States Parties Self-Assessment Annual Reporting (SPAR) database. The latest (second) edition of SPAR (2021) contains 15 capacities and 35 indicators:\nhttps://cdn.who.int/media/docs/default-source/health-security-preparedness/cap/spar/9789240040120-eng-new.pdf?sfvrsn=5dc09bd9_3"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 100 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B123,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A multisectoral food-safety mechanism indicates that a country can detect, investigate and manage food-borne hazards quickly and in a co-ordinated way. By ensuring that safe food remains available, even during contamination events, this capacity directly supports the pillar’s goal of providing populations with safe, balanced diets and strengthens overall food-system resilience."}]
[null,"3.4.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B124,Lists_indicators!$D$2:$D$106,0))","v":"3.4.3) Food safety innovation"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B124,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":100},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B124,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B124,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B124,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B124,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there evidence of public/private/multilateral/donor/blended investment in R&D/pilots/scaling of solutions to minimise and improve the scanning and identification of potential food safety risks and response to food safety disaster events?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"0 = No \n1 = Yes"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B124,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Investment in R&D and scaling of innovative solutions is needed to both optimise the operational efficiency of current food safety mechanisms and effectively respond to emerging food safety challenges. Tracking this investment shows whether a food system is moving from basic control towards proactive, technology-enabled safety.\nhttps://openknowledge.fao.org/server/api/core/bitstreams/a21712a8-b125-444e-96eb-b07b057e4fe1/content"}]
[null,"3.4.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B125,Lists_indicators!$D$2:$D$106,0))","v":"3.4.4) Household food safety capacity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B125,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":10.1},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B125,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B125,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B125,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B125,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculations based on data from World Bank, WHO, Global Data Lab and EI country research"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of household capacity to store, prepare and consume food safely"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100; calculated as the weighted average of the scores of the underlying sub-indicators"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B125,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to safely managed drinking water and refrigeration is essential for maintaining household-level food hygiene, enabling the safe storage, preparation and consumption of food."}]
[null,"3.4.4.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B126,Lists_indicators!$D$2:$D$106,0))","v":"3.4.4.1) Access to safely managed drinking water"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B126,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":11.9},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B126,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B126,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":11.872999999999999},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B126,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B126,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"% of population with access to safely managed drinking water services"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Bank, WHO:\nhttps://www.who.int/data/gho/data/indicators/indicator-details/GHO/population-using-safely-managed-drinking-water-services-(-)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the percentage of people using safely managed drinking water services. The Joint Monitoring Programme of the WHO and UNICEF defines safely managed water services as the level of access wherein drinking water from an improved water source is accessible on premises, available when needed and free from faecal and priority chemical contamination. Drinking water is defined as water used by households for drinking, cooking, personal hygiene and other domestic uses."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":4},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B126,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A safely managed water supply is essential for households, both to prepare food safely and as a vital dietary component. \nhttps://www.sciencedirect.com/science/article/pii/S2161831322005191"}]
[null,"3.4.4.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B127,Lists_indicators!$D$2:$D$106,0))","v":"3.4.4.2) Ability to store food safely"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B127,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":8.3000000000000007},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B127,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B127,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":8.27},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B127,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B127,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"% of household with a refrigerator"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Global Data Lab; EI country research:\nhttps://globaldatalab.org/wealth/table/fridge/"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Access to a refrigerator allows households to store food safely and can minimise food waste."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2018-23"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":4},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B127,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Food-borne illnesses can result from various factors, including improper food storage. Refrigeration plays a key role in slowing the growth of bacteria that cause these illnesses. Higher national coverage therefore signals safer domestic food storage, less spoilage and better nutrient retention.\nhttps://www.fsis.usda.gov/food-safety/safe-food-handling-and-preparation/food-safety-basics/refrigeration#:~:text=Refrigeration%20slows%20bacterial%20growth.,of%20bacteria%20can%20cause%20illness."}]
[null,4,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B128,Lists_indicators!$D$2:$D$106,0))","v":"4) CLIMATE RISK RESPONSIVENESS"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B128,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":40},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B128,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B128,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B128,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B128,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B128,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B128,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B128,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Assesses the endurance and responsiveness of the food system to the impacts of climate change. It measures exposure to physical risks, preparedness for disaster events, and progress towards mitigation and adapation efforts aimed at strengthening long-term systemic capacity to manage climate change-related risks."}]
[null,4.0999999999999996,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B129,Lists_indicators!$D$2:$D$106,0))","v":"4.1) Physical risk exposure"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B129,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":55.5},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B129,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B129,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B129,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B129,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B129,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B129,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B129,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures exposure to the impacts of climate change"},null,null,null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B129,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"4.1.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B130,Lists_indicators!$D$2:$D$106,0))","v":"4.1.1) Projected temperature rise"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B130,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":74.400000000000006},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B130,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B130,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1.3720000000000001},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B130,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B130,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Absolute change in the projected annual average temp (°F) between 2020 and 2039, compared with the historic baseline period of 1986-2005"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"University of Chicago Climate Impact Labs:\nhttps://impactlab.org/map"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of projected temperature rise. The projected change is the absolute change in the annual average temperature in 2020-39, compared with the baseline period of 1986-2005, using the moderate emissions scenario SSP2; RCP 4.5 (ie Socioeconomic Pathway (SSP2) with the Representative Concentration Pathway (RCP) 4.5), median probability (0.5). Climate projections are based on the World Climate Research Programme’s Sixth Coupled Model Intercomparison Project (CMIP6)."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B130,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Climate and weather extremes in global warming, drought, flooding and precipitation significantly impact the food sector by increasing demand for agricultural inputs, disrupting crop yields, increasing food prices and ultimately affecting food security for the end consumer.\nhttps://www.sciencedirect.com/science/article/pii/S2212096322000808"}]
[null,"4.1.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B131,Lists_indicators!$D$2:$D$106,0))","v":"4.1.2) Agricultural water risk: quantity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B131,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":13},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B131,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B131,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":4.4800000000000004},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B131,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B131,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Risk score 1-5; 5 = highest risk"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Resources Institute (WRI) Aqueduct:\nhttps://www.wri.org/resources/type/data-52/subtype/data-set-54/tags/aqueduct-19504"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the ratio of total annual water withdrawals to total available annual renewable supply. Data are based on the WRI’s agriculture weighting scheme and is an average of baseline water stress, inter-annual variability, seasonal variability, upstream storage and groundwater stress."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 1 scores 100; a value of 5 scores 0. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B131,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Water quantity risks can lead to a reduced amount of water available for irrigation, leading to a decline in agricultural productivity."}]
[null,"4.1.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B132,Lists_indicators!$D$2:$D$106,0))","v":"4.1.3) Agricultural water risk: quality"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B132,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":42.9},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B132,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B132,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":3.2839999999999998},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B132,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B132,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Risk score 1-5; 5 = highest risk"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"WRI Aqueduct:\nhttps://www.wri.org/resources/type/data-52/subtype/data-set-54/tags/aqueduct-19504"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of the risk that water might be polluted. Data are based on the WRI’s agriculture weighting scheme for return flow ratio and upstream protected land."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 1 scores 100; a value of 5 scores 0. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B132,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Poor water quality as a result of untreated wastewater can lead to nutrient imbalance in the soil and declining crop yields. Additionally, coastal eutrophication can reduce fish stocks and aquaculture yields. \nhttps://www.sciencedirect.com/science/article/pii/S2468584421000945,\nhttps://oceanservice.noaa.gov/facts/eutrophication.html#:~:text=the%20nation's%20estuaries.-,Harmful%20algal%20blooms%2C%20dead%20zones%2C%20and%20fish%20kills%20are%20the,harvests%20and%20more%20expensive%20seafood."}]
[null,"4.1.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B133,Lists_indicators!$D$2:$D$106,0))","v":"4.1.4) Land degradation risk"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B133,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":73.400000000000006},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B133,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B133,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":15.6},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B133,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B133,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Trends.Earth:\nhttps://docs.trends.earth/en/latest/for_users/downloads/index.html; \nhttps://zenodo.org/records/17514520"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The proportion of land that is degraded over total land area. This is a composite indicator, which captures change across three key signals of land degradation: land cover; land productivity; and soil organic carbon stock between 2015 and 2023."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2015-2023"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B133,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A decline in natural land cover classes, land productivity and soil organic carbon content can exacerbate the risk of land degradation. Increased land degradation contributes to lower agricultural productivity."}]
[null,4.2,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B134,Lists_indicators!$D$2:$D$106,0))","v":"4.2) Disaster management"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B134,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":26.2},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B134,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B134,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B134,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B134,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B134,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B134,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B134,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures preparedness for managing climate change-related extreme weather events or disasters"},null,null,null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B134,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"4.2.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B135,Lists_indicators!$D$2:$D$106,0))","v":"4.2.1) Severity of natural disasters"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B135,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":99.7},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B135,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B135,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2E-3},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B135,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B135,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%, average total damages from natural disasters per year (2014-2024) as a share of GDP"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EM-DAT, World Bank:\nhttps://public.emdat.be/data"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of physical risk exposure trend for a given country. The indicator specifically measures the annual average (2014-2024) of direct and indirect total damages from natural disasters as a share of GDP (US dollar 2024 terms)."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2014-24"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B135,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The cost of natural disasters to countries over the past decade serves as a measure of intensity of the economic and social impacts for all sectors of the economy, including agrifood."}]
[null,"4.2.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B136,Lists_indicators!$D$2:$D$106,0))","v":"4.2.2) Maturity of mutli-hazard early warning systems"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B136,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":45},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B136,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B136,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0.45},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B136,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B136,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"Least developed countries (LDCs) average"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best; continuous"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Sendai Monitor, UN Office for Disaster Risk Reduction (UNDRR):\nhttps://sendaimonitor.undrr.org/\nhttps://sendaimonitor.undrr.org/analytics/global-targets-all/21 "},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of availability and access to comprehensive multi-hazard early warning systems. Scores on Target G: Early Warning of the Sendai Framework for Disaster Risk Reduction track performance on five underlying indicators measuring: presence of multi-hazard early warning systems; presence of monitoring and forecasting systems; number of people per 100,000 of population covered by early warning information; share of local governments with plans to act on early warnings; and availability of understandable and usable disaster risk and assessment information. \n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 1 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B136,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Mature early-warning systems allow countries to effectively monitor, forecast and disseminate information on impending disaster risks. It can prepare countries to better withstand the immediate impacts of disasters, contain damage, prevent cascading effects and expeditiously set recovery in motion for the food sector."}]
[null,"4.2.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B137,Lists_indicators!$D$2:$D$106,0))","v":"4.2.3) Adoption and implementation of national and local disaster risk reduction strategy"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B137,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B137,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B137,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B137,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B137,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1= best; continuous"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Sendai Monitor, UNDRR:\nhttps://sendaimonitor.undrr.org/"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of adoption and implementation of national and local disaster risk reduction strategy, as captured by the composite score on Target E: Strategy of the Sendai Framework for Disaster Risk Reduction."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2017-2023"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 1 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B137,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Adoption and implementation of comprehensive disaster risk reduction strategies at national level, as well as local level co-ordination on these, can prepare countries to better withstand the immediate impacts of disasters, contain damage, prevent cascading effects, expeditiously set recovery in motion and identify opportunities to build back better for the food sector."}]
[null,"4.2.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B138,Lists_indicators!$D$2:$D$106,0))","v":"4.2.4) Pest infestation and disease management"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B138,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B138,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B138,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B138,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B138,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-2; 2 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI country research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there a national policy in place to mitigate the risk of pest infestation and infections from diseases on production and respond to pest infestation disaster events?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"0 = No evidence of a national policy\n1 = Evidence of a national policy on mitigating risks of pest infection and/or responding to pest infestation disaster events, but no or only partial budget allocation\n2 = Evidence of a national policy on mitigating risks of pest infection and responding to pest infestation disaster events and an annual budget allocated/earmarked for the implementation of the policy"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B138,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Climate change will exacerbate the spread of invasive species, ie pests. A targeted national policy and earmarked annual budget to mitigate the risk of pest infestation and infections by diseases and pest-related disaster response strategy can allow countries to better manage the risk and impact of such events. \nhttps://www.unepfi.org/wordpress/wp-content/uploads/2023/03/Agriculture-Sector-Risks-Briefing.pdf"}]
[null,4.3,{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B139,Lists_indicators!$D$2:$D$106,0))","v":"4.3) Mitigation and adaptation"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B139,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":37.299999999999997},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B139,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B139,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":""},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B139,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B139,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B139,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B139,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B139,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A composite indicator that measures progress towards mitigation and adaptation efforts aimed at strengthening long-term systemic capacity of food systems to manage climate change-related risks"},null,null,null,{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B139,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":2}]
[null,"4.3.1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B140,Lists_indicators!$D$2:$D$106,0))","v":"4.3.1) Political commitment to mitigation and adaptation"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B140,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":61.3},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B140,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B140,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":5.5170000000000003},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B140,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B140,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-9"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"CGIAR Research Programme on Climate Change, Agriculture and Food Security database:\nhttps://hdl.handle.net/10568/115962 "},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of political commitment to climate change mitigation and adaptation as captured in the country's NDC: specifically, the underlying data track if a country's NDC contains mitigation and adaptation measures for the agricultural sector under three categories: livestock, soil carbon and rice. These three categories make up the largest pools of emissions for the agricultural sector. \nhttps://www.wri.org/insights/4-charts-explain-greenhouse-gas-emissions-countries-and-sectors"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 9 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B140,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"National commitments are a sign of political will and investments towards reducing emissions from the agriculture sector and adapting the sector to withstand future climate change-related physical risks."}]
[null,"4.3.2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B141,Lists_indicators!$D$2:$D$106,0))","v":"4.3.2) Climate finance aid flows to agriculture"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B141,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":17.2},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B141,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B141,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1.056},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B141,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B141,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"US$ per head"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"OECD RioMarkers: Aid activities targeting global environmental objectives dataset:\nhttps://data-explorer.oecd.org/vis"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of climate mitigation- and adaptation-related aid for the agriculture, forestry and fisheries sector that is allocated to recipient countries. Calculated by taking the annual average of aid received by recipient countries between 2021 and 2023"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B141,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"For donor countries, contributing to climate finance aid for agriculture indicates commitment towards promoting sustainable agriculture globally. For aid recipient countries, higher flows of climate finance aid for the agricultural sector indicate commitment to implementing climate mitigation and adaptation measures domestically."}]
[null,"4.3.3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B142,Lists_indicators!$D$2:$D$106,0))","v":"4.3.3) Mainstreaming sustainable agriculture practices"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B142,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":33.299999999999997},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B142,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B142,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B142,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B142,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI research (proprietary research using publicly available data sources)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Is there evidence of public-sector support to promote sustainable agricultural practices particularly in the context of fertiliser application, livestock management and soil management?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"0 = No evidence of provision of public-sector support\n1 = Evidence of public-sector support for promoting sustainable agricultural practices in one of the three areas: fertiliser application; livestock management; and soil management\n2 = Evidence of public-sector support for promoting sustainable agricultural practices in two of the three areas: fertiliser application; livestock management; and soil management \n3 = Evidence of public-sector support for promoting sustainable agricultural practices in all three areas: fertiliser application; livestock management; and soil management\nAward 0.5 points at each level if there is evidence of policy but no public-sector financial and/or technical support."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B142,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Public-sector support in the form of financial and technical assistance to enable mainstream adoption of sustainable agricultural practices—specifically those related to fertiliser application, livestock management and soil management—can both mitigate emissions from the agrifood sector and prepare the sector for future phyiscal risks.\nIn addition to carbon dioxide (CO2) emissions, nitrous oxide (N2O) emissions from fertiliser use and methane (CH4) emissions from livestock and carbon-intensive soil management practices are critical sources of emissions from the agricultural sector. These also make up a significant share of scope 3 emissions of all downstream participants of the agrifood value chain.\nhttps://www.cifor-icraf.org/publications/pdf_files/OccPapers/CIFOR-ICRAF-OP-3.pdf, https://cdn.cdp.net/cdp-production/cms/guidance_docs/pdfs/000/003/504/original/CDP-technical-note-scope-3-relevance-by-sector.pdf?1649687608"}]
[null,"4.3.4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B143,Lists_indicators!$D$2:$D$106,0))","v":"4.3.4) Change in GHG emissions from the agrifood sector"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B143,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":42.8},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B143,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B143,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":2.5070000000000001},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B143,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B143,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI calculation based on FAO data:\nhttps://www.fao.org/faostat/en/#data/GT"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of change in total GHG emissions from the agrifood sector in 2005-07 and 2022 (latest period available). The compounded annual growth rate of emissions is calculated between 2005-07 and 2022. All major GHG emissions (CO2, CH4, N2O and fluorinated gases) from the agrifood sector (before, during and post-production) are accounted for. \nThe baseline period of 2005-07 is chosen in line with FAO's calculation period (see page 11): https://openknowledge.fao.org/server/api/core/bitstreams/121cc613-3d0f-431c-b083-cc2031dd8826/content#:~:text=FAO%20estimates%20of%20the%20emissions,soils%20(1990%E2%80%932021)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2005-07 (baseline); 2022"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B143,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The food sector is responsible for approximately a third of the total global pool of emissions. GHG emissions exacerbate the food sector's physical risk exposure. To manage this risk, it is important for the sector to lower its emissions."}]
[null,"4.3.5",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B144,Lists_indicators!$D$2:$D$106,0))","v":"4.3.5) Projected ocean health for aquaculture"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B144,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":40},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B144,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B144,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":40.03},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B144,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B144,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Global Ocean Health Index (global scenarios data for Ocean Health Index, University of California, Santa Barbara):\nhttps://oceanhealthindex.org/global-scores/goal-scores/food-provision/"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of future ocean health in the context of food provision. The underlying metric is the score awarded to countries on the sub-goal of Food Provision under the ten goals tracked by the Ocean Health Index. The food provision goal specifically measures the amount of seafood sustainably harvested or grown for human consumption from wild-caught commercial fisheries and mariculture. We take the \"Likely future status\" score, which is the predicted status score five years into the future (on a scale of 0-100). This is estimated by adjusting the current status score by three variables:\nTrend: the change in a goal’s status observed over the most recent five years.\nPressures: the ecological and social factors that decrease a goal’s status.\nResilience: ecological factors and social initiatives (policies, laws, etc) that mitigate the pressures acting on a goal."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 100 scores 100. Higher data values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B144,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Socioeconomic and ecological pressures affecting ocean health can reduce aquaculture yields, putting future food supplies at risk."}]
[null,"4.3.6",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B145,Lists_indicators!$D$2:$D$106,0))","v":"4.3.6) Change in risk of biodiversity loss"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B145,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":88},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B145,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B145,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0.88},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B145,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B145,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-1; 1 = best; continuous"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"International Union for Conservation of Nature (IUCN) Red List Index (RLI): https://www.iucnredlist.org/statistics; \nOur World In Data: https://archive.ourworldindata.org/20250909-093708/grapher/red-list-index.html"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A measure of change in the risk of biodiversity loss. The RLI measures the change in aggregate extinction risk across groups of species. It is based on genuine changes in the number of species in each category of extinction risk on the IUCN Red List of Threatened Species. An RLI value of 1.0 equates to all species qualifying as \"Least Concern\" (ie not expected to become extinct in the near future). An RLI value of 0 equates to all species having become extinct."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 1 scores 100. Higher data values produce higher scores.\n\nThe RLI shows trends in overall extinction risk for species, and is used by governments to track their progress towards targets for reducing biodiversity loss (https://www.iucnredlist.org/assessment/red-list-index). An RLI value of 1.0 equates to all species qualifying as \"Least Concern\". EI has translated the index to a scale of 0-100."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B145,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Biodiversity offers a genetic pool for developing resilient and sustainable food crops, livestock and marine species. It plays a crucial role in breeding varieties resistant to pests, diseases and climate extremes. Therefore, conserving environmental biodiversity is critical to improving the capacity of food systems to sustain and adapt to the impacts of climate risks. \nhttps://www.who.int/news-room/fact-sheets/detail/biodiversity#:~:text=Healthy%20diets%20with%20adequate%20nutrient,food%20security%20and%20public%20health."}]
[null,"4.3.7",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B146,Lists_indicators!$D$2:$D$106,0))","v":"4.3.7) Public and blended sector support for low-emissions R&D in the agrifood sector"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B146,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":33.299999999999997},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B146,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B146,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":1},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B146,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B146,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI research"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Does the government offer any targeted financial support for the R&D of low-emissions solutions for the agrifood sector? Are there any incubators and innovation sandboxes supported by the public or blended sector to develop and pilot early-stage low-emissions solutions for the agrifood sector?"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each:\n- There is a national policy document (strategy/action plan) promoting R&D of low-emissions solutions for the agrifood sector.\n- The government offers targeted financial support for R&D of low-emissions solutions for the agrifood sector in the form of subsidies/tax incentives/grants.\n- The public and/or blended sector provides dedicated technical support to enable the development, pilot and demos of R&D of low-emissions solutions for the agrifood sector via innovation incubators and/or sandboxes."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B146,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Public and blended sector support is necessary to de-risk and promote investment in the research, development and piloting of early stage low-emissions solutions that can enable the agrifood sector to mitigate its GHG footprint and to adapt to the impacts of climate change.\nhttps://cgspace.cgiar.org/server/api/core/bitstreams/e5bf31f5-7f05-4e80-ae1d-c98e974fc00a/content"}]
