The recent 2023 SDG Atlas, powered by the World Bank, tracks progress towards achieving the Sustainable Development Goals (SDGs), revealing concerning trends, particularly regarding SDG 2 on zero hunger. Recent data indicates a rise in food insecurity, emphasizing the need for better data coverage, standards, and transparency. To aid in tracking progress, the World Bank introduced the World Food Security Outlook (WFSO) database, utilizing machine learning to provide timely and comprehensive statistics on severe food insecurity globally.
The WFSO database offers historical, preliminary, and forecast data on severe food insecurity, enhancing transparency and aiding policymakers in developing effective strategies. It complements official data from the Food and Agriculture Organization and includes estimates for countries not covered by existing reports. The WFSO is supported by Food Systems 2030, a multi-donor Trust Fund, aimed at establishing sustainable food systems. Historical estimates from the WFSO reveal global improvements in food security conditions driven by advancements in larger countries in Latin America and Asia, while many smaller-population African countries experience deterioration. Projections suggest global food security conditions are expected to stabilize, but disparities between income groups are increasing.
Please find the original version of the article below:
https://blogs.worldbank.org/opendata/navigating-future-food-security-machine-learning
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