Grand Challenges: Forecasting Acute Malnutrition for Anticipatory Action
As of 2020, over 45 million children under 5 years of age were affected worldwide by acute malnutrition – the most life-threatening form of undernutrition in early childhood. This urgent problem is exacerbated by a rising number and complexity of humanitarian emergencies. Extraordinary public health, climate change, political instability, and supply chain issues have intersected to undermine food security broadly and cause unprecedented simultaneous famine- like conditions in several countries. Existing analysis of acute malnutrition risks is inadequate for stakeholders to anticipate situations of concern, take action, and implement measures before the onset of food and nutrition crises.
The project aims to advance statistical models using methods of predictive analytics, to develop tools that facilitate interactive engagement with model-based forecasts, and to test their deployment in decision-making processes of multilateral agencies. The models are expected to provide a rigorous, reliable means to foresee where and when crises are most likely to occur, and at what scale of severity, in the process illuminating leading indicators, driving factors, and fruitful paths of intervention. The applied research will study whether and how forecasting can affect management of crises, including the potential to strengthen capacities for gauging and responding to risks, to facilitate strategizing about crisis preparedness and early action programming, to support coordination mechanisms in setting priorities that achieve efficiencies, and to optimize resources invested in humanitarian responses. The project is being undertaken in partnership with UNICEF and the World Food Program and feeds into the Nutrition Vulnerabilities Assessment in Crisis (NuVAC) initiative, an emergent collaboration that aspires to fulfill the global sustainable development goal of ending hunger through improved food security and nutrition.