[null,"4.3.8",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B147,Lists_indicators!$D$2:$D$106,0))","v":"4.3.8) Financial services support for low-emissions R&D in the agrifood sector"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B147,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":0},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B147,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B147,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B147,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B147,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Qualitative rating 0-3; 3 = best"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"EI research"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Composite indicator tracking different underwriting and financing services offered by insurers, banks and private equity/venture capital to support the research and development of low-emissions solutions for the agrifood sector"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2025},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Award one point for each: \n- Banks provide multiple options of financial instruments to support R&D of low-emissions solutions for the agrifood sector. \n- Insurers provide multiple types of underwriting products and coverage options to support R&D of low-emissions solutions for the agrifood sector. \n- Evidence of venture capital/private equity/private credit investment deals in start-ups researching and developing low-emissions solutions for the agrifood sector in the last five years."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":3},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B147,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Support from financial services in the form of innovative financing and risk management mechanisms is necessary to promote the research and development of low-emissions solutions that can enable the agrifood sector to mitigate its GHG footprint and to adapt to the impacts of climate change.\nhttps://cgspace.cgiar.org/server/api/core/bitstreams/e5bf31f5-7f05-4e80-ae1d-c98e974fc00a/content"}]
[null,"BG","BACKGROUND INDICATORS"]
[null,"BG1",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B149,Lists_indicators!$D$2:$D$106,0))","v":"BG1) Food loss and waste"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B149,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B149,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B149,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":6.7910000000000004},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B149,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B149,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/faostat/en/#data/FBS"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Total amount of food lost or wasted across the food supply chain from production to household consumption as a percentage of total domestic food supply"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B149,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The indicator serves as an outcome metric for inefficiencies in the food value chain, which ultimately impacts availability of food."}]
[null,"BG2",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B150,Lists_indicators!$D$2:$D$106,0))","v":"BG2) Environmental Performance Index"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B150,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B150,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B150,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":39.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B150,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B150,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Yale Center for Environmental Law & Policy:\nhttps://epi.yale.edu/measure/2024/epi"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The 2024 EPI combines 58 indicators across 11 issue categories, ranging from climate change mitigation and air pollution to waste management, sustainability of fisheries and agriculture, deforestation and biodiversity protection."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 100 scores 100. Higher values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B150,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The EPI provides a composite measure of how well countries manage key sustainability challenges, including air and water quality, biodiversity and climate change. Higher EPI scores signal stronger environmental stewardship, which underpins long-term food system resilience and security."}]
[null,"BG3",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B151,Lists_indicators!$D$2:$D$106,0))","v":"BG3) Prevalence of undernourishment"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B151,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B151,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B151,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":38.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B151,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B151,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/sustainable-development-goals-data-portal/data/indicators/2.1.1-prevalence-of-undernourishment/en"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The proportion of the population who do not receive the minimum number of required calories for an average person, as defined by the FAO/WHO/UNU Expert Consultation in 2001"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B151,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The indicator serves as an outcome metric gauging access to healthy and nutritious diets for all."}]
[null,"BG4",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B152,Lists_indicators!$D$2:$D$106,0))","v":"BG4) Prevalence of severe food insecurity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B152,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B152,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B152,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":42.5},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B152,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B152,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"FAO:\nhttps://www.fao.org/sustainable-development-goals-data-portal/data/indicators/212-prevalence-of-moderate-or-severe-food-insecurity-in-the-population-based-on-the-food-insecurity-experience-scale/en"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"An estimate percentage of population who live in households classified as severely food insecure by the FAO."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2018-2023"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B152,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Reducing food insecurity is both an input variable to and outcome a more resilient food system."}]
[null,"BG5",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B153,Lists_indicators!$D$2:$D$106,0))","v":"BG5) Percentage of children stunted"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B153,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B153,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B153,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":44.7},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B153,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B153,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"WHO: \nhttps://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-jme-country-children-aged-5-years-stunted-(-height-for-age--2-sd)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The percentage of children under five years who have a height-for-age less than minus-two standard deviations of the National Centre for Health Statistics (NCHS)/WHO reference median"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2018-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B153,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The indicator serves as an outcome metric gauging access to healthy and nutritious diets for children."}]
[null,"BG6",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B154,Lists_indicators!$D$2:$D$106,0))","v":"BG6) Percentage of children underweight"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B154,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B154,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B154,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":24.021999999999998},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B154,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B154,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"WHO: \nhttps://www.who.int/data/gho/data/indicators/indicator-details/GHO/gho-jme-underweight-prevalence"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The percentage of children under five years who have a weight-for-age less than minus-two standard deviations of the NCHS/WHO reference median"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2022},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B154,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The indicator serves as an outcome metric gauging access to healthy and nutritious diets for children."}]
[null,"BG7",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B155,Lists_indicators!$D$2:$D$106,0))","v":"BG7) Prevalence of obesity"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B155,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B155,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B155,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":6.64},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B155,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B155,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"WHO: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-obesity-among-adults-bmi-=-30-(age-standardized-estimate)-(-)"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Measures the percentage of the population, over 18 years of age, that is obese. Obesity is defined as having an age-standardised body mass index greater than 30.0."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2022},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B155,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The indicator serves as an outcome metric gauging access to healthy and nutritious diets for the population."}]
[null,"BG8",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B156,Lists_indicators!$D$2:$D$106,0))","v":"BG8) Prevalence of anaemia among women of reproductive age (% of women aged 15-49)"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B156,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B156,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B156,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":40},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B156,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B156,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Bank: https://data.who.int/indicators/i/41D099F/8D58801\n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The percentage of women aged 15 to 49 with a haemoglobin concentration less than 120 g/L for non-pregnant women and lactating women, and less than 110 g/L for pregnant women, adjusted for altitude and smoking"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B156,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The indicator serves as an outcome metric gauging access to healthy and nutritious diets for women."}]
[null,"BG9",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B157,Lists_indicators!$D$2:$D$106,0))","v":"BG9) Human Development Index"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B157,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B157,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B157,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":0.52200000000000002},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B157,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B157,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-1"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"UN Development Programme: http://hdr.undp.org/en/data\n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"The HDI is a summary measure of average achievement in key dimensions of human development: a long and healthy life; being knowledgeable; and having a decent standard of living. The HDI is the geometric mean of normalised indices for each of the three dimensions."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2023},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Higher values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B157,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"A higher HDI score indicates better education, health, and income outcomes critical to accessing to affordable and nutritious diets."}]
[null,"BG10",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B158,Lists_indicators!$D$2:$D$106,0))","v":"BG10) GDP growth per capita"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B158,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B158,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B158,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":3.2719999999999998},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B158,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B158,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"%"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"World Bank: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG\n"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Denotes the percentage change in GDP per capita over each previous year of the constant price (base year 2015) series in US$"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":2024},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 or below scores 0. Above 0, higher values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"High = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B158,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Growth in GDP per capita can signal both rising productivity in the agricultural sector and improved food availability and affordability for consumers."}]
[null,"BG11",{"$f":"INDEX(Lists_indicators!$F$2:$F$106,MATCH($B159,Lists_indicators!$D$2:$D$106,0))","v":"BG11) GINI coefficient"},null,{"$f":"IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH($B159,'SCORE TABLE'!$B$10:$B$101,0), MATCH($C$13,'SCORE TABLE'!$H$9:$BO$9,0)),1),\"Not scored\")","v":"Not scored"},null,{"$f":"IF(INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B159,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0))=\"\",\"\",INDEX('DATA TABLE'!$M$10:$BT$117, MATCH($B159,'DATA TABLE'!$B$10:$B$117,0), MATCH($C$13,'DATA TABLE'!$M$9:$BT$9,0)))","v":44.7},{"$f":"IF(INDEX(Data_summary!$E$3:$BL$106, MATCH($B159,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0))=\"\",\"\",INDEX(Data_summary!$E$3:$BL$106, MATCH($B159,Data_summary!$C$3:$C$106,0),MATCH($C$13,Data_summary!$E$2:$BL$2,0)))","v":""},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(I$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Score 0-100"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(J$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Gini index: https://data.worldbank.org/indicator/SI.POV.GINI"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(K$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(L$55,'DATA TABLE'!$D$9:$L$9,0))","v":"2020-2024"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(M$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Min-max normalisation; linear transformation of data values to score scale 0-100. Lower values produce higher scores."},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(N$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Low = good"},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(O$55,'DATA TABLE'!$D$9:$L$9,0))","v":0},{"$f":"INDEX('DATA TABLE'!$D$10:$L$113,MATCH(COUNTRIES!$B159,'DATA TABLE'!$B$10:$B$113,0),MATCH(P$55,'DATA TABLE'!$D$9:$L$9,0))","v":"Gini coefficient measures economic inequality, a key factor influencing a population's ability to access and afford food."}]
[null,"BG12"]
[null,"BG13"]

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[222,"2.1.4","Adoption of agritech solutions","Qualitative rating 0-3; 3=best","EI country research (proprietary research using publicly available data sources)","Is there a national policy/action plan to promote adoption of mature agritech solutions? Is there evidence of public, private, multilateral or blended funding mechanisms to promote adoption of mature agritech solutions? Does the national policy/action plan or the targeted funding mechanism focus on disadvantaged groups of farmers?",2025,"Award 1 point for each element: \n- There exists a national policy/action plan to promote adoption of agritech solutions (such as farm equipment and high-quality seeds)\n- There is evidence of a current targeted funding mechanism (not a one-off programme/pilot) supported by the public, private, multilateral or blended sectors to promote adoption of agritech solutions. \n- The existing national policy/action plan or targeted funding mechanism promoting the adoption of agritech solutions has a special focus on disadvantaged groups of farmers (smallholders, subsistence, youth, women and/or other minorities)","Qual","High = good",3,"Widespread adoption of mature agritech solutions such as but not limited to high-quality seeds and farm equipment such as tractors, power tillers, combine harvesters, seeders, sprayers is fundamental to increasing crop yields and improving the reliability of agricultural production. Policies and funding mechanisms that focus on making these solutions accessible to farmers, particularly disadvantaged groups such as ie, smallholders, subsistence, youth, women and other country-specific underserved minorities, contribute to increasing the availability of nutritious food and raise incomes of workers in the agriculture sector. 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[251,"2.2.1","Employment in agriculture: youth vs total population","Percentage points (pp)","ILOSTAT, World Bank, National sources:\n\nhttps://rshiny.ilo.org/dataexplorer05/?lang=en&segment=indicator&id=EMP_3EMP_SEX_AGE_OCU_NB_A\n\nhttps://data.worldbank.org/indicator/SL.AGR.EMPL.ZS","A measure of youth employed (aged 15-29) in agricultural sector compared to the overall population. A percentage point difference is calculated between the share of working-age youth (aged 15-29) employed as “market-oriented skilled agricultural workers\" and the share of total working population employed as “market-oriented skilled agricultural workers\". Values less than 0 indicate that youth workers are underrepresented compared to the overall working population in the agricultural sector.","2020-2024","Threshold-adjusted linear transformation of data values to score scale 0-100. Higher data values produce higher scores upto 0. A value of 0 or above scores 100.","Quant","High = good",3,"A higher participation rate of youth in farming is crucial for resilient food systems because it ensures the continuation of agricultural knowledge and practices, introduces innovation and technological advancements and addresses the challenges of an ageing farming population. Young people are essential for the long-term sustainability and adaptability of food production, especially as the world faces increasing demands and climate change 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[322,"3.2.3","Nutrition labelling","Qualitative rating 0-1; 1 = best","EI country research based on WHO, FAO and national health ministry documents","An assessment of whether the government requires packaged foods to include nutrition labelling information (nutrient declarations) in accordance with Codex recommendations (calories, protein, carbohydrates, fats, sodium and sugar)",2025,"1 = Yes\n0 = No","Qual","High = good",3,"In combination with education campaigns and initiatives on nutrition, mandatory nutrition labelling equips consumers with transparent information to make healthier and nutritious food choices, contributing to improving their overall dietary 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[null,"4.3.6","Change in risk of biodiversity loss","Qualitative rating 0-1; 1 = best; continuous","International Union for Conservation of Nature (IUCN) Red List Index (RLI): https://www.iucnredlist.org/statistics; \nOur World In Data: https://archive.ourworldindata.org/20250909-093708/grapher/red-list-index.html","A measure of change in the risk of biodiversity loss. The RLI measures the change in aggregate extinction risk across groups of species. It is based on genuine changes in the number of species in each category of extinction risk on the IUCN Red List of Threatened Species. An RLI value of 1.0 equates to all species qualifying as \"Least Concern\" (ie not expected to become extinct in the near future). An RLI value of 0 equates to all species having become extinct.",2024,"Threshold-adjusted linear transformation of data values to score scale 0-100. A value of 0 scores 0; a value of 1 scores 100. Higher data values produce higher scores.\n\nThe RLI shows trends in overall extinction risk for species, and is used by governments to track their progress towards targets for reducing biodiversity loss (https://www.iucnredlist.org/assessment/red-list-index). An RLI value of 1.0 equates to all species qualifying as \"Least Concern\". EI has translated the index to a scale of 0-100.","Quant","High = good",3,"Biodiversity offers a genetic pool for developing resilient and sustainable food crops, livestock and marine species. It plays a crucial role in breeding varieties resistant to pests, diseases and climate extremes. Therefore, conserving environmental biodiversity is critical to improving the capacity of food systems to sustain and adapt to the impacts of climate risks. 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["B272","B2.7.2","Justification of wife-beating among male adolescents","What proportion of male adolescents believe that wife-beating is justified under certain circumstances?","UNICEF","Percentage of boys aged 15–19 who consider a husband justified in hitting or beating his wife for at least one of the specified reasons (e.g. if his wife burns the food, argues with him, goes out without telling him, neglects the children or refuses sexual relations)","%; lower=better",2024,null,null,null,"https://data.unicef.org/topic/child-protection/violence/attitudes-and-social-norms-on-violence/ "]
["B273","B2.7.3","Justification of wife-beating among female adolescents","What proportion of female adolescents believe that wife-beating is justified under certain circumstances?","UNICEF","Percentage of girls aged 15–19 who consider a husband justified in hitting or beating his wife for at least one of the specified reasons (e.g. if his wife burns the food, argues with him, goes out without telling him, neglects the children or refuses sexual relations)","%; lower=better",2024,null,null,null,"https://data.unicef.org/topic/child-protection/violence/attitudes-and-social-norms-on-violence/ "]

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[null,"Score table"]
[]
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 ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Q$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":90},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!R$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!R$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!R$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":95},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!S$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!S$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!S$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":84},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!T$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!T$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!T$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":88},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!U$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!U$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!U$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":42},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!V$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!V$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!V$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":92},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!W$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!W$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!W$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":90},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!X$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!X$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!X$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":57},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Y$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Y$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Y$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":79},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Z$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Z$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!Z$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":95},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AA$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AA$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AA$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":83},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AB$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AB$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AB$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":89},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AC$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AC$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AC$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":79},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AD$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AD$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AD$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":0},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AE$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AE$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AE$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":92},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AF$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AF$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AF$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":91},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AG$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AG$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AG$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":98},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AH$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AH$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AH$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":91},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AI$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AI$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AI$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":95},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AJ$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AJ$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AJ$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":57},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AK$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AK$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AK$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":79},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AL$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AL$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AL$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":95},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AM$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AM$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AM$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":94},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AN$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AN$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AN$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":94},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AO$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AO$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AO$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":66},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AP$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AP$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AP$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":83},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AQ$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AQ$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AQ$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":88},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AR$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AR$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AR$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":90},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AS$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AS$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AS$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":81},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AT$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AT$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AT$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":45},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AU$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AU$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AU$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":99},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AV$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AV$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AV$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":86},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AW$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AW$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AW$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":75},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AX$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AX$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AX$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":64},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AY$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AY$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AY$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":77},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AZ$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AZ$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!AZ$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":0},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BA$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BA$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BA$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":95},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BB$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BB$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BB$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":62},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BC$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BC$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BC$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":76},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BD$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BD$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BD$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":87},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BE$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BE$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BE$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":89},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BF$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BF$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BF$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":63},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BG$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BG$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BG$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":61},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BH$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BH$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BH$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":93},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BI$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BI$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BI$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":51},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BJ$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BJ$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BJ$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":77},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BK$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BK$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BK$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":74},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BL$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BL$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BL$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":82},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BM$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BM$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BM$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":58},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BN$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BN$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BN$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  ),\n0)","v":78},{"$f":"IFERROR(\n  IF(\n    INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BO$9,'DATA TABLE'!$M$9:$BT$9,0)) <= $F46,\n    100,\n    IF(\n      INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BO$9,'DATA TABLE'!$M$9:$BT$9,0)) >= $G46,\n      0,\n      ROUND(\n        (($G46 - INDEX('DATA TABLE'!$M$10:$BT$117, MATCH('SCORE TABLE'!$B46,'DATA TABLE'!$B$10:$B$117,0), MATCH('SCORE TABLE'!BO$9,'DATA TABLE'!$M$9:$BT$9,0))) / ($G46 - $F46)) * 100,\n        0\n      )\n    )\n  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[null,"BG5"]
[null,"BG13"]

{"sheet":"Data_summary","index":7,"n_rows":106,"n_cols":64,"rows_kept":106,"cut":false,"hidden":false,"merged":[]}
["Data - summary"]
[null,"UID","No.","Indicator name","Algeria","Argentina","Australia","Bangladesh","Belgium","Brazil","Canada","Chile","China","Colombia","Congo (Democratic Republic)","Costa Rica","Czech Republic","Denmark","Egypt","Ethiopia","France","Germany","Ghana","Greece","Guatemala","Honduras","Hungary","India","Indonesia","Israel","Italy","Japan","Jordan","Kenya","Lebanon","Malaysia","Mexico","Namibia","Netherlands","Nicaragua","Nigeria","Pakistan","Paraguay","Peru","Philippines","Poland","Portugal","Qatar","Romania","Rwanda","Saudi Arabia","Singapore","South Africa","South Korea","Spain","Sri Lanka","Tanzania","Thailand","Turkey","Uganda","United Arab Emirates","United Kingdom","United States","Vietnam"]
[null,null,0,"RESILIENT FOOD SYSTEMS ENVIRONMENT"]
[null,null,1,"AFFORDABILITY"]
[null,null,1.1000000000000001,"Change in average food costs",null,null,null,null,null,null,null,null,null,null,"General consumer price index (CPI) from EIU was used as the FAO food CPI dataset for Congo (Democratic Republic) was only available up to 2017. \nhttps://viewpoint.eiu.com/data/results?searchId=140b5b6c-771e-436a-8dc7-333e87ac9b0b#"]
[null,null,1.2,"Affordability of a healthy diet",null,"Estimated the affordability of a healthy diet in Argentina as the latest data for the cost of a healthy diet for the country is from 2017. We have taken a midpoint between the inflation-adjusted cost of a healthy diet in Argentina (2017-2024) and the average of the cost of a healthy diet in Paraguay, Brazil, Colombia, Dominican Republic, Ecuador, El Salvador, Jamaica, Mexico and Peru (upper middle income economies of Latin American countries [LAC]) in 2024.",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Latest year of data available for the cost of a healthy diet",null,null,null,null,"Latest year of data available for the cost of a healthy diet",null,null,null,null,null,null,null,null,null,null,null,null,null,"Latest year of data available for the cost of a healthy diet"]
[null,null,1.3,"Affordability of a healthy diet to bottom 40%",null,"Estimated the affordability of a healthy diet in Argentina as the latest data for the cost of a healthy diet for the country is from 2017. We have taken the average of the cost of a healthy diet in Paraguay, Brazil, Colombia, Mexico and Peru (upper middle income economies of LAC covered in the index).",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Latest year of data available for the cost of a healthy diet",null,null,null,null,"Latest year of data available for the cost of a healthy diet",null,null,null,null,null,null,null,null,null,null,null,null,null,"Latest year of data available for the cost of a healthy diet"]
[null,null,1.4,"Agricultural trade"]
[null,null,"1.4.1","Agricultural import tariffs","Latest year of data available. Extracted from WTO data: https://www.wto.org/english/res_e/statis_e/daily_update_e/tariff_profiles/DZ_E.pdf",null,null,null,"Most favoured nation (MFN) applied tariff for the European Union (EU)",null,null,null,null,null,"Latest year of data available",null,"MFN applied tariff for the European Union","MFN applied tariff for the EU","Latest year of data available","Latest year of data available","MFN applied tariff for the EU","MFN applied tariff for the EU",null,"MFN applied tariff for the EU",null,null,"MFN applied tariff for the EU",null,null,null,"MFN applied tariff for the EU",null,null,null,null,null,null,null,"MFN applied tariff for the EU",null,null,null,null,null,null,"MFN applied tariff for the EU","MFN applied tariff for the EU",null,"MFN applied tariff for the EU",null,null,null,null,null,"MFN applied tariff for the EU"]
[null,null,"1.4.2","Agricultural and food products import non-tariff measures (NTMs)",null,null,null,"According to WTO's Integrated Trade Intelligence Portal (I-TIP) dataset, Bangladesh has imposed three NTMs in total and none of these apply to agrifood goods (Harmonised System [HS] product codes 1-24).",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Number of NTMs imposed by the EU",null,null,null,null,null,null,null,null,null,null,null,null,null,"According to WTO's I-TIP dataset, Namibia has imposed two NTMs in total and none of these apply to agrifood goods (HS product codes 1-24).",null,null,null,null,null,null,null,null,"Estimate. Number of NTMs imposed by the EU."]
