With its partners, the Shamba Centre for Food & Climate, the JUNO Evidence Alliance and the Food and Agriculture Organization of the United Nations (FAO), Hesat2030 is developing a comprehensive assessment and economic modelling of nutrition-sensitive interventions to determine the additional public investment needed to achieve food and nutrition security in the most vulnerable populations by 2030, and within the limits set by the Paris climate agreement.
The assessment consists of an evidence-synthesis of nutrition-sensitive interventions that interface with the agrifood systems, followed by economic modelling for the interventions selected based on the review’s findings, using the MIRAGRODEP model.
The evidence-synthesis combines manual search and artificial intelligence to screen relevant bibliographic and organization databases to ensure the inclusion of key scientific articles and grey literature reports from 2008 to 2024.
The Hesat2030 assessment aims to:
Provide a comprehensive analysis and costing of the most effective nutrition sensitive interventions in agrifood systems that improve diets and nutrition.
Advance the understanding of the linkages between multiple nutrition sensitive interventions in order to maximise impact.
Formulate evidence-based recommendations on climate-smart actions that achieve healthy diets and improve nutrition sustainably, without breaching the 1.5 °C threshold.
Facilitate consensus among practitioners of nutrition and foods systems policies on a shortlist of essential actions to take.
These recommendations will help inform policy makers and the donor community on how to prioritize their investments for maximum impact. This is especially timely given that many countries deliberating on their commitments for the upcoming Nutrition for Growth summit in March 2025. It also complements similar work underway such as the World Bank’s forthcoming update for their Investment Framework for Nutrition which focuses on nutrition specific and sensitive interventions in relation to health targets.
Read the full concept note:
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