Catholic Relief Services leverages machine learning to fight hunger

Data collection and machine learning help CRS predict which households will face food scarcity within the next few months, allowing it to respond faster and more efficiently.

Catholic Relief Services leverages machine learning to fight hunger
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Catholic Relief Services (CRS) has a mission to provide humanitarian relief to people in the developing world. Since 2016, it has been using data collection and machine learning to help guide those efforts.

CRS, established by the U.S. Conference of Catholic Bishops in 1943 to aid World War II refugees in Europe, is an international humanitarian agency in the U.S. and a member of the Caritas International network of Catholic humanitarian agencies.

CRS began developing the Measurement Indicators for Resilience Analysis (MIRA), a protocol for monitoring and evaluating the resilience of disaster-stricken communities, in Malawi. Malawi, a land-locked country in southeastern Africa, is particularly vulnerable to weather-related shocks. Eighty-four percent of its population lives in rural areas and relies on subsistence agriculture.

"MIRA is used to predict hunger and study household recovery trajectories in Malawi. The increased severity of natural disasters exacerbates food insecurity," says James Campbell, regional technical director for monitoring, evaluation, accountability, and learning at CRS.

Severe flooding displaced hundreds of thousands of people in southern Malawi in 2015. The flooding was followed by a severe drought, which in turn led to crop destruction by a crop pest called fall armyworm.

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