[null,null,"1.4.3","Import partner diversification"]
[null,null,"1.4.4","Export partner diversification"]
[null,null,1.5,"Food safety net programmes"]
[null,null,"1.5.1","Presence of food safety net programmes"]
[null,null,"1.5.2","Funding for food safety net programmes"]
[null,null,"1.5.3","Coverage of food safety net programmes"]
[null,null,"1.5.4","Operation of food safety net programmes"]
[null,null,"1.5.5","End-to-end monitoring of food safety net programmes"]
[null,null,2,"AVAILABILITY"]
[null,null,2.1,"Access to agricultural inputs"]
[null,null,"2.1.1","Irrigation infrastructure",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"100% is awarded to Singapore for its efforts to supply sufficient water and promote water efficiency to its high-tech farms. Additionally, Singapore experiences low-medium agricultural water risk (quantity), according to WRI data. \nSingapore imports more than 90% of its food; as of 2023, only approximately 0.92% of its total land area was under agriculture. However, the Singapore Food Agency (SFA) has taken steps to increase local production. As part of its \"30 by 30 vision\", the SFA—with the aim of expanding local food production—tenders out spaces to agrifood companies on a competitive land tender basis. The SFA provides access to portable water for water storage and irrigation to these land parcels. Furthermore, as part of its award evalution criteria, the SFA gauges the resource efficiency (including water use) of the bidder. \nhttps://www.mse.gov.sg/policies/food/\nhttps://www.sfa.gov.sg/docs/default-source/food-farming/tender-document/sas-2025-tender-briefing-slide-deck-27-june-2025.pdf\nhttps://www.fao.org/faostat/en/#data/RL"]
[null,null,"2.1.2","Reliable access to electricity"]
[null,null,"2.1.2.1","Access to electricity, rural (% of rural population)"]
[null,null,"2.1.2.2","Reliability of electricity supply",null,null,null,null,null,null,null,null,null,null,"Regional average",null,null,null,null,"Average of income and regional grouping averages",null,null,"Average of income and regional grouping averages",null,"Average of income and regional grouping averages","Average of income and regional grouping averages",null,null,null,null,null,null,null,null,"Average of income and regional grouping averages",null,null,"Average of income and regional grouping averages",null,"Average of income and regional grouping averages",null,null,"Average of income and regional grouping averages",null,null,null,null,null,null,"Regional average",null,null,null,null,null,null,"Average of income and regional grouping averages",null,null,"Regional average"]
[null,null,"2.1.3","Nutrient use efficiency"]
[null,null,"2.1.4","Adoption of agritech solutions"]
[null,null,"2.1.5","Access to internet at home"]
[null,null,"2.1.6","Basic financial services"]
[null,null,"2.1.6.1","Access to formal savings account",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Datapoint is not available via World Bank. We instead use the bank account penetration rate as reported by the US Department of State. This is 82% for 2025. \nhttps://www.state.gov/reports/2025-investment-climate-statements/qatar",null,"Datapoint is not available via World Bank. According to the 2024 Rwanda Finscope Survey, 59% of the population use banks and other formal institutions to save money. \nhttp://www.alpha.statistics.gov.rw/sites/default/files/documents/2024-09/Rwanda-Finscope-2024-Report_compressed.pdf (p. 44)",null,null,null,null,null,null,null,null,null,null,"Datapoint is not available via World Bank. EI has taken the personal account ownership rate across the total population in the country, which stands at 94% as of 2024.\nhttps://www.arabianbusiness.com/gcc/uae/uae-reports-94-surge-in-bank-account-ownership;\nhttps://thefinanceworld.com/uae-sees-94-rise-in-personal-bank-account-ownership/;\nhttps://www.khaleejtimes.com/business/surge-in-bank-account-ownerships-positions-uae-among-most-banked-nations;"]
[null,null,"2.1.6.2","Access to formal sources of credit"]
[null,null,"2.1.7","Diversified financial services for agrifood value chain"]
[null,null,2.2000000000000002,"Inclusive and skilled agricultural workforce"]
[null,null,"2.2.1","Employment in agriculture: youth vs total population","Estimate. Average for upper middle income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. Across 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317",null,null,null,null,null,"Estimate. Farm operators under 35 as a share of total persons employed under the age of 35. The only available statistic on youth in agriculture was the number of farm operators under the age of 35 from 2021 [1,2]. Therefore this approximation approach was selected. \n[1] https://agriculture.canada.ca/en/department/transparency/briefing-documents/aafc-transition-books/book-1-sector-overview-ministers-transition-book-2025-aafc\n[2] https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410001701&pickMembers%5B0%5D=1.1&pickMembers%5B1%5D=2.3&cubeTimeFrame.startMonth=01&cubeTimeFrame.startYear=2021&cubeTimeFrame.endMonth=12&cubeTimeFrame.endYear=2021&referencePeriods=20210101%2C20211201",null,"Estimate. Average for upper middle income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. \nAcross 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Average for high income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. Across 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317",null,null,null,null,"Estimate. Average for lower middle income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. \nAcross 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317","Estimate. Share of working population aged 15-34 employed in agriculture. Working population statistics were not available for 15-29 years. Therefore, this approximation approach was selected. \nhttps://storage.dosm.gov.my/labour/lfs_qtr_2024-q4.pdf\nhttps://codeblue.galencentre.org/2025/09/kpkm-raises-alarm-over-malaysias-ageing-agricultural-workforce/",null,"Estimate. Average for lower middle income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. Across 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317",null,"Estimate. Average for lower middle income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. \nAcross 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317",null,null,null,null,null,null,null,"Estimate. Average for high income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. Across 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317",null,null,"Estimate. Average for high income economies. An income-based average approach was chosen based on the findings of Comin et al, 2021. Across 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317","Estimate. As of 2023, 0% of Singapore's total working population was employed in the agricultural sector. \nhttps://data.worldbank.org/indicator/SL.AGR.EMPL.ZS","Estimate. Average for upper middle income economies. An income-based average approach was chosen, based on the findings of Comin et al, 2021. Across 39 advanced and emerging economies, income effects were found to account for the bulk of the within-country evolution of sectoral reallocation. \nComin D, Lashkari D, Mestieri M. Structural Change with Long-run Income and Price Effects. Econometrica. January 2020. 89;1:311-374. Available at: https://doi.org/10.3982/ECTA16317"]
[null,null,"2.2.2","Wage gap: Agriculture sector vs national average","Estimate. Average percentage difference across upper middle income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.",null,"Estimate. Average percentage difference across high income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.",null,null,null,"Estimate. Average percentage difference across high income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.",null,"Estimate. Average percentage difference across upper middle income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.",null,"Estimate. Average percentage difference between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors in Ethiopia, Rwanda and Uganda.",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Average percentage difference across high income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.",null,"Estimate. Lower middle income group average compound annual growth rate (CAGR) used to extrapolate 2019 data values for wages to 2024.","Estimate. Lower middle income group average CAGR used to extrapolate 2019 data values values for wages to 2024.","Estimate. Upper middle income group average CAGR used to extrapolate 2020 data values for wages to 2024.",null,"Estimate. Average percentage difference across lower middle income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.",null,"Estimate. Average percentage difference across lower middle income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.","Estimate. Lower middle income group average CAGR used to extrapolate 2019 data values for wages to 2024",null,null,null,null,null,null,null,null,null,"Estimate. Average percentage difference across high income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors.","Estimate. A neglible share of workers in Singapore are employed in the agricultural sector. Therefore, the wages of workers employed in the larger agrifood sector (Food, Beverages & Tobacco, Wholesale Trade, Retail Trade and Food & Beverage Services) was calculated. A percentage difference was calculated between the median gross monthly wage of workers in the agrifood sector and median gross monthly wage for all workers in the country.","Estimate. Upper middle income group average CAGR used to extrapolate 2020 data values for wages to 2024",null,null,null,null,null,null,null,"Estimate. Average percentage difference across high income countries between average monthly wage of workers in the agricultural sector and average monthly wage of workers across all sectors."]
[null,null,"2.2.3","Access to extension and information dissemination"]
[null,null,"2.2.4","Community organisations"]
[null,null,"2.2.5","Political commitment to just transition"]
[null,null,2.2999999999999998,"Public expenditure on agricultural research and development",null,null,null,null,"Estimate. Spending on R&D as a share of GDP is used. \nhttps://ec.europa.eu/eurostat/databrowser/view/RD_E_GERDTOT__custom_19030760/default/table",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Spending on R&D as a share of GDP is used. \nhttps://www.nrf.gov.sg/files/2022_RIE_Survey_Publication.pdf"]
[null,null,2.4,"Volatility of agricultural production"]
[null,null,2.5,"Growth in productivity of the agricultural sector",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Regional average of East Asia and Pacific countries included in the index"]
[null,null,2.6,"Efficient agrifood supply chains"]
[null,null,"2.6.1","Agriculture producer prices",null,null,null,null,null,null,null,null,null,null,"Sub-Saharan Africa regional average",null,null,null,null,null,null,null,null,null,"Latin America and the Caribbean regional average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Sub-Saharan Africa regional average","Middle East and North Africa regional average"]
[null,null,"2.6.2","Blended market access support for smaller-scale farmers"]
[null,null,"2.6.3","Policy interventions to tackle food loss and waste"]
[null,null,"2.6.4","Crop storage facilities"]
[null,null,"2.6.5","Distribution infrastructure and logistics",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Sub-Saharan Africa average logistics performance index (LPI) score",null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Middle East and North Africa average LPI score","Estimate. Sub-Saharan Africa average LPI score",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Sub-Saharan Africa average LPI score",null,null,"Estimate. Sub-Saharan Africa average LPI score"]
[null,null,"2.6.6","End-to-end cold chain capacity"]
[null,null,2.7,"Sufficiency of supply"]
[null,null,"2.7.1","Food supply adequacy",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Australia, China and South Korea average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"UAE and Saudi Arabia average",null,null,null,"Australia, China and South Korea average"]
[null,null,"2.7.2","Dependency on chronic food aid",null,null,null,null,null,null,null,"Chile is a donor. Chile is a member of the International Forum on Total Official Support for Sustainable Development (TOSSD). Chile reported US$4.1m in support of sustainable development in the form of cross-border resources\nto TOSSD recipients in 2023. This includes developmental food aid as part of Sustainable Development Goal 2. \nhttps://www.oecd.org/content/dam/oecd/en/publications/reports/2025/06/development-co-operation-profiles_02ffa45c/chile_b0814ef5/f4312ff3-en.pdf"]
[null,null,2.8,"Food security and access policy commitments"]
[null,null,2.9,"Socio-political risk outlook"]
[null,null,"2.9.1","Security risk"]
[null,null,"2.9.2","Political stability risk"]
[null,null,"2.9.3","Government effectiveness"]
[null,null,3,"QUALITY AND SAFETY"]
[null,null,3.1,"Dietary diversity"]
[null,null,"3.1.1","Dietary diversity score (DDS): total",null,"Average of income and regional grouping","Average of income and regional grouping",null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n",null,"Average of income and regional grouping",null,null,null,null,null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n","Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n\"",null,null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n","Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n",null,null,null,null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n",null,null,null,"Calculated country-level DDSs by applying country-level weights to the average EU-level low, medium, and high DDS scores as provided in Russo et al, 2023. See the \"methodology note\" and \"EU weighted averages\" tabs.","Average of income and regional grouping",null,null,null,null,null,null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n",null,null,null,null,null,null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n","Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n","Average of income and regional grouping","Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n","Average of income and regional grouping","Average of income and regional grouping","Average of income and regional grouping",null,"Average of income and regional grouping","Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n",null,null,null,null,null,null,"Estimate. Europe average DDS\nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study \nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003\n"]
[null,null,"3.1.2","Gap in DDS: male vs female",null,"Average of income and regional grouping","Average of income and regional grouping",null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003",null,"Average of income and regional grouping",null,null,null,null,null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003","Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003",null,null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003","Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003",null,null,null,null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003",null,null,null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003","Average of income and regional grouping",null,null,null,null,null,null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003",null,null,null,null,null,null,"Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003","Proxy. Used the average of the estimated DDS difference for Spain and Italy","Average of income and regional grouping","Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003","Average of income and regional grouping","Average of income and regional grouping","Average of income and regional grouping",null,"Average of income and regional grouping","Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003",null,null,null,null,null,"Average of income and regional grouping","Male and female scores for each country were modelled by allocating its low, medium and high DDS scores, according to the corresponding EU-wide male/female proportions observed within each tertile, as provided in Russo et al, 2023. \nIFamily study: Dietary Diversity and Its Association with Diet Quality and Health Status of European Children, Adolescents, and Adults: Results from the I.Family Study\nhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10743104/#foods-12-04458-t003"]
[null,null,"3.1.3","Sugary and ultra-processed food consumption: total"]
[null,null,"3.1.4","Sugary and ultra-processed food consumption: male vs female"]
[null,null,3.2,"Nutritional standards"]
[null,null,"3.2.1","National dietary guidelines"]
[null,null,"3.2.2","National nutrition plan or strategy"]
[null,null,"3.2.3","Nutrition labelling"]
[null,null,"3.2.4","Nutrition monitoring and surveillance"]
[null,null,3.3,"Protein quality",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Average of Jordan and Turkey",null,null,"Estimate. Average of income and regional groupings of the country",null,null,null,null,null,null,null,null,null,"Estimate. Average of Saudi Arabia and UAE",null,null,null,"Estimate. Average of Malaysia and South Korea"]
[null,null,3.4,"Food safety"]
[null,null,"3.4.1","Relevant food safety legislation"]
[null,null,"3.4.2","Food safety mechanisms"]
[null,null,"3.4.3","Food safety innovation"]
[null,null,"3.4.4","Household food safety capacity"]
[null,null,"3.4.4.1","Access to safely managed drinking water",null,"Estimate. Average of income and regional grouping","Estimate. Average of income and regional grouping",null,null,null,null,null,"Estimate. Average of income and regional grouping",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Estimate. Average of income and regional grouping",null,null,null,"Estimate. Average of income and regional grouping",null,"Estimate. Average of income and regional grouping",null,null,null,null,null,null,null,null,null,"Estimate. Average of income and regional grouping","Estimate. Average of income and regional grouping",null,null,null,null,null,null,"Estimate. Average of income and regional grouping","Estimate. Average of income and regional grouping"]
[null,null,"3.4.4.2","Ability to store food safely",null,"Regional and income averages","Alternative source (Australian Bureau of Statistics)\nhttps://www.abs.gov.au/AUSSTATS/abs@.nsf/39433889d406eeb9ca2570610019e9a5/0E43C98B32A7FE85CA25750E00109A1D\nUNEP Global Cooling Watch 2025\nhttps://www.unep.org/resources/global-cooling-watch-2025",null,"Average of proxy sources from Europe. See \"methodology\" tab.",null,"Average of alternative sources from Europe, high income","Regional and income averages",null,null,null,null,"Average of proxy sources from Europe. See \"methodology\" tab.","Average of proxy sources from Europe. See \"methodology\" tab.",null,null,"Alternative source (Household appliances penetration and ownership trends in residential \nbuildings, University of Lleida)\nhttps://repositori.udl.cat/server/api/core/bitstreams/5dd86e99-d28a-4639-92ce-1ab2ed53b984/content\nUNEP Global Cooling Watch 2025\nhttps://www.unep.org/resources/global-cooling-watch-2025","Average of proxy sources from Europe. See \"methodology\" tab.",null,"Average of proxy sources from Europe. See \"methodology\" tab.",null,null,"Average of proxy sources from Europe. See \"methodology\" tab.",null,null,"Alternative source (Central Bureau of Statistics: Israel, archives)\nhttps://web.archive.org/web/20171222051038/http://cbs.gov.il/publications17/1677/pdf/t14.pdf\nUNEP Global Cooling Watch 2025\nhttps://www.unep.org/resources/global-cooling-watch-2025","Average of proxy sources from Europe. See \"methodology\" tab.","Regional and income averages",null,null,"Regional and income averages",null,null,null,"Average of proxy sources from Europe. See \"methodology\" tab.",null,null,null,null,null,null,"Average of proxy sources from Europe. See \"methodology\" tab.","Average of proxy sources from Europe. See \"methodology\" tab.","Regional and income averages","Average of proxy sources from Europe. See \"methodology\" tab.",null,"Regional and income averages","Average of proxy sources from Europe, high income countries (also aligns with high upper middle income countries in Asia)",null,"Average of proxy sources from Europe, high income countries (also aligns with high upper middle income countries in Asia)","Alternative source (Household appliances penetration and ownership trends in residential \nbuildings, University of Lleida)\nhttps://repositori.udl.cat/server/api/core/bitstreams/5dd86e99-d28a-4639-92ce-1ab2ed53b984/content\nUNEP Global Cooling Watch 2025\nhttps://www.unep.org/resources/global-cooling-watch-2025","Regional and income averages",null,null,null,null,"Regional and income averages","Alternative source (Association of Manufacturers of Domestic Appliances industry information)\nhttps://www.amdea.org.uk/industry-information/market-information/\nUNEP Global Cooling Watch 2025\nhttps://www.unep.org/resources/global-cooling-watch-2025","Regional and income averages"]
[null,null,4,"CLIMATE RISK RESPONSIVENESS"]
[null,null,4.0999999999999996,"Physical risk exposure"]
[null,null,"4.1.1","Projected temperature rise"]
[null,null,"4.1.2","Agricultural water risk: quantity"]
[null,null,"4.1.3","Agricultural water risk: quality"]
[null,null,"4.1.4","Land degradation risk"]
[null,null,4.2,"Disaster management"]
[null,null,"4.2.1","Severity of natural disasters","Used regional average","Used regional average",null,null,null,null,null,null,null,null,null,null,null,"Used regional average",null,null,null,null,null,null,null,"Used regional average","Used regional average",null,null,null,null,null,"Used regional average",null,"Used regional average",null,null,null,null,null,null,null,"Used regional average",null,null,null,null,null,null,null,null,"Used regional average",null,null,null,null,null,null,null,null,"Used regional average"]
[null,null,"4.2.2","Maturity of mutli-hazard early warning systems",null,null,null,null,null,null,null,null,"UNICEF Multiple Indicator Cluster Surveys (MICS) average",null,"Least developed countries (LDCs) average",null,null,null,null,null,null,null,null,null,null,"MICS average",null,null,null,"Middle East and North Africa average",null,null,null,null,null,null,null,null,"Europe average","MICS average",null,"MICS average","MICS average",null,null,null,null,null,null,"LDCs average","Europe average","Small island developing states average",null,null,"Europe average",null,null,null,"MICS average",null,null,null,null,"MICS average"]
[null,null,"4.2.3","Adoption and implementation of national and local disaster risk reduction strategy",null,null,null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,null,null,null,null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/","No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,null,null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/","No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/",null,null,null,null,"No disaster risk reduction strategy in place. For Target E of the Sendai Framework, only scores above 0 are counted as \"reported\". So the number of countries that have reported is equal to the number of countries that report having a disaster risk reduction strategy. \nhttps://sendaimonitor.undrr.org/"]
[null,null,"4.2.4","Pest infestation and disease management"]
[null,null,4.3,"Mitigation and adaptation"]
[null,null,"4.3.1","Political commitment to mitigation and adaptation","Average of income and regional grouping"]
