A Forensic Framework and DSS for Food System Resilience and Sustainability Analysis Prince Agyemang, Ebenezer Kwofie, Marie-Anne Dessureault, John M. Ulimwengu

#2023ReSAKSS #2023ATOR Present State of the African Food System Source:Welthungerhlife & World Economic Forum 20% of people in Africa face chronic hunger DR Congo 15.6 to 21.8 million Zimbabwe 3.6 to 6 million Southern Africa Burkina Faso, Niger and Mali, 3.2 to 12.7 million Source: Africa Center for Strategic Studies Central Africa Sudan 7 to 9.6 million East Africa West Africa 2019-2020 Increase in number of people facing food crises

#2023ReSAKSS #2023ATOR Key DRIVERS Shocks and Stressors affecting Africa food system (2022) ( Each year since 2015) ( Each year since 2019 ( 2008-2018 is Sub-Saharan and North Africa)

#2023ReSAKSS #2023ATOR v How do we measure these shocks and stressors? v How do we assess the resilience of food systems? v How do we assess the sustainability of food systems? Climate change Globalization & Trade Income growth and distribution Politics and Governance Food Supply Chain v Food production v Storage and distribution v Processing Food Environments v Availability v Affordability v Product properties Diets Socioeconomic factors Individual Factors v Economic v Situation v Cognitive v Is there a causal relationship between resilience and a sustainable food system?

#2023ReSAKSS #2023ATOR Casual relationship between resilience and sustainable food systems neglected? 3 No commonly agreed-upon domains for measuring the food systems’ resilience and sustainability? 2 There is a proliferation in resilience and sustainability indicators 1 Key Challenges in the food system sustainability and resilience measurement

#2023ReSAKSS #2023ATOR Methodological Framework Step 1: Resilience and sustainability framework identification Step 2: Domain and indicator identification and characterization Step 3: Forensic Framework development Step 4: Case Study application Step 5: Scenario construction (Continental and regional level) Step 6: Development of a novel Decision Support System (FS- ROAS)

#2023ReSAKSS #2023ATOR Domains and Indicators translation Household Fuzzy entropy approach Politics and Governance Food Security and nutrition Socioeconomic Environment District Regional Global Rural or Urban Indicators Domains identified from literature Step 2

#2023ReSAKSS #2023ATOR Forensic Framework vWhat happened? vWhy did it happen? vWhat will happen? vWhat is the best that could happen? KEY QUESTIONS Data-Driven Approach Step 3

#2023ReSAKSS #2023ATOR What and Why did it happen? v A weak negative correlation of between 0.19 and 0.76 is observed between cereal supply v A negative correlation in the range of 0.33 to 0.62 exists between milk supply and the selected indicators v Establish the relationship between product, supply, loss, and other relevant indicators v A strong positive correlation between the selected indicators and driving forces.

#2023ReSAKSS #2023ATOR vProduction increase by 15% by 2030. vReduce food loss by 25% vIncrease agriculture credit by 9-12% Stable Scenario 1: Increased agricultural production vIncrease food supply by ~12% and reduce loss by ~10-15%. vIncrease in support from international donors (19-20 %) vIncrease agriculture credit by 15-18% Stable Scenario 2: Increased agricultural credit What could/will happen? Step 4

#2023ReSAKSS #2023ATOR v326.1 million people become undernourished (71.5 million more than 2020 levels). v103.2 million people become obese. v167.5 million people become anemic. Snapshots of unfolding futures at the Continental level Increased Ag. Production v11.7 million fewer people are undernourished (9.4% decrease). v15.5 million more obese people than BAU v80.2% increase in the number who become anemic Increased Ag. Credit v23 million fewer people are undernourished (9.4% decrease). v7.3 million more obese people than BAU v7.5% reduction in the number who are anemic BAU BAU = business-as-usual; S1 = scenario 1; S2 = scenario 2. Step 5

#2023ReSAKSS #2023ATOR Snapshots of unfolding futures at the Continental level vRise in surface temperature to 1.44 ℃ (18% above the 2020 levels). v59.6% increase in food price index Increased Ag. Production vRise in surface temperature to 1.62℃ (25% above 2020 levels) v1.1% marginal decrease in food price inflation below the 2020 levels. BAU BAU = business-as-usual; S1 = scenario 1; S2 = scenario 2. Increased Ag. Credit vRise in surface temperature to 1.68℃ (27.8% above the 2020 levels) v~17% increase in food price inflation above the 2020 levels.

#2023ReSAKSS #2023ATOR Snapshots of unfolding futures at the sub-regional level Increased Ag. Production v7.61 million fewer people are undernourished in Central Africa(~17% below 2020 levels). v6.05 million more obese people in Southern Africa v11% increase in emissions from agrifood systems in Central and East African regions. Increased Ag. Credit v7.5 million fewer people are undernourished in Central Africa (17.5% below 2020 levels). v8.9 million more obese people in West Africa (35.8% above the 2020 levels) v11.4% increase in emissions from the agrifood in East Africa BAU = business-as-usual; S1 = scenario 1; S2 = scenario 2.

#2023ReSAKSS #2023ATOR The persistence of trade-offs (a) Increased agricultural production (b) Increased agricultural credit

#2023ReSAKSS #2023ATOR Translation of the framework into the Proposed FS-ROAS Step 6

#2023ReSAKSS #2023ATOR Key takeaways and implications for Post-Malabo Agenda Provide a tool for exploration and trade-off for different outcomes at the national and regional level The tool relies on the accuracy of the data. Positioning and making the tool useful post-Malabo Agenda The need to revise and design better strategies to collect accurate data. Potential to adapt the tool for a national level assessment

#2023ReSAKSS #2023ATOR Thank you to the team on the McGill Campus

THANK YOU