Undernutrition is responsible for nearly half of all deaths of children under five years of age. In the developing world, where many communities rely on subsistence farming, one way of combating undernutrition is through food aid provided by governmental and non-governmental organizations. In this analysis we develop a flexible optimization based approach to support food aid planning capable of incorporating a variety of inputs to capture micro-scale food demand. We apply this optimization model to the specific case of Mali, one of the poorest countries in the world, with large food aid programs. The results are compared to the current distribution of food aid outlets as presented by the World Food Program and suggest that an optimization based framework provides quantitative-based insights of demand and resource allocation useful for planning efforts. In particular, the results indicate that a reallocation of existing food aid outlets towards more dense areas where vegetation is reduced could markedly increase access to outlets by those with food needs. The developed approach has potential to support ongoing efforts to reduce food insecurity and improve the cost-effective targeting of food aid in Mali and elsewhere.
Bibliographical noteFunding Information:
This study was partially funded by NASA grant #NNX13AC67G The first author is an affiliated researcher with FEWS NET and has received funding from FEWS NET, USGS and USAID, as well as NASA.
© 2017, Springer Science+Business Media B.V. and International Society for Plant Pathology.
Copyright 2017 Elsevier B.V., All rights reserved.
- Applied remote sensing
- Food aid
- Food insecurity
- Spatial optimization