[null,null,"4.3.2","Climate finance aid flows to agriculture",null,null,null,null,null,null,null,"No evidence of developmental assistance specifically to support climate mitigation and/or adaptation efforts in the agricultural sector of recipient countries",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"The country is a non-Development Assistance Committee (DAC) provider. However, there is no evidence of developmental assistance specifically to support climate mitigation and/or adaptation efforts in the agricultural sector of recipient countries. \nDAC5: Aid Official Development Assistance (ODA) by sector and provider: https://data-explorer.oecd.org/",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"The Qatar Fund for Development does provide ODA for climate-smart agriculture. \nhttps://www.oecd.org/en/publications/development-co-operation-profiles_04b376d7-en/qatar_8eb760f1-en.html","The country is a non-DAC provider. However, there is no evidence of developmental assistance specifically to support climate mitigation and/or adaptation efforts in the agricultural sector of recipient countries. \nDAC5: Aid (ODA) by sector and provider: https://data-explorer.oecd.org/",null,"The Saudi Fund for Development (SFD)'s financing portfolio covers agriculture as a sector. Achieving sustainable food security is outlined as one of the development impact areas of investment in the sector. There is some evidence that the SFD has specifically provided climate change adaptation financing for the agricultural sector in Afghanistan. \nhttps://www.sfd.gov.sa/ar\nhttps://www.isdb.org/hub/turkey/news/sfdahtf-project-boosts-agricultural-livelihoods-climate-change-and-community-development-in-yaftal-e-payan-district-of-badakhshan#:~:text=Kabul%2C%20Afghanistan%2C%2026%20November%202024,condition%20of%20the%20previous%20canal.","Singapore has provided developmental assistance specifically to support climate mitigation and/or adaptation efforts in the agricultural sector of recipient countries. Through the Temasek foundation, the philanthropic arm of the state sovereign fund, Singapore provides credit guarantee to the Climate Smart Fund aimed at reducing deforestation, increasing smallholder farmer incomes and building climate resilience in Indonesia.\nhttps://www.norfund.no/climate-smart-fund-scales-to-tackle-deforestation-and-climate-adaptation-in-indonesia/",null,null,null,null,null,null,null,null,"The UAE has provided developmental assistance specifically to support climate mitigation and/or adaptation efforts in the agricultural sector of recipient countries. One notable example is the Agriculture Innovation Mission for Climate, a joint initiative by the US and the UAE. The initiative raised US$29.2bn investment in, and support for, climate-smart agriculture and food systems innovation between 2021–2025. \nhttps://aimforclimate.org/"]
[null,null,"4.3.3","Mainstreaming sustainable agriculture practices"]
[null,null,"4.3.4","Change in GHG emissions from the agrifood sector"]
[null,null,"4.3.5","Projected ocean health for aquaculture",null,null,null,null,null,null,null,null,null,null,null,null,"Landlocked country. Calculated the average Ocean Health Index (OHI) Food Provision (FP) future score for the EU",null,null,"Landlocked country. Used the weighted average of OHI FP future scores of the country’s top five import partners by trade volume (US$m) for the product category: 03: Fish and Crustaceans, Molluscs and other Aquatic Invertebrates",null,null,null,null,null,null,"Landlocked country. Calculated the average OHI FP future score for the EU",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Landlocked country. Used the weighted average of OHI FP future scores of the country’s top five import partners by trade volume (US$m) for the product category: 03: Fish and Crustaceans, Molluscs and other Aquatic Invertebrates",null,null,null,null,null,null,"Landlocked country. Used the weighted average of OHI FP future scores of the country’s top five import partners by trade volume (US$m) for the product category: 03: Fish and Crustaceans, Molluscs and other Aquatic Invertebrates",null,null,null,null,null,null,null,null,null,"Landlocked country. Used the weighted average of OHI FP future scores of the country’s top five import partners by trade volume (US$m) for the product category: 03: Fish and Crustaceans, Molluscs and other Aquatic Invertebrates"]
[null,null,"4.3.6","Change in risk of biodiversity loss"]
[null,null,"4.3.7","Public and blended sector support for low-emissions R&D in the agrifood sector"]
[null,null,"4.3.8","Financial services support for low-emissions R&D in the agrifood sector"]
[null,null,"BG","BACKGROUND INDICATORS"]
[null,null,"BG1","Food loss and waste",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average"]
[null,null,"BG2","Environmental Performance Index"]
[null,null,"BG3","Prevalence of undernourishment",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,"Data not available; filled using regional and income average",null,"Data not available; filled using regional and income average"]
[null,null,"BG4","Prevalence of severe food insecurity",null,null,null,"Data not available; filled using regional and income average",null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,"Data not available; filled using regional and income average",null,"Data not available; filled using regional and income average",null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,null,null,"Data not available; filled using regional and income average",null,"Data not available; filled using regional and income average","Data not available; filled using regional and income average",null,null,null,null,null,null,null,"Data not available; filled using regional and income average"]
[null,null,"BG5","Percentage of children stunted",null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data not available; filled using regional and income average","Data were too old. We filled the gap using an alternative source with more recent estimates: \nhttps://www.globalhungerindex.org/download/all.html","Data were too old. We filled the gap using an alternative source with more recent estimates: \nhttps://www.globalhungerindex.org/download/all.html","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data not available; filled using regional and income average",null,null,"Data not available; filled using regional and income average","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old. We filled the gap using an alternative source with more recent estimates: \nhttps://www.globalhungerindex.org/download/all.html",null,null,"Data not available; filled using regional and income average","Data not available; filled using regional and income average","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,null,null,null,null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,null,"Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,"Data were too old. We filled the gap using an alternative source with more recent estimates: \nhttps://www.globalhungerindex.org/download/all.html",null,null,"Data were too old, used high income country average","Data were too old, so we used an alternative source with more recent estimates: https://humancapital.worldbank.org/en/indicator/WB_HCP_STUNTING",null,"Data not available; filled using regional and income average",null,null,null,null,null,"Data not available; filled using regional and income average"]
[null,null,"BG6","Percentage of children underweight",null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,"Obsolete data; filled using region and income average","Data not available; filled using regional and income average",null,null,"Data not available; filled using regional and income average",null,null,"Obsolete data; filled using region and income average",null,null,"Data not available; filled using regional and income average",null,null,"Data not available; filled using regional and income average","Data not available; filled using regional and income average",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average",null,null,null,null,null,"Data not available; filled using regional and income average"]
[null,null,"BG7","Prevalence of obesity"]
[null,null,"BG8","Prevalence of anaemia among women of reproductive age (% of women aged 15-49)",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data not available; filled using regional and income average"]
[null,null,"BG9","Human Development Index"]
[null,null,"BG10","GDP growth per capita"]
[null,null,"BG11","GINI coefficient","Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,null,null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,null,null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database","Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database","Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database","Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database",null,null,"Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database","Data were too old, so we filled the gap with estimates from the World Income Inequality Database, a dataset run by UNU-WIDER: https://www.wider.unu.edu/project/world-income-inequality-database"]

{"sheet":"Lists_indicators","index":8,"n_rows":105,"n_cols":9,"rows_kept":105,"cut":false,"hidden":false,"merged":[]}
["Pillars",null,null,"No.","Indicator",null,null,null,"Sorting"]
["RESILIENT FOOD SYSTEMS ENVIRONMENT","OVERALL",null,{"$f":"'DATA TABLE'!B10","v":0},"RESILIENT FOOD SYSTEMS ENVIRONMENT",{"$f":"E2","v":"RESILIENT FOOD SYSTEMS ENVIRONMENT"},"Overall index",null,"Alphabetical"]
["1) Affordability","_1Affordability",null,{"$f":"'DATA TABLE'!B11","v":1},"AFFORDABILITY",{"$f":"IF(D3=\"\",E3,CONCATENATE(D3,\") \",E3))","v":"1) AFFORDABILITY"},"Affordability",null,"Best response to worst"]
["2) Availability","_2Availability",null,{"$f":"'DATA TABLE'!B12","v":1.1000000000000001},"Change in average food costs",{"$f":"IF(D4=\"\",E4,CONCATENATE(D4,\") \",E4))","v":"1.1) Change in average food costs"},"Affordability >> Change in average food costs",null,"Worst response to best"]
["3) Quality and safety","_3QualitySafety",null,{"$f":"'DATA TABLE'!B13","v":1.2},"Affordability of a healthy diet","1.2) Affordability of a healthy diet","Affordability >> Affordability of a healthy diet"]
["4) Climate risk responsiveness","_4ClimateRisk",null,{"$f":"'DATA TABLE'!B14","v":1.3},"Affordability of a healthy diet to bottom 40%","1.3) Affordability of a healthy diet to bottom 40%","Affordability >> Affordability of a healthy diet to bottom 40%"]
["Background indicators","BACKGROUND",null,{"$f":"'DATA TABLE'!B15","v":1.4},"Agricultural trade","1.4) Agricultural trade","Affordability >> Agricultural trade"]
[null,null,null,{"$f":"'DATA TABLE'!B16","v":"1.4.1"},"Agricultural import tariffs","1.4.1) Agricultural import tariffs","Affordability >> Agricultural trade"]
[null,null,null,{"$f":"'DATA TABLE'!B17","v":"1.4.2"},"Agricultural and food products import non-tariff measures (NTMs)","1.4.2) Agricultural and food products import non-tariff measures (NTMs)","Affordability >> Agricultural trade"]
[null,null,null,{"$f":"'DATA TABLE'!B18","v":"1.4.3"},"Import partner diversification","1.4.3) Import partner diversification","Affordability >> Agricultural trade"]
[null,null,null,{"$f":"'DATA TABLE'!B19","v":"1.4.4"},"Export partner diversification","1.4.4) Export partner diversification","Affordability >> Agricultural trade"]
[null,null,null,{"$f":"'DATA TABLE'!B20","v":1.5},"Food safety net programmes","1.5) Food safety net programmes","Affordability >> Food safety net programmes"]
[null,null,null,{"$f":"'DATA TABLE'!B21","v":"1.5.1"},"Presence of food safety net programmes","1.5.1) Presence of food safety net programmes","Affordability >> Food safety net programmes"]
[null,null,null,{"$f":"'DATA TABLE'!B22","v":"1.5.2"},"Funding for food safety net programmes","1.5.2) Funding for food safety net programmes","Affordability >> Food safety net programmes"]
[null,null,null,{"$f":"'DATA TABLE'!B23","v":"1.5.3"},"Coverage of food safety net programmes","1.5.3) Coverage of food safety net programmes","Affordability >> Food safety net programmes"]
[null,null,null,{"$f":"'DATA TABLE'!B24","v":"1.5.4"},"Operation of food safety net programmes","1.5.4) Operation of food safety net programmes","Affordability >> Food safety net programmes"]
[null,null,null,{"$f":"'DATA TABLE'!B25","v":"1.5.5"},"End-to-end monitoring of food safety net programmes","1.5.5) End-to-end monitoring of food safety net programmes","Affordability >> Food safety net programmes"]
[null,null,null,{"$f":"'DATA TABLE'!B26","v":2},"AVAILABILITY","2) AVAILABILITY","Availability"]
[null,null,null,{"$f":"'DATA TABLE'!B27","v":2.1},"Access to agricultural inputs","2.1) Access to agricultural inputs","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B28","v":"2.1.1"},"Irrigation infrastructure","2.1.1) Irrigation infrastructure","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B29","v":"2.1.2"},"Reliable access to electricity","2.1.2) Reliable access to electricity","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B30","v":"2.1.2.1"},"Access to electricity, rural (% of rural population)","2.1.2.1) Access to electricity, rural (% of rural population)","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B31","v":"2.1.2.2"},"Reliability of electricity supply","2.1.2.2) Reliability of electricity supply","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B32","v":"2.1.3"},"Nutrient use efficiency","2.1.3) Nutrient use efficiency","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B33","v":"2.1.4"},"Adoption of agritech solutions","2.1.4) Adoption of agritech solutions","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B34","v":"2.1.5"},"Access to internet at home","2.1.5) Access to internet at home","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B35","v":"2.1.6"},"Basic financial services","2.1.6) Basic financial services","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B36","v":"2.1.6.1"},"Access to formal savings account","2.1.6.1) Access to formal savings account","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B37","v":"2.1.6.2"},"Access to formal sources of credit","2.1.6.2) Access to formal sources of credit","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B38","v":"2.1.7"},"Diversified financial services for agrifood value chain","2.1.7) Diversified financial services for agrifood value chain","Availability >> Access to agricultural inputs"]
[null,null,null,{"$f":"'DATA TABLE'!B39","v":2.2000000000000002},"Inclusive and skilled agricultural workforce","2.2) Inclusive and skilled agricultural workforce","Availability >> Inclusive and skilled agricultural workforce"]
[null,null,null,{"$f":"'DATA TABLE'!B40","v":"2.2.1"},"Employment in agriculture: youth vs total population","2.2.1) Employment in agriculture: youth vs total population","Availability >> Inclusive and skilled agricultural workforce"]
[null,null,null,{"$f":"'DATA TABLE'!B41","v":"2.2.2"},"Wage gap: Agriculture sector vs national average","2.2.2) Wage gap: Agriculture sector vs national average","Availability >> Inclusive and skilled agricultural workforce"]
[null,null,null,{"$f":"'DATA TABLE'!B42","v":"2.2.3"},"Access to extension and information dissemination","2.2.3) Access to extension and information dissemination","Availability >> Inclusive and skilled agricultural workforce"]
[null,null,null,{"$f":"'DATA TABLE'!B43","v":"2.2.4"},"Community organisations","2.2.4) Community organisations","Availability >> Inclusive and skilled agricultural workforce"]
[null,null,null,{"$f":"'DATA TABLE'!B44","v":"2.2.5"},"Political commitment to just transition","2.2.5) Political commitment to just transition","Availability >> Inclusive and skilled agricultural workforce"]
[null,null,null,{"$f":"'DATA TABLE'!B45","v":2.2999999999999998},"Public expenditure on agricultural research and development","2.3) Public expenditure on agricultural research and development","Availability >> Public expenditure on agricultural research and development"]
[null,null,null,{"$f":"'DATA TABLE'!B46","v":2.4},"Volatility of agricultural production","2.4) Volatility of agricultural production","Availability >> Volatility of agricultural production"]
[null,null,null,{"$f":"'DATA TABLE'!B47","v":2.5},"Growth in productivity of the agricultural sector","2.5) Growth in productivity of the agricultural sector","Availability >> Productivity of the agricultural sector"]
[null,null,null,{"$f":"'DATA TABLE'!B48","v":2.6},"Efficient agrifood supply chains","2.6) Efficient agrifood supply chains","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B49","v":"2.6.1"},"Agriculture producer prices","2.6.1) Agriculture producer prices","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B50","v":"2.6.2"},"Blended market access support for smaller-scale farmers","2.6.2) Blended market access support for smaller-scale farmers","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B51","v":"2.6.3"},"Policy interventions to tackle food loss and waste","2.6.3) Policy interventions to tackle food loss and waste","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B52","v":"2.6.4"},"Crop storage facilities","2.6.4) Crop storage facilities","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B53","v":"2.6.5"},"Distribution infrastructure and logistics","2.6.5) Distribution infrastructure and logistics","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B54","v":"2.6.6"},"End-to-end cold chain capacity","2.6.6) End-to-end cold chain capacity","Availability >> Efficient agrifood supply chains"]
[null,null,null,{"$f":"'DATA TABLE'!B55","v":2.7},"Sufficiency of supply","2.7) Sufficiency of supply","Availability >> Sufficiency of supply"]
[null,null,null,{"$f":"'DATA TABLE'!B56","v":"2.7.1"},"Food supply adequacy","2.7.1) Food supply adequacy","Availability >> Sufficiency of supply"]
[null,null,null,{"$f":"'DATA TABLE'!B57","v":"2.7.2"},"Dependency on chronic food aid","2.7.2) Dependency on chronic food aid","Availability >> Sufficiency of supply"]
[null,null,null,{"$f":"'DATA TABLE'!B58","v":2.8},"Food security and access policy commitments","2.8) Food security and access policy commitments","Availability >> Food security and access policy commitments"]
[null,null,null,{"$f":"'DATA TABLE'!B59","v":2.9},"Socio-political risk outlook","2.9) Socio-political risk outlook","Availability >> Socio-political risk outlook"]
[null,null,null,{"$f":"'DATA TABLE'!B60","v":"2.9.1"},"Security risk","2.9.1) Security risk","Availability >> Socio-political risk outlook"]
[null,null,null,{"$f":"'DATA TABLE'!B61","v":"2.9.2"},"Political stability risk","2.9.2) Political stability risk","Availability >> Socio-political risk outlook"]
[null,null,null,{"$f":"'DATA TABLE'!B62","v":"2.9.3"},"Government effectiveness","2.9.3) Government effectiveness","Availability >> Socio-political risk outlook"]
[null,null,null,{"$f":"'DATA TABLE'!B63","v":3},"QUALITY AND SAFETY","3) QUALITY AND SAFETY","Quality and safety"]
[null,null,null,{"$f":"'DATA TABLE'!B64","v":3.1},"Dietary diversity","3.1) Dietary diversity","Quality and safety >> Dietary diversity"]
[null,null,null,{"$f":"'DATA TABLE'!B65","v":"3.1.1"},"Dietary diversity score (DDS): total","3.1.1) Dietary diversity score (DDS): total","Quality and safety >> Dietary diversity"]
[null,null,null,{"$f":"'DATA TABLE'!B66","v":"3.1.2"},"Gap in DDS: male vs female","3.1.2) Gap in DDS: male vs female","Quality and safety >> Dietary diversity"]
[null,null,null,{"$f":"'DATA TABLE'!B67","v":"3.1.3"},"Sugary and ultra-processed food consumption: total","3.1.3) Sugary and ultra-processed food consumption: total","Quality and safety >> Dietary diversity"]
[null,null,null,{"$f":"'DATA TABLE'!B68","v":"3.1.4"},"Sugary and ultra-processed food consumption: male vs female","3.1.4) Sugary and ultra-processed food consumption: male vs female","Quality and safety >> Dietary diversity"]
[null,null,null,{"$f":"'DATA TABLE'!B69","v":3.2},"Nutritional standards","3.2) Nutritional standards","Quality and safety >> Nutritional standards"]
[null,null,null,{"$f":"'DATA TABLE'!B70","v":"3.2.1"},"National dietary guidelines","3.2.1) National dietary guidelines","Quality and safety >> Nutritional standards"]
[null,null,null,{"$f":"'DATA TABLE'!B71","v":"3.2.2"},"National nutrition plan or strategy","3.2.2) National nutrition plan or strategy","Quality and safety >> Nutritional standards"]
[null,null,null,{"$f":"'DATA TABLE'!B72","v":"3.2.3"},"Nutrition labelling","3.2.3) Nutrition labelling","Quality and safety >> Nutritional standards"]
[null,null,null,{"$f":"'DATA TABLE'!B73","v":"3.2.4"},"Nutrition monitoring and surveillance",{"$f":"IF(D65=\"\",E65,CONCATENATE(D65,\") \",E65))","v":"3.2.4) Nutrition monitoring and surveillance"},"Quality and safety >> Nutritional standards"]
[null,null,null,{"$f":"'DATA TABLE'!B74","v":3.3},"Protein quality","3.3) Protein quality","Quality and safety >> Protein quality"]
[null,null,null,{"$f":"'DATA TABLE'!B75","v":3.4},"Food safety","3.4) Food safety","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B76","v":"3.4.1"},"Relevant food safety legislation","3.4.1) Relevant food safety legislation","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B77","v":"3.4.2"},"Food safety mechanisms","3.4.2) Food safety mechanisms","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B78","v":"3.4.3"},"Food safety innovation","3.4.3) Food safety innovation","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B79","v":"3.4.4"},"Household food safety capacity","3.4.4) Household food safety capacity","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B80","v":"3.4.4.1"},"Access to safely managed drinking water","3.4.4.1) Access to safely managed drinking water","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B81","v":"3.4.4.2"},"Ability to store food safely","3.4.4.2) Ability to store food safely","Quality and safety >> Food safety"]
[null,null,null,{"$f":"'DATA TABLE'!B82","v":4},"CLIMATE RISK RESPONSIVENESS","4) CLIMATE RISK RESPONSIVENESS","Climate risk responsiveness"]
[null,null,null,{"$f":"'DATA TABLE'!B83","v":4.0999999999999996},"Physical risk exposure","4.1) Physical risk exposure","Climate risk responsiveness >> Physical risk exposure"]
[null,null,null,{"$f":"'DATA TABLE'!B84","v":"4.1.1"},"Projected temperature rise","4.1.1) Projected temperature rise","Climate risk responsiveness >> Physical risk exposure"]
[null,null,null,{"$f":"'DATA TABLE'!B85","v":"4.1.2"},"Agricultural water risk: quantity","4.1.2) Agricultural water risk: quantity","Climate risk responsiveness >> Physical risk exposure"]
[null,null,null,{"$f":"'DATA TABLE'!B86","v":"4.1.3"},"Agricultural water risk: quality","4.1.3) Agricultural water risk: quality","Climate risk responsiveness >> Physical risk exposure"]
[null,null,null,{"$f":"'DATA TABLE'!B87","v":"4.1.4"},"Land degradation risk","4.1.4) Land degradation risk","Climate risk responsiveness >> Physical risk exposure"]
[null,null,null,{"$f":"'DATA TABLE'!B88","v":4.2},"Disaster management","4.2) Disaster management","Climate risk responsiveness >> Disaster management"]
[null,null,null,{"$f":"'DATA TABLE'!B89","v":"4.2.1"},"Severity of natural disasters","4.2.1) Severity of natural disasters","Climate risk responsiveness >> Disaster management"]
[null,null,null,{"$f":"'DATA TABLE'!B90","v":"4.2.2"},"Maturity of mutli-hazard early warning systems","4.2.2) Maturity of mutli-hazard early warning systems","Climate risk responsiveness >> Disaster management"]
[null,null,null,{"$f":"'DATA TABLE'!B91","v":"4.2.3"},"Adoption and implementation of national and local disaster risk reduction strategy","4.2.3) Adoption and implementation of national and local disaster risk reduction strategy","Climate risk responsiveness >> Disaster management"]
[null,null,null,{"$f":"'DATA TABLE'!B92","v":"4.2.4"},"Pest infestation and disease management","4.2.4) Pest infestation and disease management","Climate risk responsiveness >> Disaster management"]
[null,null,null,{"$f":"'DATA TABLE'!B93","v":4.3},"Mitigation and adaptation","4.3) Mitigation and adaptation","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B94","v":"4.3.1"},"Political commitment to mitigation and adaptation","4.3.1) Political commitment to mitigation and adaptation","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B95","v":"4.3.2"},"Climate finance aid flows to agriculture","4.3.2) Climate finance aid flows to agriculture","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B96","v":"4.3.3"},"Mainstreaming sustainable agriculture practices","4.3.3) Mainstreaming sustainable agriculture practices","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B97","v":"4.3.4"},"Change in GHG emissions from the agrifood sector","4.3.4) Change in GHG emissions from the agrifood sector","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B98","v":"4.3.5"},"Projected ocean health for aquaculture","4.3.5) Projected ocean health for aquaculture","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B99","v":"4.3.6"},"Change in risk of biodiversity loss","4.3.6) Change in risk of biodiversity loss","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B100","v":"4.3.7"},"Public and blended sector support for low-emissions R&D in the agrifood sector","4.3.7) Public and blended sector support for low-emissions R&D in the agrifood sector","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B101","v":"4.3.8"},"Financial services support for low-emissions R&D in the agrifood sector","4.3.8) Financial services support for low-emissions R&D in the agrifood sector","Climate risk responsiveness >> Mitigation and adaptation"]
[null,null,null,{"$f":"'DATA TABLE'!B102","v":"BG"},"BACKGROUND INDICATORS","BG) BACKGROUND INDICATORS","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B103","v":"BG1"},"Food loss and waste",{"$f":"IF(D95=\"\",E95,CONCATENATE(D95,\") \",E95))","v":"BG1) Food loss and waste"},"Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B104","v":"BG2"},"Environmental Performance Index",{"$f":"IF(D96=\"\",E96,CONCATENATE(D96,\") \",E96))","v":"BG2) Environmental Performance Index"},"Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B105","v":"BG3"},"Prevalence of undernourishment","BG3) Prevalence of undernourishment","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B106","v":"BG4"},"Prevalence of severe food insecurity","BG4) Prevalence of severe food insecurity","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B107","v":"BG5"},"Percentage of children stunted","BG5) Percentage of children stunted","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B108","v":"BG6"},"Percentage of children underweight","BG6) Percentage of children underweight","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B109","v":"BG7"},"Prevalence of obesity","BG7) Prevalence of obesity","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B110","v":"BG8"},"Prevalence of anaemia among women of reproductive age (% of women aged 15-49)","BG8) Prevalence of anaemia among women of reproductive age (% of women aged 15-49)","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B111","v":"BG9"},"Human Development Index","BG9) Human Development Index","Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B112","v":"BG10"},"GDP growth per capita",{"$f":"IF(D104=\"\",E104,CONCATENATE(D104,\") \",E104))","v":"BG10) GDP growth per capita"},"Background indicator"]
[null,null,null,{"$f":"'DATA TABLE'!B113","v":"BG11"},"GINI coefficient","BG11) GINI coefficient","Background indicator"]

{"sheet":"Lists_countries","index":9,"n_rows":63,"n_cols":28,"rows_kept":63,"cut":false,"hidden":false,"merged":[]}
["Groups",null,null,"Regional groups",null,null,null,null,"RFSI classification",null,"Income groups",null,null,null,null,null,"MAX:",{"$f":"COUNTA(R$3:R$155)","v":61},11,3,15,{"$f":"COUNTA(V$3:V$155)","v":15},{"$f":"COUNTA(W$3:W$155)","v":10},{"$f":"COUNTA(X$3:X$155)","v":12},5,17,15,27]
["Global","Global",null,"Algeria","Middle East and North Africa","Northern Africa",null,"Congo (Democratic Republic)","Sub-Saharan Africa",null,"Algeria","Upper middle income",null,"Australia","High income",null,null,"Global","Sub-Saharan Africa","North America","Asia Pacific","Europe","Middle East and North Africa","Latin America and the Caribbean","Low income","Lower middle income","Upper middle income","High income"]
["Sub-Saharan Africa","Sub_Saharan_Africa",null,"Argentina","Latin America and the Caribbean","Latin America and the Caribbean",null,"Ethiopia","Sub-Saharan Africa",null,"Argentina","Upper middle income",null,"Belgium","High income",null,1,"Algeria","Congo (Democratic Republic)","Canada","Australia","Belgium","Algeria","Argentina","Congo (Democratic Republic)","Bangladesh","Algeria","Australia"]
["North America","North_America",null,"Australia","Asia-Pacific","Australia and New Zealand",null,"Ghana","Sub-Saharan Africa",null,"Australia","High income",null,"Canada","High income",null,2,"Argentina","Ethiopia","United States","Bangladesh","Czech Republic","Egypt","Brazil","Ethiopia","Egypt","Argentina","Belgium"]
["Asia Pacific","Asia_Pacific",null,"Bangladesh","Asia-Pacific","Southern Asia",null,"Kenya","Sub-Saharan Africa",null,"Bangladesh","Lower middle income",null,"Chile","High income",null,3,"Australia","Ghana","AVERAGE","China","Denmark","Israel","Chile","Rwanda","Ghana","Brazil","Canada"]
["Europe","Europe",null,"Belgium","Europe","Western Europe",null,"Namibia","Sub-Saharan Africa",null,"Belgium","High income",null,"Costa Rica","High income",null,4,"Bangladesh","Kenya",null,"India","France","Jordan","Colombia","Uganda","Honduras","China","Chile"]
["Middle East and North Africa","Middle_East_and_North_Africa",null,"Brazil","Latin America and the Caribbean","Latin America and the Caribbean",null,"Nigeria","Sub-Saharan Africa",null,"Brazil","Upper middle income",null,"Czech Republic","High income",null,5,"Belgium","Namibia",null,"Indonesia","Germany","Lebanon","Costa Rica","AVERAGE","India","Colombia","Costa Rica"]
["Latin America and the Caribbean","Latin_America_and_the_Caribbean",null,"Canada","North America","Northern America",null,"Rwanda","Sub-Saharan Africa",null,"Canada","High income",null,"Denmark","High income",null,6,"Brazil","Nigeria",null,"Japan","Greece","Qatar","Guatemala",null,"Jordan","Guatemala","Czech Republic"]
["Low income","Low_income",null,"Chile","Latin America and the Caribbean","Latin America and the Caribbean",null,"South Africa","Sub-Saharan Africa",null,"Chile","High income",null,"France","High income",null,7,"Canada","Rwanda",null,"Malaysia","Hungary","Saudi Arabia","Honduras",null,"Kenya","Indonesia","Denmark"]
["Lower middle income","Lower_middle_income",null,"China","Asia-Pacific","Eastern Asia",null,"Tanzania","Sub-Saharan Africa",null,"China","Upper middle income",null,"Germany","High income",null,8,"Chile","South Africa",null,"Pakistan","Italy","Turkey","Mexico",null,"Lebanon","Malaysia","France"]
["Upper middle income","Upper_middle_income",null,"Colombia","Latin America and the Caribbean","Latin America and the Caribbean",null,"Uganda","Sub-Saharan Africa",null,"Colombia","Upper middle income",null,"Greece","High income",null,9,"China","Tanzania",null,"Philippines","Netherlands","United Arab Emirates","Nicaragua",null,"Namibia","Mexico","Germany"]
["High income","High_income",null,"Congo (Democratic Republic)","Sub-Saharan Africa","Middle Africa",null,"Canada","North America",null,"Congo (Democratic Republic)","Low income",null,"Hungary","High income",null,10,"Colombia","Uganda",null,"Singapore","Poland","AVERAGE","Paraguay",null,"Nicaragua","Paraguay","Greece"]
[null,null,null,"Costa Rica","Latin America and the Caribbean","Latin America and the Caribbean",null,"United States","North America",null,"Costa Rica","High income",null,"Israel","High income",null,11,"Congo (Democratic Republic)","AVERAGE",null,"South Korea","Portugal",null,"Peru",null,"Nigeria","Peru","Hungary"]
[null,null,null,"Czech Republic","Europe","Eastern Europe",null,"Australia","Asia Pacific",null,"Czech Republic","High income",null,"Italy","High income",null,12,"Costa Rica",null,null,"Sri Lanka","Romania",null,"AVERAGE",null,"Pakistan","South Africa","Israel"]
[null,null,null,"Denmark","Europe","Northern Europe",null,"Bangladesh","Asia Pacific",null,"Denmark","High income",null,"Japan","High income",null,13,"Czech Republic",null,null,"Thailand","Spain",null,null,null,"Philippines","Thailand","Italy"]
[null,null,null,"Egypt","Middle East and North Africa","Northern Africa",null,"China","Asia Pacific",null,"Egypt","Lower middle income",null,"Netherlands","High income",null,14,"Denmark",null,null,"Vietnam","United Kingdom",null,null,null,"Sri Lanka","Turkey","Japan"]
[null,null,null,"Ethiopia","Sub-Saharan Africa","Eastern Africa",null,"India","Asia Pacific",null,"Ethiopia","Low income",null,"Poland","High income",null,15,"Egypt",null,null,"AVERAGE","AVERAGE",null,null,null,"Tanzania","AVERAGE","Netherlands"]
[null,null,null,"France","Europe","Western Europe",null,"Indonesia","Asia Pacific",null,"France","High income",null,"Portugal","High income",null,16,"Ethiopia",null,null,null,null,null,null,null,"Vietnam",null,"Poland"]
[null,null,null,"Germany","Europe","Western Europe",null,"Japan","Asia Pacific",null,"Germany","High income",null,"Qatar","High income",null,17,"France",null,null,null,null,null,null,null,"AVERAGE",null,"Portugal"]
[null,null,null,"Ghana","Sub-Saharan Africa","Western Africa",null,"Malaysia","Asia Pacific",null,"Ghana","Lower middle income",null,"Romania","High income",null,18,"Germany",null,null,null,null,null,null,null,null,null,"Qatar"]
[null,null,null,"Greece","Europe","Southern Europe",null,"Pakistan","Asia Pacific",null,"Greece","High income",null,"Saudi Arabia","High income",null,19,"Ghana",null,null,null,null,null,null,null,null,null,"Romania"]
[null,null,null,"Guatemala","Latin America and the Caribbean","Latin America and the Caribbean",null,"Philippines","Asia Pacific",null,"Guatemala","Upper middle income",null,"Singapore","High income",null,20,"Greece",null,null,null,null,null,null,null,null,null,"Saudi Arabia"]
[null,null,null,"Honduras","Latin America and the Caribbean","Latin America and the Caribbean",null,"Singapore","Asia Pacific",null,"Honduras","Lower middle income",null,"South Korea","High income",null,21,"Guatemala",null,null,null,null,null,null,null,null,null,"Singapore"]
[null,null,null,"Hungary","Europe","Eastern Europe",null,"South Korea","Asia Pacific",null,"Hungary","High income",null,"Spain","High income",null,22,"Honduras",null,null,null,null,null,null,null,null,null,"South Korea"]
[null,null,null,"India","Asia-Pacific","Southern Asia",null,"Sri Lanka","Asia Pacific",null,"India","Lower middle income",null,"United Arab Emirates","High income",null,23,"Hungary",null,null,null,null,null,null,null,null,null,"Spain"]
[null,null,null,"Indonesia","Asia-Pacific","Southeastern Asia",null,"Thailand","Asia Pacific",null,"Indonesia","Upper middle income",null,"United Kingdom","High income",null,24,"India",null,null,null,null,null,null,null,null,null,"United Arab Emirates"]
[null,null,null,"Israel","Middle East and North Africa","Western Asia",null,"Vietnam","Asia Pacific",null,"Israel","High income",null,"United States","High income",null,25,"Indonesia",null,null,null,null,null,null,null,null,null,"United Kingdom"]
[null,null,null,"Italy","Europe","Southern Europe",null,"Belgium","Europe",null,"Italy","High income",null,"Congo (Democratic Republic)","Low income",null,26,"Israel",null,null,null,null,null,null,null,null,null,"United States"]
[null,null,null,"Japan","Asia-Pacific","Eastern Asia",null,"Czech Republic","Europe",null,"Japan","High income",null,"Ethiopia","Low income",null,27,"Italy",null,null,null,null,null,null,null,null,null,"AVERAGE"]
[null,null,null,"Jordan","Middle East and North Africa","Western Asia",null,"Denmark","Europe",null,"Jordan","Lower middle income",null,"Rwanda","Low income",null,28,"Japan"]
[null,null,null,"Kenya","Sub-Saharan Africa","Eastern Africa",null,"France","Europe",null,"Kenya","Lower middle income",null,"Uganda","Low income",null,29,"Jordan"]
[null,null,null,"Lebanon","Middle East and North Africa","Western Asia",null,"Germany","Europe",null,"Lebanon","Lower middle income",null,"Bangladesh","Lower middle income",null,30,"Kenya"]
[null,null,null,"Malaysia","Asia-Pacific","Southeastern Asia",null,"Greece","Europe",null,"Malaysia","Upper middle income",null,"Egypt","Lower middle income",null,31,"Lebanon"]
[null,null,null,"Mexico","Latin America and the Caribbean","Latin America and the Caribbean",null,"Hungary","Europe",null,"Mexico","Upper middle income",null,"Ghana","Lower middle income",null,32,"Malaysia"]
[null,null,null,"Namibia","Sub-Saharan Africa","Southern Africa",null,"Italy","Europe",null,"Namibia","Lower middle income",null,"Honduras","Lower middle income",null,33,"Mexico"]
[null,null,null,"Netherlands","Europe","Western Europe",null,"Netherlands","Europe",null,"Netherlands","High income",null,"India","Lower middle income",null,34,"Namibia"]
[null,null,null,"Nicaragua","Latin America and the Caribbean","Latin America and the Caribbean",null,"Poland","Europe",null,"Nicaragua","Lower middle income",null,"Jordan","Lower middle income",null,35,"Netherlands"]
[null,null,null,"Nigeria","Sub-Saharan Africa","Western Africa",null,"Portugal","Europe",null,"Nigeria","Lower middle income",null,"Kenya","Lower middle income",null,36,"Nicaragua"]
[null,null,null,"Pakistan","Asia-Pacific","Southern Asia",null,"Romania","Europe",null,"Pakistan","Lower middle income",null,"Lebanon","Lower middle income",null,37,"Nigeria"]
[null,null,null,"Paraguay","Latin America and the Caribbean","Latin America and the Caribbean",null,"Spain","Europe",null,"Paraguay","Upper middle income",null,"Namibia","Lower middle income",null,38,"Pakistan"]
[null,null,null,"Peru","Latin America and the Caribbean","Latin America and the Caribbean",null,"United Kingdom","Europe",null,"Peru","Upper middle income",null,"Nicaragua","Lower middle income",null,39,"Paraguay"]
[null,null,null,"Philippines","Asia-Pacific","Southeastern Asia",null,"Argentina","Latin America and the Caribbean",null,"Philippines","Lower middle income",null,"Nigeria","Lower middle income",null,40,"Peru"]
[null,null,null,"Poland","Europe","Eastern Europe",null,"Brazil","Latin America and the Caribbean",null,"Poland","High income",null,"Pakistan","Lower middle income",null,41,"Philippines"]
[null,null,null,"Portugal","Europe","Southern Europe",null,"Chile","Latin America and the Caribbean",null,"Portugal","High income",null,"Philippines","Lower middle income",null,42,"Poland"]
[null,null,null,"Qatar","Middle East and North Africa","Western Asia",null,"Colombia","Latin America and the Caribbean",null,"Qatar","High income",null,"Sri Lanka","Lower middle income",null,43,"Portugal"]
[null,null,null,"Romania","Europe","Eastern Europe",null,"Costa Rica","Latin America and the Caribbean",null,"Romania","High income",null,"Tanzania","Lower middle income",null,44,"Qatar"]
[null,null,null,"Rwanda","Sub-Saharan Africa","Eastern Africa",null,"Guatemala","Latin America and the Caribbean",null,"Rwanda","Low income",null,"Vietnam","Lower middle income",null,45,"Romania"]
[null,null,null,"Saudi Arabia","Middle East and North Africa","Western Asia",null,"Honduras","Latin America and the Caribbean",null,"Saudi Arabia","High income",null,"Algeria","Upper middle income",null,46,"Rwanda"]
[null,null,null,"Singapore","Asia-Pacific","Southeastern Asia",null,"Mexico","Latin America and the Caribbean",null,"Singapore","High income",null,"Argentina","Upper middle income",null,47,"Saudi Arabia"]
[null,null,null,"South Africa","Sub-Saharan Africa","Southern Africa",null,"Nicaragua","Latin America and the Caribbean",null,"South Africa","Upper middle income",null,"Brazil","Upper middle income",null,48,"Singapore"]
[null,null,null,"South Korea","Asia-Pacific","Eastern Asia",null,"Paraguay","Latin America and the Caribbean",null,"South Korea","High income",null,"China","Upper middle income",null,49,"South Africa"]
[null,null,null,"Spain","Europe","Southern Europe",null,"Peru","Latin America and the Caribbean",null,"Spain","High income",null,"Colombia","Upper middle income",null,50,"South Korea"]
[null,null,null,"Sri Lanka","Asia-Pacific","Southern Asia",null,"Algeria","Middle East and North Africa",null,"Sri Lanka","Lower middle income",null,"Guatemala","Upper middle income",null,51,"Spain"]
[null,null,null,"Tanzania","Sub-Saharan Africa","Eastern Africa",null,"Egypt","Middle East and North Africa",null,"Tanzania","Lower middle income",null,"Indonesia","Upper middle income",null,52,"Sri Lanka"]
[null,null,null,"Thailand","Asia-Pacific","Southeastern Asia",null,"Israel","Middle East and North Africa",null,"Thailand","Upper middle income",null,"Malaysia","Upper middle income",null,53,"Tanzania"]
[null,null,null,"Turkey","Middle East and North Africa","Western Asia",null,"Jordan","Middle East and North Africa",null,"Turkey","Upper middle income",null,"Mexico","Upper middle income",null,54,"Thailand"]
[null,null,null,"Uganda","Sub-Saharan Africa","Eastern Africa",null,"Lebanon","Middle East and North Africa",null,"Uganda","Low income",null,"Paraguay","Upper middle income",null,55,"Turkey"]
[null,null,null,"United Arab Emirates","Middle East and North Africa","Western Asia",null,"Qatar","Middle East and North Africa",null,"United Arab Emirates","High income",null,"Peru","Upper middle income",null,56,"Uganda"]
[null,null,null,"United Kingdom","Europe","Northern Europe",null,"Saudi Arabia","Middle East and North Africa",null,"United Kingdom","High income",null,"South Africa","Upper middle income",null,57,"United Arab Emirates"]
[null,null,null,"United States","North America","Northern America",null,"Turkey","Middle East and North Africa",null,"United States","High income",null,"Thailand","Upper middle income",null,58,"United Kingdom"]
[null,null,null,"Vietnam","Asia-Pacific","Southeastern Asia",null,"United Arab Emirates","Middle East and North Africa",null,"Vietnam","Lower middle income",null,"Turkey","Upper middle income",null,59,"United States"]
[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,60,"Vietnam"]
[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,61,"AVERAGE"]

{"sheet":"Selected values_pillars","index":10,"n_rows":67,"n_cols":59,"rows_kept":67,"cut":false,"hidden":false,"merged":[]}
[null,"B","C","D","E","F","G","H","I","J","K",null,null,"N","O","P","Q","R","S","T","U","V","W",null,null,"Z","AA","AB","AC","AD","AE","AF","AG","AH","AI",null,null,"AL","AM","AN","AO","AP","AQ","AR","AS","AT","AU",null,null,"AX","AY","AZ","BA","BB","BC","BD","BE","BF","BG"]
["Selected indicator: ",null,null,null,null,null,null,null,null,null,null,null,"Selected indicator: ",null,null,null,null,null,null,null,null,null,null,null,"Selected indicator: ",null,null,null,null,null,null,null,null,null,null,null,"Selected indicator: ",null,null,null,null,null,null,null,null,null,null,null,"Selected indicator: "]
[0,{"$f":"INDEX(Lists_indicators!$G$2:$G$107,MATCH(A$3,Lists_indicators!$D$2:$D$106))","v":"Overall index"},null,null,null,null,null,null,null,null,null,null,1,{"$f":"INDEX(Lists_indicators!$G$2:$G$92,MATCH(M$3,Lists_indicators!$D$2:$D$91))","v":"Affordability"},null,null,null,null,null,null,null,null,null,null,2,{"$f":"INDEX(Lists_indicators!$G$2:$G$107,MATCH(Y$3,Lists_indicators!$D$2:$D$106))","v":"Availability"},null,null,null,null,null,null,null,null,null,null,3,{"$f":"INDEX(Lists_indicators!$G$2:$G$107,MATCH(AK$3,Lists_indicators!$D$2:$D$106))","v":"Quality and safety"},null,null,null,null,null,null,null,null,null,null,4,{"$f":"INDEX(Lists_indicators!$G$2:$G$107,MATCH(AW$3,Lists_indicators!$D$2:$D$106))","v":"Climate risk responsiveness"}]
[{"$f":"PILLARS!$B$7","v":"Global"},{"$f":"INDEX(Lists_countries!$R$1:$AB$1, MATCH(A4,Lists_countries!$R$2:$AB$2,0))","v":61},null,null,null,null,null,null,null,null,null,null,{"$f":"PILLARS!$B$7","v":"Global"},{"$f":"INDEX(Lists_countries!$R$1:$AB$1, MATCH(M4,Lists_countries!$R$2:$AB$2,0))","v":61},null,null,null,null,null,null,null,null,null,null,{"$f":"PILLARS!$B$7","v":"Global"},{"$f":"INDEX(Lists_countries!$R$1:$AB$1, MATCH(Y4,Lists_countries!$R$2:$AB$2,0))","v":61},null,null,null,null,null,null,null,null,null,null,{"$f":"PILLARS!$B$7","v":"Global"},{"$f":"INDEX(Lists_countries!$R$1:$AB$1, MATCH(AK4,Lists_countries!$R$2:$AB$2,0))","v":61},null,null,null,null,null,null,null,null,null,null,{"$f":"PILLARS!$B$7","v":"Global"},{"$f":"INDEX(Lists_countries!$R$1:$AB$1, MATCH(AW4,Lists_countries!$R$2:$AB$2,0))","v":61}]
[]
[null,null,"Score","Rank_alphabetical","Rank_unique","Rank_shared",null,"Re-ordered",null,null,null,null,null,null,"Score","Rank_alphabetical","Rank_unique","Rank_shared",null,"Re-ordered",null,null,null,null,null,null,"Score","Rank_alphabetical","Rank_unique","Rank_shared",null,"Re-ordered",null,null,null,null,null,null,"Score","Rank_alphabetical","Rank_unique","Rank_shared",null,"Re-ordered",null,null,null,null,null,null,"Score","Rank_alphabetical","Rank_unique","Rank_shared",null,"Re-ordered"]
[1,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A7,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A7,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A7,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Algeria"},{"$f":"IF(B7=\"\",\"\",IF(B7=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH(A$3,'SCORE TABLE'!$B$10:$B$101,0), MATCH(B7,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":64.66},{"$f":"IF(B7=\"\",\"\",A7)","v":1},{"$f":"IF(B7=\"\",\"\",IF(C7=\"Not scored\",D7,(RANK(C7,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C7,C7)-1)))","v":32},{"$f":"IF(B7=\"\",\"\",IF(C7=\"Not scored\",D7,(SUMPRODUCT((C7<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":32},{"$f":"IF(B7=\"\",\"\",IF(B7=\"AVERAGE\",\"\",IF(C7=\"Not scored\",D7,(SUMPRODUCT((C7<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":32},{"$f":"IF(B7=\"\",\"\",INDEX(B$7:B$159,MATCH(A7,E$7:E$159,0)))","v":"Portugal"},{"$f":"IF(B7=\"\",\"\",IF(H7=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H7, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H7,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H7,B$7:B$159,0)),1)))))","v":1},{"$f":"IF(B7=\"\",\"\",IF(K7=K8,CONCATENATE(\"=\",K7),K7))","v":1},{"$f":"IF(B7=\"\",\"\",I7)","v":1},null,1,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(M7,Lists_countries!$Q$3:$Q$155,0),MATCH(M$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(M7,Lists_countries!$Q$3:$Q$155,0),MATCH(M$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(N$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(M7,Lists_countries!$Q$3:$Q$155,0),MATCH(M$4,Lists_countries!$R$2:$AB$2,0))))","v":"Algeria"},{"$f":"IF(N7=\"\",\"\",IF(N7=\"AVERAGE\",AVERAGE(O$7:INDIRECT(O$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH(M$3,'SCORE TABLE'!$B$10:$B$101,0), MATCH(N7,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":77.38},{"$f":"IF(N7=\"\",\"\",M7)","v":1},{"$f":"IF(N7=\"\",\"\",IF(O7=\"Not scored\",P7,(RANK(O7,O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4),0)+COUNTIF(O$7:O7,O7)-1)))","v":28},{"$f":"IF(N7=\"\",\"\",IF(O7=\"Not scored\",P7,(SUMPRODUCT((O7<=O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4))/COUNTIF(O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4),O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4))))))","v":28},{"$f":"IF(N7=\"\",\"\",IF(N7=\"AVERAGE\",\"\",IF(O7=\"Not scored\",P7,(SUMPRODUCT((O7<=O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4-1))/COUNTIF(O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4),O$7:INDIRECT(O$1&(ROW(Q$7)-1)+N$4-1)))))))","v":28},{"$f":"IF(N7=\"\",\"\",INDEX(N$7:N$159,MATCH(M7,Q$7:Q$159,0)))","v":"United Kingdom"},{"$f":"IF(N7=\"\",\"\",IF(T7=\"AVERAGE\",\"\", IF(COUNTIF(T$7:T7, \"AVERAGE\") < 1, (ROUNDUP(INDEX(R$7:R$159,MATCH(T7,N$7:N$159,0)),1)), (ROUNDUP(INDEX(S$7:S$158,MATCH(T7,N$7:N$159,0)),1)))))","v":1},{"$f":"IF(N7=\"\",\"\",IF(W7=W8,CONCATENATE(\"=\",W7),W7))","v":1},{"$f":"IF(N7=\"\",\"\",U7)","v":1},null,1,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(Y7,Lists_countries!$Q$3:$Q$155,0),MATCH(Y$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(Y7,Lists_countries!$Q$3:$Q$155,0),MATCH(Y$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(Z$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(Y7,Lists_countries!$Q$3:$Q$155,0),MATCH(Y$4,Lists_countries!$R$2:$AB$2,0))))","v":"Algeria"},{"$f":"IF(Z7=\"\",\"\",IF(Z7=\"AVERAGE\",AVERAGE(AA$7:INDIRECT(AA$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH(Y$3,'SCORE TABLE'!$B$10:$B$101,0), MATCH(Z7,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":53.04},{"$f":"IF(Z7=\"\",\"\",Y7)","v":1},{"$f":"IF(Z7=\"\",\"\",IF(AA7=\"Not scored\",AB7,(RANK(AA7,AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4),0)+COUNTIF(AA$7:AA7,AA7)-1)))","v":46},{"$f":"IF(Z7=\"\",\"\",IF(AA7=\"Not scored\",AB7,(SUMPRODUCT((AA7<=AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4))/COUNTIF(AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4),AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4))))))","v":46},{"$f":"IF(Z7=\"\",\"\",IF(Z7=\"AVERAGE\",\"\",IF(AA7=\"Not scored\",AB7,(SUMPRODUCT((AA7<=AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4-1))/COUNTIF(AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4),AA$7:INDIRECT(AA$1&(ROW(AC$7)-1)+Z$4-1)))))))","v":45},{"$f":"IF(Z7=\"\",\"\",INDEX(Z$7:Z$159,MATCH(Y7,AC$7:AC$159,0)))","v":"Chile"},{"$f":"IF(Z7=\"\",\"\",IF(AF7=\"AVERAGE\",\"\", IF(COUNTIF(AF$7:AF7, \"AVERAGE\") < 1, (ROUNDUP(INDEX(AD$7:AD$159,MATCH(AF7,Z$7:Z$159,0)),1)), (ROUNDUP(INDEX(AE$7:AE$158,MATCH(AF7,Z$7:Z$159,0)),1)))))","v":1},{"$f":"IF(Z7=\"\",\"\",IF(AI7=AI8,CONCATENATE(\"=\",AI7),AI7))","v":1},{"$f":"IF(Z7=\"\",\"\",AG7)","v":1},null,1,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(AK7,Lists_countries!$Q$3:$Q$155,0),MATCH(AK$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(AK7,Lists_countries!$Q$3:$Q$155,0),MATCH(AK$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(AL$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(AK7,Lists_countries!$Q$3:$Q$155,0),MATCH(AK$4,Lists_countries!$R$2:$AB$2,0))))","v":"Algeria"},{"$f":"IF(AL7=\"\",\"\",IF(AL7=\"AVERAGE\",AVERAGE(AM$7:INDIRECT(AM$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH(AK$3,'SCORE TABLE'!$B$10:$B$101,0), MATCH(AL7,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":65.48},{"$f":"IF(AL7=\"\",\"\",AK7)","v":1},{"$f":"IF(AL7=\"\",\"\",IF(AM7=\"Not scored\",AN7,(RANK(AM7,AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4),0)+COUNTIF(AM$7:AM7,AM7)-1)))","v":37},{"$f":"IF(AL7=\"\",\"\",IF(AM7=\"Not scored\",AN7,(SUMPRODUCT((AM7<=AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4))/COUNTIF(AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4),AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4))))))","v":36},{"$f":"IF(AL7=\"\",\"\",IF(AL7=\"AVERAGE\",\"\",IF(AM7=\"Not scored\",AN7,(SUMPRODUCT((AM7<=AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4-1))/COUNTIF(AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4),AM$7:INDIRECT(AM$1&(ROW(AO$7)-1)+AL$4-1)))))))","v":35},{"$f":"IF(AL7=\"\",\"\",INDEX(AL$7:AL$159,MATCH(AK7,AO$7:AO$159,0)))","v":"France"},{"$f":"IF(AL7=\"\",\"\",IF(AR7=\"AVERAGE\",\"\", IF(COUNTIF(AR$7:AR7, \"AVERAGE\") < 1, (ROUNDUP(INDEX(AP$7:AP$159,MATCH(AR7,AL$7:AL$159,0)),1)), (ROUNDUP(INDEX(AQ$7:AQ$158,MATCH(AR7,AL$7:AL$159,0)),1)))))","v":1},{"$f":"IF(AL7=\"\",\"\",IF(AU7=AU8,CONCATENATE(\"=\",AU7),AU7))","v":1},{"$f":"IF(AL7=\"\",\"\",AS7)","v":1},null,1,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(AW7,Lists_countries!$Q$3:$Q$155,0),MATCH(AW$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(AW7,Lists_countries!$Q$3:$Q$155,0),MATCH(AW$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(AX$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(AW7,Lists_countries!$Q$3:$Q$155,0),MATCH(AW$4,Lists_countries!$R$2:$AB$2,0))))","v":"Algeria"},{"$f":"IF(AX7=\"\",\"\",IF(AX7=\"AVERAGE\",AVERAGE(AY$7:INDIRECT(AY$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$101, MATCH(AW$3,'SCORE TABLE'!$B$10:$B$101,0), MATCH(AX7,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":62.45},{"$f":"IF(AX7=\"\",\"\",AW7)","v":1},{"$f":"IF(AX7=\"\",\"\",IF(AY7=\"Not scored\",AZ7,(RANK(AY7,AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4),0)+COUNTIF(AY$7:AY7,AY7)-1)))","v":12},{"$f":"IF(AX7=\"\",\"\",IF(AY7=\"Not scored\",AZ7,(SUMPRODUCT((AY7<=AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4))/COUNTIF(AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4),AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4))))))","v":12},{"$f":"IF(AX7=\"\",\"\",IF(AX7=\"AVERAGE\",\"\",IF(AY7=\"Not scored\",AZ7,(SUMPRODUCT((AY7<=AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4-1))/COUNTIF(AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4),AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4-1)))))))","v":12},{"$f":"IF(AX7=\"\",\"\",INDEX(AX$7:AX$159,MATCH(AW7,BA$7:BA$159,0)))","v":"United Kingdom"},{"$f":"IF(AX7=\"\",\"\",IF(BD7=\"AVERAGE\",\"\", IF(COUNTIF(BD$7:BD7, \"AVERAGE\") < 1, (ROUNDUP(INDEX(BB$7:BB$159,MATCH(BD7,AX$7:AX$159,0)),1)), (ROUNDUP(INDEX(BC$7:BC$158,MATCH(BD7,AX$7:AX$159,0)),1)))))","v":1},{"$f":"IF(AX7=\"\",\"\",IF(BG7=BG8,CONCATENATE(\"=\",BG7),BG7))","v":1},{"$f":"IF(AX7=\"\",\"\",BE7)","v":1}]
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scored\")))","v":56.429166666666653},61,{"$f":"IF(AX67=\"\",\"\",IF(AY67=\"Not scored\",AZ67,(RANK(AY67,AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4),0)+COUNTIF(AY$7:AY67,AY67)-1)))","v":37},{"$f":"IF(AX67=\"\",\"\",IF(AY67=\"Not scored\",AZ67,(SUMPRODUCT((AY67<=AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4))/COUNTIF(AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4),AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4))))))","v":37},{"$f":"IF(AX67=\"\",\"\",IF(AX67=\"AVERAGE\",\"\",IF(AY67=\"Not scored\",AZ67,(SUMPRODUCT((AY67<=AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4-1))/COUNTIF(AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4),AY$7:INDIRECT(AY$1&(ROW(BA$7)-1)+AX$4-1)))))))","v":""},"Romania",{"$f":"IF(AX67=\"\",\"\",IF(BD67=\"AVERAGE\",\"\", IF(COUNTIF(BD$7:BD67, \"AVERAGE\") < 1, (ROUNDUP(INDEX(BB$7:BB$159,MATCH(BD67,AX$7:AX$159,0)),1)), (ROUNDUP(INDEX(BC$7:BC$158,MATCH(BD67,AX$7:AX$159,0)),1)))))","v":59},60,{"$f":"IF(AX67=\"\",\"\",IF(BD67=\"AVERAGE\",\"\",IF(BG66=\"\",IF(BE67=BE65,BG65,COUNTIFS(BG$5:BG65,BG65)+BG65),IF(BE67=BE66,BG66,COUNTIFS(BG$5:BG66,BG66)+BG66))))","v":60}]

{"sheet":"Selected values_indicators","index":11,"n_rows":67,"n_cols":23,"rows_kept":67,"cut":false,"hidden":false,"merged":[]}
[null,"B","C","D","E","F","G","H","I","J","K",null,null,"N","O","P","Q","R","S","T","U","V","W"]
["Selected indicator: "]
[{"$f":"INDICATORS!$B$9","v":1.2},{"$f":"INDEX(Lists_indicators!$G$2:$G$105,MATCH(A$3,Lists_indicators!$D$2:$D$105))","v":"Affordability >> Affordability of a healthy diet"}]
[{"$f":"INDICATORS!$G$7","v":"Sub-Saharan Africa"},{"$f":"INDEX(Lists_countries!$R$1:$AB$1, MATCH(A4,Lists_countries!$R$2:$AB$2,0))","v":11}]
[]
[null,null,"Score","Rank_alphabetical","Rank_unique","Rank_shared",null,"Re-ordered",null,null,null,null,null,null,null,null,null,null,"Score","Global rank"]
[1,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A7,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A7,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A7,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Congo (Democratic Republic)"},{"$f":"IF(B7=\"\",\"\",IF(B7=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B7,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":0},{"$f":"IF(B7=\"\",\"\",A7)","v":1},{"$f":"IF(B7=\"\",\"\",IF(C7=\"Not scored\",D7,(RANK(C7,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C7,C7)-1)))","v":11},{"$f":"IF(B7=\"\",\"\",IF(C7=\"Not scored\",D7,(SUMPRODUCT((C7<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":11},{"$f":"IF(B7=\"\",\"\",IF(B7=\"AVERAGE\",\"\",IF(C7=\"Not scored\",D7,(SUMPRODUCT((C7<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":10},{"$f":"IF(B7=\"\",\"\",INDEX(B$7:B$159,MATCH(A7,E$7:E$159,0)))","v":"South Africa"},{"$f":"IF(B7=\"\",\"\",IF(H7=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H7, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H7,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H7,B$7:B$159,0)),1)))))","v":1},{"$f":"IF(B7=\"\",\"\",IF(K7=K8,CONCATENATE(\"=\",K7),K7))","v":1},{"$f":"IF(B7=\"\",\"\",I7)","v":1},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C7=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C7,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":60}]
[2,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A8,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A8,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A8,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Ethiopia"},{"$f":"IF(B8=\"\",\"\",IF(B8=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B8,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":28.25},{"$f":"IF(B8=\"\",\"\",A8)","v":2},{"$f":"IF(B8=\"\",\"\",IF(C8=\"Not scored\",D8,(RANK(C8,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C8,C8)-1)))","v":10},{"$f":"IF(B8=\"\",\"\",IF(C8=\"Not scored\",D8,(SUMPRODUCT((C8<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":10},{"$f":"IF(B8=\"\",\"\",IF(B8=\"AVERAGE\",\"\",IF(C8=\"Not scored\",D8,(SUMPRODUCT((C8<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":9},{"$f":"IF(B8=\"\",\"\",INDEX(B$7:B$159,MATCH(A8,E$7:E$159,0)))","v":"Namibia"},{"$f":"IF(B8=\"\",\"\",IF(H8=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H8, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H8,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H8,B$7:B$159,0)),1)))))","v":2},{"$f":"IF(B8=\"\",\"\",IF(K8=K7,CONCATENATE(\"=\",K8), IF(K8=K9,CONCATENATE(\"=\",K8),K8)))","v":2},{"$f":"IF(B8=\"\",\"\",IF(H8=\"AVERAGE\",\"\",IF(K7=\"\",IF(I8=I6,K6,COUNTIFS(K$5:K6,K6)+K6),IF(I8=I7,K7,COUNTIFS(K$5:K7,K7)+K7))))","v":2},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C8=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C8,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":59}]
[3,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A9,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A9,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A9,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Ghana"},{"$f":"IF(B9=\"\",\"\",IF(B9=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B9,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":73.12},3,{"$f":"IF(B9=\"\",\"\",IF(C9=\"Not scored\",D9,(RANK(C9,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C9,C9)-1)))","v":3},{"$f":"IF(B9=\"\",\"\",IF(C9=\"Not scored\",D9,(SUMPRODUCT((C9<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":3},{"$f":"IF(B9=\"\",\"\",IF(B9=\"AVERAGE\",\"\",IF(C9=\"Not scored\",D9,(SUMPRODUCT((C9<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":3},"Ghana",{"$f":"IF(B9=\"\",\"\",IF(H9=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H9, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H9,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H9,B$7:B$159,0)),1)))))","v":3},3,{"$f":"IF(B9=\"\",\"\",IF(H9=\"AVERAGE\",\"\",IF(K8=\"\",IF(I9=I7,K7,COUNTIFS(K$5:K7,K7)+K7),IF(I9=I8,K8,COUNTIFS(K$5:K8,K8)+K8))))","v":3},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C9=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C9,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":50}]
[4,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A10,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A10,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A10,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Kenya"},{"$f":"IF(B10=\"\",\"\",IF(B10=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B10,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":68.92},4,{"$f":"IF(B10=\"\",\"\",IF(C10=\"Not scored\",D10,(RANK(C10,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C10,C10)-1)))","v":4},{"$f":"IF(B10=\"\",\"\",IF(C10=\"Not scored\",D10,(SUMPRODUCT((C10<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":4},{"$f":"IF(B10=\"\",\"\",IF(B10=\"AVERAGE\",\"\",IF(C10=\"Not scored\",D10,(SUMPRODUCT((C10<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":4},"Kenya",{"$f":"IF(B10=\"\",\"\",IF(H10=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H10, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H10,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H10,B$7:B$159,0)),1)))))","v":4},4,{"$f":"IF(B10=\"\",\"\",IF(H10=\"AVERAGE\",\"\",IF(K9=\"\",IF(I10=I8,K8,COUNTIFS(K$5:K8,K8)+K8),IF(I10=I9,K9,COUNTIFS(K$5:K9,K9)+K9))))","v":4},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C10=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C10,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":54}]
[5,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A11,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A11,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A11,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Namibia"},{"$f":"IF(B11=\"\",\"\",IF(B11=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B11,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":81.099999999999994},5,{"$f":"IF(B11=\"\",\"\",IF(C11=\"Not scored\",D11,(RANK(C11,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C11,C11)-1)))","v":2},{"$f":"IF(B11=\"\",\"\",IF(C11=\"Not scored\",D11,(SUMPRODUCT((C11<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":2},{"$f":"IF(B11=\"\",\"\",IF(B11=\"AVERAGE\",\"\",IF(C11=\"Not scored\",D11,(SUMPRODUCT((C11<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":2},"Nigeria",{"$f":"IF(B11=\"\",\"\",IF(H11=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H11, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H11,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H11,B$7:B$159,0)),1)))))","v":5},5,{"$f":"IF(B11=\"\",\"\",IF(H11=\"AVERAGE\",\"\",IF(K10=\"\",IF(I11=I9,K9,COUNTIFS(K$5:K9,K9)+K9),IF(I11=I10,K10,COUNTIFS(K$5:K10,K10)+K10))))","v":5},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C11=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C11,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":47}]
[6,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A12,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A12,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A12,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Nigeria"},{"$f":"IF(B12=\"\",\"\",IF(B12=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B12,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":64.45},6,{"$f":"IF(B12=\"\",\"\",IF(C12=\"Not scored\",D12,(RANK(C12,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C12,C12)-1)))","v":5},{"$f":"IF(B12=\"\",\"\",IF(C12=\"Not scored\",D12,(SUMPRODUCT((C12<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":5},{"$f":"IF(B12=\"\",\"\",IF(B12=\"AVERAGE\",\"\",IF(C12=\"Not scored\",D12,(SUMPRODUCT((C12<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":5},"Tanzania",{"$f":"IF(B12=\"\",\"\",IF(H12=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H12, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H12,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H12,B$7:B$159,0)),1)))))","v":6},6,{"$f":"IF(B12=\"\",\"\",IF(H12=\"AVERAGE\",\"\",IF(K11=\"\",IF(I12=I10,K10,COUNTIFS(K$5:K10,K10)+K10),IF(I12=I11,K11,COUNTIFS(K$5:K11,K11)+K11))))","v":6},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C12=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C12,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":55}]
[7,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A13,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A13,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A13,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Rwanda"},{"$f":"IF(B13=\"\",\"\",IF(B13=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B13,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":40.229999999999997},7,{"$f":"IF(B13=\"\",\"\",IF(C13=\"Not scored\",D13,(RANK(C13,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C13,C13)-1)))","v":9},{"$f":"IF(B13=\"\",\"\",IF(C13=\"Not scored\",D13,(SUMPRODUCT((C13<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":9},{"$f":"IF(B13=\"\",\"\",IF(B13=\"AVERAGE\",\"\",IF(C13=\"Not scored\",D13,(SUMPRODUCT((C13<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":8},"AVERAGE",{"$f":"IF(B13=\"\",\"\",IF(H13=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H13, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H13,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H13,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B13=\"\",\"\",IF(H13=\"AVERAGE\",\"\",IF(K12=\"\",IF(I13=I11,K11,COUNTIFS(K$5:K11,K11)+K11),IF(I13=I12,K12,COUNTIFS(K$5:K12,K12)+K12))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C13=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C13,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":58}]
[8,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A14,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A14,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A14,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"South Africa"},{"$f":"IF(B14=\"\",\"\",IF(B14=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B14,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":88.49},8,{"$f":"IF(B14=\"\",\"\",IF(C14=\"Not scored\",D14,(RANK(C14,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C14,C14)-1)))","v":1},{"$f":"IF(B14=\"\",\"\",IF(C14=\"Not scored\",D14,(SUMPRODUCT((C14<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":1},{"$f":"IF(B14=\"\",\"\",IF(B14=\"AVERAGE\",\"\",IF(C14=\"Not scored\",D14,(SUMPRODUCT((C14<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":1},"Uganda",{"$f":"IF(B14=\"\",\"\",IF(H14=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H14, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H14,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H14,B$7:B$159,0)),1)))))","v":7},7,{"$f":"IF(B14=\"\",\"\",IF(H14=\"AVERAGE\",\"\",IF(K13=\"\",IF(I14=I12,K12,COUNTIFS(K$5:K12,K12)+K12),IF(I14=I13,K13,COUNTIFS(K$5:K13,K13)+K13))))","v":7},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C14=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C14,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":36}]
[9,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A15,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A15,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A15,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Tanzania"},{"$f":"IF(B15=\"\",\"\",IF(B15=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B15,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":61.18},9,{"$f":"IF(B15=\"\",\"\",IF(C15=\"Not scored\",D15,(RANK(C15,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C15,C15)-1)))","v":6},{"$f":"IF(B15=\"\",\"\",IF(C15=\"Not scored\",D15,(SUMPRODUCT((C15<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":6},{"$f":"IF(B15=\"\",\"\",IF(B15=\"AVERAGE\",\"\",IF(C15=\"Not scored\",D15,(SUMPRODUCT((C15<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":6},"Rwanda",{"$f":"IF(B15=\"\",\"\",IF(H15=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H15, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H15,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H15,B$7:B$159,0)),1)))))","v":8},{"$f":"IF(B15=\"\",\"\",IF(K15=K14,CONCATENATE(\"=\",K15), IF(K15=K16,CONCATENATE(\"=\",K15),K15)))","v":8},{"$f":"IF(B15=\"\",\"\",IF(H15=\"AVERAGE\",\"\",IF(K14=\"\",IF(I15=I13,K13,COUNTIFS(K$5:K13,K13)+K13),IF(I15=I14,K14,COUNTIFS(K$5:K14,K14)+K14))))","v":8},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C15=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C15,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":56}]
[10,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A16,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A16,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A16,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":"Uganda"},{"$f":"IF(B16=\"\",\"\",IF(B16=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B16,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":45.41},10,{"$f":"IF(B16=\"\",\"\",IF(C16=\"Not scored\",D16,(RANK(C16,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C16,C16)-1)))","v":8},{"$f":"IF(B16=\"\",\"\",IF(C16=\"Not scored\",D16,(SUMPRODUCT((C16<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":8},{"$f":"IF(B16=\"\",\"\",IF(B16=\"AVERAGE\",\"\",IF(C16=\"Not scored\",D16,(SUMPRODUCT((C16<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":7},"Ethiopia",{"$f":"IF(B16=\"\",\"\",IF(H16=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H16, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H16,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H16,B$7:B$159,0)),1)))))","v":9},9,{"$f":"IF(B16=\"\",\"\",IF(H16=\"AVERAGE\",\"\",IF(K15=\"\",IF(I16=I14,K14,COUNTIFS(K$5:K14,K14)+K14),IF(I16=I15,K15,COUNTIFS(K$5:K15,K15)+K15))))","v":9},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C16=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C16,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":57}]
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[13,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A19,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A19,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A19,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B19=\"\",\"\",IF(B19=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B19,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B19=\"\",\"\",IF(C19=\"Not scored\",D19,(RANK(C19,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C19,C19)-1)))","v":""},{"$f":"IF(B19=\"\",\"\",IF(C19=\"Not scored\",D19,(SUMPRODUCT((C19<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B19=\"\",\"\",IF(B19=\"AVERAGE\",\"\",IF(C19=\"Not scored\",D19,(SUMPRODUCT((C19<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B19=\"\",\"\",IF(H19=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H19, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H19,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H19,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B19=\"\",\"\",IF(H19=\"AVERAGE\",\"\",IF(K18=\"\",IF(I19=I17,K17,COUNTIFS(K$5:K17,K17)+K17),IF(I19=I18,K18,COUNTIFS(K$5:K18,K18)+K18))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C19=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C19,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[14,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A20,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A20,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A20,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B20=\"\",\"\",IF(B20=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B20,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B20=\"\",\"\",IF(C20=\"Not scored\",D20,(RANK(C20,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C20,C20)-1)))","v":""},{"$f":"IF(B20=\"\",\"\",IF(C20=\"Not scored\",D20,(SUMPRODUCT((C20<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B20=\"\",\"\",IF(B20=\"AVERAGE\",\"\",IF(C20=\"Not scored\",D20,(SUMPRODUCT((C20<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B20=\"\",\"\",IF(H20=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H20, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H20,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H20,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B20=\"\",\"\",IF(H20=\"AVERAGE\",\"\",IF(K19=\"\",IF(I20=I18,K18,COUNTIFS(K$5:K18,K18)+K18),IF(I20=I19,K19,COUNTIFS(K$5:K19,K19)+K19))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C20=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C20,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[15,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A21,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A21,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A21,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B21=\"\",\"\",IF(B21=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B21,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B21=\"\",\"\",IF(C21=\"Not scored\",D21,(RANK(C21,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C21,C21)-1)))","v":""},{"$f":"IF(B21=\"\",\"\",IF(C21=\"Not scored\",D21,(SUMPRODUCT((C21<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B21=\"\",\"\",IF(B21=\"AVERAGE\",\"\",IF(C21=\"Not scored\",D21,(SUMPRODUCT((C21<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B21=\"\",\"\",IF(H21=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H21, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H21,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H21,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B21=\"\",\"\",IF(H21=\"AVERAGE\",\"\",IF(K20=\"\",IF(I21=I19,K19,COUNTIFS(K$5:K19,K19)+K19),IF(I21=I20,K20,COUNTIFS(K$5:K20,K20)+K20))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C21=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C21,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[16,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A22,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A22,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A22,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B22=\"\",\"\",IF(B22=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B22,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B22=\"\",\"\",IF(C22=\"Not scored\",D22,(RANK(C22,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C22,C22)-1)))","v":""},{"$f":"IF(B22=\"\",\"\",IF(C22=\"Not scored\",D22,(SUMPRODUCT((C22<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B22=\"\",\"\",IF(B22=\"AVERAGE\",\"\",IF(C22=\"Not scored\",D22,(SUMPRODUCT((C22<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B22=\"\",\"\",IF(H22=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H22, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H22,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H22,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B22=\"\",\"\",IF(H22=\"AVERAGE\",\"\",IF(K21=\"\",IF(I22=I20,K20,COUNTIFS(K$5:K20,K20)+K20),IF(I22=I21,K21,COUNTIFS(K$5:K21,K21)+K21))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C22=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C22,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[17,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A23,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A23,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A23,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B23=\"\",\"\",IF(B23=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B23,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B23=\"\",\"\",IF(C23=\"Not scored\",D23,(RANK(C23,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C23,C23)-1)))","v":""},{"$f":"IF(B23=\"\",\"\",IF(C23=\"Not scored\",D23,(SUMPRODUCT((C23<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B23=\"\",\"\",IF(B23=\"AVERAGE\",\"\",IF(C23=\"Not scored\",D23,(SUMPRODUCT((C23<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B23=\"\",\"\",IF(H23=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H23, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H23,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H23,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B23=\"\",\"\",IF(H23=\"AVERAGE\",\"\",IF(K22=\"\",IF(I23=I21,K21,COUNTIFS(K$5:K21,K21)+K21),IF(I23=I22,K22,COUNTIFS(K$5:K22,K22)+K22))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C23=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C23,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[18,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A24,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A24,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A24,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B24=\"\",\"\",IF(B24=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B24,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B24=\"\",\"\",IF(C24=\"Not scored\",D24,(RANK(C24,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C24,C24)-1)))","v":""},{"$f":"IF(B24=\"\",\"\",IF(C24=\"Not scored\",D24,(SUMPRODUCT((C24<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B24=\"\",\"\",IF(B24=\"AVERAGE\",\"\",IF(C24=\"Not scored\",D24,(SUMPRODUCT((C24<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B24=\"\",\"\",IF(H24=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H24, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H24,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H24,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B24=\"\",\"\",IF(H24=\"AVERAGE\",\"\",IF(K23=\"\",IF(I24=I22,K22,COUNTIFS(K$5:K22,K22)+K22),IF(I24=I23,K23,COUNTIFS(K$5:K23,K23)+K23))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C24=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C24,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[19,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A25,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A25,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A25,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B25=\"\",\"\",IF(B25=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B25,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B25=\"\",\"\",IF(C25=\"Not scored\",D25,(RANK(C25,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C25,C25)-1)))","v":""},{"$f":"IF(B25=\"\",\"\",IF(C25=\"Not scored\",D25,(SUMPRODUCT((C25<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B25=\"\",\"\",IF(B25=\"AVERAGE\",\"\",IF(C25=\"Not scored\",D25,(SUMPRODUCT((C25<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B25=\"\",\"\",IF(H25=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H25, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H25,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H25,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B25=\"\",\"\",IF(H25=\"AVERAGE\",\"\",IF(K24=\"\",IF(I25=I23,K23,COUNTIFS(K$5:K23,K23)+K23),IF(I25=I24,K24,COUNTIFS(K$5:K24,K24)+K24))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C25=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C25,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[20,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A26,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A26,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A26,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B26=\"\",\"\",IF(B26=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B26,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B26=\"\",\"\",IF(C26=\"Not scored\",D26,(RANK(C26,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C26,C26)-1)))","v":""},{"$f":"IF(B26=\"\",\"\",IF(C26=\"Not scored\",D26,(SUMPRODUCT((C26<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B26=\"\",\"\",IF(B26=\"AVERAGE\",\"\",IF(C26=\"Not scored\",D26,(SUMPRODUCT((C26<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B26=\"\",\"\",IF(H26=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H26, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H26,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H26,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B26=\"\",\"\",IF(H26=\"AVERAGE\",\"\",IF(K25=\"\",IF(I26=I24,K24,COUNTIFS(K$5:K24,K24)+K24),IF(I26=I25,K25,COUNTIFS(K$5:K25,K25)+K25))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C26=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C26,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[21,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A27,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A27,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A27,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B27=\"\",\"\",IF(B27=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B27,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B27=\"\",\"\",IF(C27=\"Not scored\",D27,(RANK(C27,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C27,C27)-1)))","v":""},{"$f":"IF(B27=\"\",\"\",IF(C27=\"Not scored\",D27,(SUMPRODUCT((C27<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B27=\"\",\"\",IF(B27=\"AVERAGE\",\"\",IF(C27=\"Not scored\",D27,(SUMPRODUCT((C27<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B27=\"\",\"\",IF(H27=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H27, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H27,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H27,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B27=\"\",\"\",IF(H27=\"AVERAGE\",\"\",IF(K26=\"\",IF(I27=I25,K25,COUNTIFS(K$5:K25,K25)+K25),IF(I27=I26,K26,COUNTIFS(K$5:K26,K26)+K26))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C27=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C27,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[22,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A28,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A28,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A28,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B28=\"\",\"\",IF(B28=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B28,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B28=\"\",\"\",IF(C28=\"Not scored\",D28,(RANK(C28,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C28,C28)-1)))","v":""},{"$f":"IF(B28=\"\",\"\",IF(C28=\"Not scored\",D28,(SUMPRODUCT((C28<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B28=\"\",\"\",IF(B28=\"AVERAGE\",\"\",IF(C28=\"Not scored\",D28,(SUMPRODUCT((C28<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B28=\"\",\"\",IF(H28=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H28, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H28,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H28,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B28=\"\",\"\",IF(H28=\"AVERAGE\",\"\",IF(K27=\"\",IF(I28=I26,K26,COUNTIFS(K$5:K26,K26)+K26),IF(I28=I27,K27,COUNTIFS(K$5:K27,K27)+K27))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C28=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C28,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[23,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A29,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A29,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A29,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B29=\"\",\"\",IF(B29=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B29,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B29=\"\",\"\",IF(C29=\"Not scored\",D29,(RANK(C29,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C29,C29)-1)))","v":""},{"$f":"IF(B29=\"\",\"\",IF(C29=\"Not scored\",D29,(SUMPRODUCT((C29<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B29=\"\",\"\",IF(B29=\"AVERAGE\",\"\",IF(C29=\"Not scored\",D29,(SUMPRODUCT((C29<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B29=\"\",\"\",IF(H29=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H29, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H29,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H29,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B29=\"\",\"\",IF(H29=\"AVERAGE\",\"\",IF(K28=\"\",IF(I29=I27,K27,COUNTIFS(K$5:K27,K27)+K27),IF(I29=I28,K28,COUNTIFS(K$5:K28,K28)+K28))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C29=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C29,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[24,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A30,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A30,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A30,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B30=\"\",\"\",IF(B30=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B30,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B30=\"\",\"\",IF(C30=\"Not scored\",D30,(RANK(C30,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C30,C30)-1)))","v":""},{"$f":"IF(B30=\"\",\"\",IF(C30=\"Not scored\",D30,(SUMPRODUCT((C30<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B30=\"\",\"\",IF(B30=\"AVERAGE\",\"\",IF(C30=\"Not scored\",D30,(SUMPRODUCT((C30<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B30=\"\",\"\",IF(H30=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H30, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H30,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H30,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B30=\"\",\"\",IF(H30=\"AVERAGE\",\"\",IF(K29=\"\",IF(I30=I28,K28,COUNTIFS(K$5:K28,K28)+K28),IF(I30=I29,K29,COUNTIFS(K$5:K29,K29)+K29))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C30=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C30,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[25,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A31,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A31,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A31,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B31=\"\",\"\",IF(B31=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B31,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B31=\"\",\"\",IF(C31=\"Not scored\",D31,(RANK(C31,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C31,C31)-1)))","v":""},{"$f":"IF(B31=\"\",\"\",IF(C31=\"Not scored\",D31,(SUMPRODUCT((C31<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B31=\"\",\"\",IF(B31=\"AVERAGE\",\"\",IF(C31=\"Not scored\",D31,(SUMPRODUCT((C31<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B31=\"\",\"\",IF(H31=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H31, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H31,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H31,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B31=\"\",\"\",IF(H31=\"AVERAGE\",\"\",IF(K30=\"\",IF(I31=I29,K29,COUNTIFS(K$5:K29,K29)+K29),IF(I31=I30,K30,COUNTIFS(K$5:K30,K30)+K30))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C31=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C31,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[26,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A32,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A32,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A32,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B32=\"\",\"\",IF(B32=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B32,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B32=\"\",\"\",IF(C32=\"Not scored\",D32,(RANK(C32,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C32,C32)-1)))","v":""},{"$f":"IF(B32=\"\",\"\",IF(C32=\"Not scored\",D32,(SUMPRODUCT((C32<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B32=\"\",\"\",IF(B32=\"AVERAGE\",\"\",IF(C32=\"Not scored\",D32,(SUMPRODUCT((C32<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B32=\"\",\"\",IF(H32=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H32, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H32,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H32,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B32=\"\",\"\",IF(H32=\"AVERAGE\",\"\",IF(K31=\"\",IF(I32=I30,K30,COUNTIFS(K$5:K30,K30)+K30),IF(I32=I31,K31,COUNTIFS(K$5:K31,K31)+K31))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C32=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C32,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[27,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A33,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A33,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A33,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B33=\"\",\"\",IF(B33=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B33,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B33=\"\",\"\",IF(C33=\"Not scored\",D33,(RANK(C33,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C33,C33)-1)))","v":""},{"$f":"IF(B33=\"\",\"\",IF(C33=\"Not scored\",D33,(SUMPRODUCT((C33<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B33=\"\",\"\",IF(B33=\"AVERAGE\",\"\",IF(C33=\"Not scored\",D33,(SUMPRODUCT((C33<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B33=\"\",\"\",IF(H33=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H33, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H33,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H33,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B33=\"\",\"\",IF(H33=\"AVERAGE\",\"\",IF(K32=\"\",IF(I33=I31,K31,COUNTIFS(K$5:K31,K31)+K31),IF(I33=I32,K32,COUNTIFS(K$5:K32,K32)+K32))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C33=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C33,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[28,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A34,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A34,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A34,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B34=\"\",\"\",IF(B34=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B34,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B34=\"\",\"\",IF(C34=\"Not scored\",D34,(RANK(C34,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C34,C34)-1)))","v":""},{"$f":"IF(B34=\"\",\"\",IF(C34=\"Not scored\",D34,(SUMPRODUCT((C34<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B34=\"\",\"\",IF(B34=\"AVERAGE\",\"\",IF(C34=\"Not scored\",D34,(SUMPRODUCT((C34<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B34=\"\",\"\",IF(H34=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H34, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H34,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H34,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B34=\"\",\"\",IF(H34=\"AVERAGE\",\"\",IF(K33=\"\",IF(I34=I32,K32,COUNTIFS(K$5:K32,K32)+K32),IF(I34=I33,K33,COUNTIFS(K$5:K33,K33)+K33))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C34=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C34,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[29,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A35,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A35,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A35,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B35=\"\",\"\",IF(B35=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B35,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B35=\"\",\"\",IF(C35=\"Not scored\",D35,(RANK(C35,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C35,C35)-1)))","v":""},{"$f":"IF(B35=\"\",\"\",IF(C35=\"Not scored\",D35,(SUMPRODUCT((C35<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B35=\"\",\"\",IF(B35=\"AVERAGE\",\"\",IF(C35=\"Not scored\",D35,(SUMPRODUCT((C35<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B35=\"\",\"\",IF(H35=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H35, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H35,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H35,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B35=\"\",\"\",IF(H35=\"AVERAGE\",\"\",IF(K34=\"\",IF(I35=I33,K33,COUNTIFS(K$5:K33,K33)+K33),IF(I35=I34,K34,COUNTIFS(K$5:K34,K34)+K34))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C35=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C35,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[30,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A36,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A36,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A36,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B36=\"\",\"\",IF(B36=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B36,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B36=\"\",\"\",IF(C36=\"Not scored\",D36,(RANK(C36,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C36,C36)-1)))","v":""},{"$f":"IF(B36=\"\",\"\",IF(C36=\"Not scored\",D36,(SUMPRODUCT((C36<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B36=\"\",\"\",IF(B36=\"AVERAGE\",\"\",IF(C36=\"Not scored\",D36,(SUMPRODUCT((C36<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B36=\"\",\"\",IF(H36=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H36, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H36,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H36,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B36=\"\",\"\",IF(H36=\"AVERAGE\",\"\",IF(K35=\"\",IF(I36=I34,K34,COUNTIFS(K$5:K34,K34)+K34),IF(I36=I35,K35,COUNTIFS(K$5:K35,K35)+K35))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C36=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C36,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[31,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A37,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A37,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A37,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B37=\"\",\"\",IF(B37=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B37,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B37=\"\",\"\",IF(C37=\"Not scored\",D37,(RANK(C37,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C37,C37)-1)))","v":""},{"$f":"IF(B37=\"\",\"\",IF(C37=\"Not scored\",D37,(SUMPRODUCT((C37<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B37=\"\",\"\",IF(B37=\"AVERAGE\",\"\",IF(C37=\"Not scored\",D37,(SUMPRODUCT((C37<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B37=\"\",\"\",IF(H37=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H37, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H37,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H37,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B37=\"\",\"\",IF(H37=\"AVERAGE\",\"\",IF(K36=\"\",IF(I37=I35,K35,COUNTIFS(K$5:K35,K35)+K35),IF(I37=I36,K36,COUNTIFS(K$5:K36,K36)+K36))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C37=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C37,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[32,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A38,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A38,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A38,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B38=\"\",\"\",IF(B38=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B38,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B38=\"\",\"\",IF(C38=\"Not scored\",D38,(RANK(C38,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C38,C38)-1)))","v":""},{"$f":"IF(B38=\"\",\"\",IF(C38=\"Not scored\",D38,(SUMPRODUCT((C38<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B38=\"\",\"\",IF(B38=\"AVERAGE\",\"\",IF(C38=\"Not scored\",D38,(SUMPRODUCT((C38<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B38=\"\",\"\",IF(H38=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H38, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H38,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H38,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B38=\"\",\"\",IF(H38=\"AVERAGE\",\"\",IF(K37=\"\",IF(I38=I36,K36,COUNTIFS(K$5:K36,K36)+K36),IF(I38=I37,K37,COUNTIFS(K$5:K37,K37)+K37))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C38=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C38,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[33,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A39,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A39,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A39,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B39=\"\",\"\",IF(B39=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B39,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B39=\"\",\"\",IF(C39=\"Not scored\",D39,(RANK(C39,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C39,C39)-1)))","v":""},{"$f":"IF(B39=\"\",\"\",IF(C39=\"Not scored\",D39,(SUMPRODUCT((C39<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B39=\"\",\"\",IF(B39=\"AVERAGE\",\"\",IF(C39=\"Not scored\",D39,(SUMPRODUCT((C39<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},{"$f":"IF(B39=\"\",\"\",INDEX(B$7:B$159,MATCH(A39,E$7:E$159,0)))","v":""},{"$f":"IF(B39=\"\",\"\",IF(H39=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H39, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H39,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H39,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B39=\"\",\"\",IF(H39=\"AVERAGE\",\"\",IF(K38=\"\",IF(I39=I37,K37,COUNTIFS(K$5:K37,K37)+K37),IF(I39=I38,K38,COUNTIFS(K$5:K38,K38)+K38))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C39=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C39,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[34,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A40,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A40,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A40,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B40=\"\",\"\",IF(B40=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B40,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B40=\"\",\"\",IF(C40=\"Not scored\",D40,(RANK(C40,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C40,C40)-1)))","v":""},{"$f":"IF(B40=\"\",\"\",IF(C40=\"Not scored\",D40,(SUMPRODUCT((C40<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B40=\"\",\"\",IF(B40=\"AVERAGE\",\"\",IF(C40=\"Not scored\",D40,(SUMPRODUCT((C40<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B40=\"\",\"\",IF(H40=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H40, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H40,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H40,B$7:B$159,0)),1)))))","v":""},{"$f":"IF(B40=\"\",\"\",IF(K40=K39,CONCATENATE(\"=\",K40), IF(K40=K41,CONCATENATE(\"=\",K40),K40)))","v":""},{"$f":"IF(B40=\"\",\"\",IF(H40=\"AVERAGE\",\"\",IF(K39=\"\",IF(I40=I38,K38,COUNTIFS(K$5:K38,K38)+K38),IF(I40=I39,K39,COUNTIFS(K$5:K39,K39)+K39))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C40=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C40,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[35,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A41,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A41,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A41,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B41=\"\",\"\",IF(B41=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B41,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B41=\"\",\"\",IF(C41=\"Not scored\",D41,(RANK(C41,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C41,C41)-1)))","v":""},{"$f":"IF(B41=\"\",\"\",IF(C41=\"Not scored\",D41,(SUMPRODUCT((C41<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B41=\"\",\"\",IF(B41=\"AVERAGE\",\"\",IF(C41=\"Not scored\",D41,(SUMPRODUCT((C41<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B41=\"\",\"\",IF(H41=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H41, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H41,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H41,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B41=\"\",\"\",IF(H41=\"AVERAGE\",\"\",IF(K40=\"\",IF(I41=I39,K39,COUNTIFS(K$5:K39,K39)+K39),IF(I41=I40,K40,COUNTIFS(K$5:K40,K40)+K40))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C41=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C41,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[36,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A42,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A42,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A42,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B42=\"\",\"\",IF(B42=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B42,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B42=\"\",\"\",IF(C42=\"Not scored\",D42,(RANK(C42,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C42,C42)-1)))","v":""},{"$f":"IF(B42=\"\",\"\",IF(C42=\"Not scored\",D42,(SUMPRODUCT((C42<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B42=\"\",\"\",IF(B42=\"AVERAGE\",\"\",IF(C42=\"Not scored\",D42,(SUMPRODUCT((C42<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B42=\"\",\"\",IF(H42=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H42, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H42,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H42,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B42=\"\",\"\",IF(H42=\"AVERAGE\",\"\",IF(K41=\"\",IF(I42=I40,K40,COUNTIFS(K$5:K40,K40)+K40),IF(I42=I41,K41,COUNTIFS(K$5:K41,K41)+K41))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C42=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C42,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[37,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A43,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A43,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A43,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B43=\"\",\"\",IF(B43=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B43,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B43=\"\",\"\",IF(C43=\"Not scored\",D43,(RANK(C43,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C43,C43)-1)))","v":""},{"$f":"IF(B43=\"\",\"\",IF(C43=\"Not scored\",D43,(SUMPRODUCT((C43<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B43=\"\",\"\",IF(B43=\"AVERAGE\",\"\",IF(C43=\"Not scored\",D43,(SUMPRODUCT((C43<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B43=\"\",\"\",IF(H43=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H43, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H43,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H43,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B43=\"\",\"\",IF(H43=\"AVERAGE\",\"\",IF(K42=\"\",IF(I43=I41,K41,COUNTIFS(K$5:K41,K41)+K41),IF(I43=I42,K42,COUNTIFS(K$5:K42,K42)+K42))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C43=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C43,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[38,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A44,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A44,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A44,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B44=\"\",\"\",IF(B44=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B44,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B44=\"\",\"\",IF(C44=\"Not scored\",D44,(RANK(C44,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C44,C44)-1)))","v":""},{"$f":"IF(B44=\"\",\"\",IF(C44=\"Not scored\",D44,(SUMPRODUCT((C44<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B44=\"\",\"\",IF(B44=\"AVERAGE\",\"\",IF(C44=\"Not scored\",D44,(SUMPRODUCT((C44<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B44=\"\",\"\",IF(H44=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H44, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H44,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H44,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B44=\"\",\"\",IF(H44=\"AVERAGE\",\"\",IF(K43=\"\",IF(I44=I42,K42,COUNTIFS(K$5:K42,K42)+K42),IF(I44=I43,K43,COUNTIFS(K$5:K43,K43)+K43))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C44=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C44,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[39,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A45,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A45,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A45,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B45=\"\",\"\",IF(B45=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B45,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B45=\"\",\"\",IF(C45=\"Not scored\",D45,(RANK(C45,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C45,C45)-1)))","v":""},{"$f":"IF(B45=\"\",\"\",IF(C45=\"Not scored\",D45,(SUMPRODUCT((C45<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B45=\"\",\"\",IF(B45=\"AVERAGE\",\"\",IF(C45=\"Not scored\",D45,(SUMPRODUCT((C45<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B45=\"\",\"\",IF(H45=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H45, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H45,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H45,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B45=\"\",\"\",IF(H45=\"AVERAGE\",\"\",IF(K44=\"\",IF(I45=I43,K43,COUNTIFS(K$5:K43,K43)+K43),IF(I45=I44,K44,COUNTIFS(K$5:K44,K44)+K44))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C45=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C45,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[40,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A46,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A46,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A46,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B46=\"\",\"\",IF(B46=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B46,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B46=\"\",\"\",IF(C46=\"Not scored\",D46,(RANK(C46,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C46,C46)-1)))","v":""},{"$f":"IF(B46=\"\",\"\",IF(C46=\"Not scored\",D46,(SUMPRODUCT((C46<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B46=\"\",\"\",IF(B46=\"AVERAGE\",\"\",IF(C46=\"Not scored\",D46,(SUMPRODUCT((C46<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B46=\"\",\"\",IF(H46=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H46, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H46,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H46,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B46=\"\",\"\",IF(H46=\"AVERAGE\",\"\",IF(K45=\"\",IF(I46=I44,K44,COUNTIFS(K$5:K44,K44)+K44),IF(I46=I45,K45,COUNTIFS(K$5:K45,K45)+K45))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C46=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C46,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[41,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A47,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A47,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A47,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B47=\"\",\"\",IF(B47=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B47,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B47=\"\",\"\",IF(C47=\"Not scored\",D47,(RANK(C47,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C47,C47)-1)))","v":""},{"$f":"IF(B47=\"\",\"\",IF(C47=\"Not scored\",D47,(SUMPRODUCT((C47<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B47=\"\",\"\",IF(B47=\"AVERAGE\",\"\",IF(C47=\"Not scored\",D47,(SUMPRODUCT((C47<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B47=\"\",\"\",IF(H47=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H47, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H47,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H47,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B47=\"\",\"\",IF(H47=\"AVERAGE\",\"\",IF(K46=\"\",IF(I47=I45,K45,COUNTIFS(K$5:K45,K45)+K45),IF(I47=I46,K46,COUNTIFS(K$5:K46,K46)+K46))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C47=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C47,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
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[43,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A49,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A49,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A49,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B49=\"\",\"\",IF(B49=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B49,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B49=\"\",\"\",IF(C49=\"Not scored\",D49,(RANK(C49,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C49,C49)-1)))","v":""},{"$f":"IF(B49=\"\",\"\",IF(C49=\"Not scored\",D49,(SUMPRODUCT((C49<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B49=\"\",\"\",IF(B49=\"AVERAGE\",\"\",IF(C49=\"Not scored\",D49,(SUMPRODUCT((C49<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B49=\"\",\"\",IF(H49=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H49, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H49,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H49,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B49=\"\",\"\",IF(H49=\"AVERAGE\",\"\",IF(K48=\"\",IF(I49=I47,K47,COUNTIFS(K$5:K47,K47)+K47),IF(I49=I48,K48,COUNTIFS(K$5:K48,K48)+K48))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C49=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C49,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[44,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A50,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A50,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A50,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B50=\"\",\"\",IF(B50=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B50,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B50=\"\",\"\",IF(C50=\"Not scored\",D50,(RANK(C50,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C50,C50)-1)))","v":""},{"$f":"IF(B50=\"\",\"\",IF(C50=\"Not scored\",D50,(SUMPRODUCT((C50<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B50=\"\",\"\",IF(B50=\"AVERAGE\",\"\",IF(C50=\"Not scored\",D50,(SUMPRODUCT((C50<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B50=\"\",\"\",IF(H50=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H50, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H50,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H50,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B50=\"\",\"\",IF(H50=\"AVERAGE\",\"\",IF(K49=\"\",IF(I50=I48,K48,COUNTIFS(K$5:K48,K48)+K48),IF(I50=I49,K49,COUNTIFS(K$5:K49,K49)+K49))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C50=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C50,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[45,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A51,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A51,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A51,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B51=\"\",\"\",IF(B51=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B51,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B51=\"\",\"\",IF(C51=\"Not scored\",D51,(RANK(C51,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C51,C51)-1)))","v":""},{"$f":"IF(B51=\"\",\"\",IF(C51=\"Not scored\",D51,(SUMPRODUCT((C51<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B51=\"\",\"\",IF(B51=\"AVERAGE\",\"\",IF(C51=\"Not scored\",D51,(SUMPRODUCT((C51<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B51=\"\",\"\",IF(H51=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H51, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H51,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H51,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B51=\"\",\"\",IF(H51=\"AVERAGE\",\"\",IF(K50=\"\",IF(I51=I49,K49,COUNTIFS(K$5:K49,K49)+K49),IF(I51=I50,K50,COUNTIFS(K$5:K50,K50)+K50))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C51=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C51,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[46,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A52,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A52,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A52,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B52=\"\",\"\",IF(B52=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B52,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B52=\"\",\"\",IF(C52=\"Not scored\",D52,(RANK(C52,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C52,C52)-1)))","v":""},{"$f":"IF(B52=\"\",\"\",IF(C52=\"Not scored\",D52,(SUMPRODUCT((C52<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B52=\"\",\"\",IF(B52=\"AVERAGE\",\"\",IF(C52=\"Not scored\",D52,(SUMPRODUCT((C52<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B52=\"\",\"\",IF(H52=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H52, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H52,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H52,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B52=\"\",\"\",IF(H52=\"AVERAGE\",\"\",IF(K51=\"\",IF(I52=I50,K50,COUNTIFS(K$5:K50,K50)+K50),IF(I52=I51,K51,COUNTIFS(K$5:K51,K51)+K51))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C52=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C52,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[47,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A53,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A53,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A53,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B53=\"\",\"\",IF(B53=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B53,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B53=\"\",\"\",IF(C53=\"Not scored\",D53,(RANK(C53,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C53,C53)-1)))","v":""},{"$f":"IF(B53=\"\",\"\",IF(C53=\"Not scored\",D53,(SUMPRODUCT((C53<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B53=\"\",\"\",IF(B53=\"AVERAGE\",\"\",IF(C53=\"Not scored\",D53,(SUMPRODUCT((C53<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B53=\"\",\"\",IF(H53=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H53, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H53,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H53,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B53=\"\",\"\",IF(H53=\"AVERAGE\",\"\",IF(K52=\"\",IF(I53=I51,K51,COUNTIFS(K$5:K51,K51)+K51),IF(I53=I52,K52,COUNTIFS(K$5:K52,K52)+K52))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C53=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C53,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
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[49,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A55,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A55,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A55,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B55=\"\",\"\",IF(B55=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B55,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B55=\"\",\"\",IF(C55=\"Not scored\",D55,(RANK(C55,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C55,C55)-1)))","v":""},{"$f":"IF(B55=\"\",\"\",IF(C55=\"Not scored\",D55,(SUMPRODUCT((C55<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B55=\"\",\"\",IF(B55=\"AVERAGE\",\"\",IF(C55=\"Not scored\",D55,(SUMPRODUCT((C55<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B55=\"\",\"\",IF(H55=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H55, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H55,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H55,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B55=\"\",\"\",IF(H55=\"AVERAGE\",\"\",IF(K54=\"\",IF(I55=I53,K53,COUNTIFS(K$5:K53,K53)+K53),IF(I55=I54,K54,COUNTIFS(K$5:K54,K54)+K54))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C55=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C55,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[50,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A56,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A56,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A56,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B56=\"\",\"\",IF(B56=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B56,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B56=\"\",\"\",IF(C56=\"Not scored\",D56,(RANK(C56,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C56,C56)-1)))","v":""},{"$f":"IF(B56=\"\",\"\",IF(C56=\"Not scored\",D56,(SUMPRODUCT((C56<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B56=\"\",\"\",IF(B56=\"AVERAGE\",\"\",IF(C56=\"Not scored\",D56,(SUMPRODUCT((C56<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B56=\"\",\"\",IF(H56=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H56, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H56,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H56,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B56=\"\",\"\",IF(H56=\"AVERAGE\",\"\",IF(K55=\"\",IF(I56=I54,K54,COUNTIFS(K$5:K54,K54)+K54),IF(I56=I55,K55,COUNTIFS(K$5:K55,K55)+K55))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C56=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C56,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[51,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A57,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A57,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A57,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B57=\"\",\"\",IF(B57=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B57,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B57=\"\",\"\",IF(C57=\"Not scored\",D57,(RANK(C57,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C57,C57)-1)))","v":""},{"$f":"IF(B57=\"\",\"\",IF(C57=\"Not scored\",D57,(SUMPRODUCT((C57<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B57=\"\",\"\",IF(B57=\"AVERAGE\",\"\",IF(C57=\"Not scored\",D57,(SUMPRODUCT((C57<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B57=\"\",\"\",IF(H57=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H57, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H57,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H57,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B57=\"\",\"\",IF(H57=\"AVERAGE\",\"\",IF(K56=\"\",IF(I57=I55,K55,COUNTIFS(K$5:K55,K55)+K55),IF(I57=I56,K56,COUNTIFS(K$5:K56,K56)+K56))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C57=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C57,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[52,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A58,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A58,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A58,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B58=\"\",\"\",IF(B58=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B58,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B58=\"\",\"\",IF(C58=\"Not scored\",D58,(RANK(C58,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C58,C58)-1)))","v":""},{"$f":"IF(B58=\"\",\"\",IF(C58=\"Not scored\",D58,(SUMPRODUCT((C58<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B58=\"\",\"\",IF(B58=\"AVERAGE\",\"\",IF(C58=\"Not scored\",D58,(SUMPRODUCT((C58<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B58=\"\",\"\",IF(H58=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H58, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H58,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H58,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B58=\"\",\"\",IF(H58=\"AVERAGE\",\"\",IF(K57=\"\",IF(I58=I56,K56,COUNTIFS(K$5:K56,K56)+K56),IF(I58=I57,K57,COUNTIFS(K$5:K57,K57)+K57))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C58=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C58,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[53,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A59,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A59,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A59,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B59=\"\",\"\",IF(B59=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B59,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B59=\"\",\"\",IF(C59=\"Not scored\",D59,(RANK(C59,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C59,C59)-1)))","v":""},{"$f":"IF(B59=\"\",\"\",IF(C59=\"Not scored\",D59,(SUMPRODUCT((C59<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B59=\"\",\"\",IF(B59=\"AVERAGE\",\"\",IF(C59=\"Not scored\",D59,(SUMPRODUCT((C59<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B59=\"\",\"\",IF(H59=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H59, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H59,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H59,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B59=\"\",\"\",IF(H59=\"AVERAGE\",\"\",IF(K58=\"\",IF(I59=I57,K57,COUNTIFS(K$5:K57,K57)+K57),IF(I59=I58,K58,COUNTIFS(K$5:K58,K58)+K58))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C59=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C59,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
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[55,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A61,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A61,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A61,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B61=\"\",\"\",IF(B61=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B61,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B61=\"\",\"\",IF(C61=\"Not scored\",D61,(RANK(C61,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C61,C61)-1)))","v":""},{"$f":"IF(B61=\"\",\"\",IF(C61=\"Not scored\",D61,(SUMPRODUCT((C61<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B61=\"\",\"\",IF(B61=\"AVERAGE\",\"\",IF(C61=\"Not scored\",D61,(SUMPRODUCT((C61<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B61=\"\",\"\",IF(H61=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H61, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H61,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H61,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B61=\"\",\"\",IF(H61=\"AVERAGE\",\"\",IF(K60=\"\",IF(I61=I59,K59,COUNTIFS(K$5:K59,K59)+K59),IF(I61=I60,K60,COUNTIFS(K$5:K60,K60)+K60))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C61=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C61,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[56,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A62,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A62,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A62,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B62=\"\",\"\",IF(B62=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B62,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B62=\"\",\"\",IF(C62=\"Not scored\",D62,(RANK(C62,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C62,C62)-1)))","v":""},{"$f":"IF(B62=\"\",\"\",IF(C62=\"Not scored\",D62,(SUMPRODUCT((C62<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B62=\"\",\"\",IF(B62=\"AVERAGE\",\"\",IF(C62=\"Not scored\",D62,(SUMPRODUCT((C62<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B62=\"\",\"\",IF(H62=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H62, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H62,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H62,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B62=\"\",\"\",IF(H62=\"AVERAGE\",\"\",IF(K61=\"\",IF(I62=I60,K60,COUNTIFS(K$5:K60,K60)+K60),IF(I62=I61,K61,COUNTIFS(K$5:K61,K61)+K61))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C62=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C62,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[57,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A63,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A63,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A63,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B63=\"\",\"\",IF(B63=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B63,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B63=\"\",\"\",IF(C63=\"Not scored\",D63,(RANK(C63,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C63,C63)-1)))","v":""},{"$f":"IF(B63=\"\",\"\",IF(C63=\"Not scored\",D63,(SUMPRODUCT((C63<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B63=\"\",\"\",IF(B63=\"AVERAGE\",\"\",IF(C63=\"Not scored\",D63,(SUMPRODUCT((C63<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B63=\"\",\"\",IF(H63=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H63, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H63,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H63,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B63=\"\",\"\",IF(H63=\"AVERAGE\",\"\",IF(K62=\"\",IF(I63=I61,K61,COUNTIFS(K$5:K61,K61)+K61),IF(I63=I62,K62,COUNTIFS(K$5:K62,K62)+K62))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C63=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C63,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[58,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A64,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A64,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A64,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B64=\"\",\"\",IF(B64=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B64,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B64=\"\",\"\",IF(C64=\"Not scored\",D64,(RANK(C64,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C64,C64)-1)))","v":""},{"$f":"IF(B64=\"\",\"\",IF(C64=\"Not scored\",D64,(SUMPRODUCT((C64<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B64=\"\",\"\",IF(B64=\"AVERAGE\",\"\",IF(C64=\"Not scored\",D64,(SUMPRODUCT((C64<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B64=\"\",\"\",IF(H64=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H64, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H64,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H64,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B64=\"\",\"\",IF(H64=\"AVERAGE\",\"\",IF(K63=\"\",IF(I64=I62,K62,COUNTIFS(K$5:K62,K62)+K62),IF(I64=I63,K63,COUNTIFS(K$5:K63,K63)+K63))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C64=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C64,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
[59,{"$f":"IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A65,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"\",\"\",IF(INDEX(Lists_countries!$R$3:$AB$155,MATCH(A65,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))=\"AVERAGE\",IF(B$3=\"Background indicator\",\"\",\"AVERAGE\"),INDEX(Lists_countries!$R$3:$AB$155,MATCH(A65,Lists_countries!$Q$3:$Q$155,0),MATCH(A$4,Lists_countries!$R$2:$AB$2,0))))","v":""},{"$f":"IF(B65=\"\",\"\",IF(B65=\"AVERAGE\",AVERAGE(C$7:INDIRECT(C$1& ROW()-1)),IFERROR(ROUND(INDEX('SCORE TABLE'!$H$10:$BO$113, MATCH(A$3,'SCORE TABLE'!$B$10:$B$113,0), MATCH(B65,'SCORE TABLE'!$H$9:$BO$9,0)),2),\"Not scored\")))","v":""},"",{"$f":"IF(B65=\"\",\"\",IF(C65=\"Not scored\",D65,(RANK(C65,C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),0)+COUNTIF(C$7:C65,C65)-1)))","v":""},{"$f":"IF(B65=\"\",\"\",IF(C65=\"Not scored\",D65,(SUMPRODUCT((C65<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4))))))","v":""},{"$f":"IF(B65=\"\",\"\",IF(B65=\"AVERAGE\",\"\",IF(C65=\"Not scored\",D65,(SUMPRODUCT((C65<=C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1))/COUNTIF(C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4),C$7:INDIRECT(C$1&(ROW(E$7)-1)+B$4-1)))))))","v":""},"",{"$f":"IF(B65=\"\",\"\",IF(H65=\"AVERAGE\",\"\", IF(COUNTIF(H$7:H65, \"AVERAGE\") < 1, (ROUNDUP(INDEX(F$7:F$159,MATCH(H65,B$7:B$159,0)),1)), (ROUNDUP(INDEX(G$7:G$158,MATCH(H65,B$7:B$159,0)),1)))))","v":""},"",{"$f":"IF(B65=\"\",\"\",IF(H65=\"AVERAGE\",\"\",IF(K64=\"\",IF(I65=I63,K63,COUNTIFS(K$5:K63,K63)+K63),IF(I65=I64,K64,COUNTIFS(K$5:K64,K64)+K64))))","v":""},null,null,null,null,null,null,null,{"$f":"IF($A$3=\"\",\"\",\n   MATCH($A$3,'SCORE TABLE'!$B:$B,0)\n)","v":13},{"$f":"IF($C65=\"\",\"\",\n   IF($S$7=\"\",\"\",\n      _xlfn.RANK.EQ(\n         $C65,\n         INDEX('SCORE TABLE'!$H:$BO,$S$7,0),\n         0\n      )\n   )\n)","v":""}]
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