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Volume 603 Issue 7903, 31 March 2022

Telephone connections

The cover shows Yournina Akinyi using her mobile phone at her produce stand in Matasia village, Kenya. In this week’s issue, Joshua Blumenstock and his colleagues show how big data derived from mobile phone networks can improve the targeting of humanitarian aid. Rapid identification of those in greatest need is a significant challenge during a crisis. Blumenstock and his team used conventional survey data to train machine-learning algorithms to recognize patterns of poverty in mobile phone data. Their method was then used in Togo to distribute millions of dollars in COVID-19 relief. The researchers found that compared with more conventional targeting methods, their machine-learning approach reduced the proportion of individuals in need who missed out on aid by 4–21%, suggesting that data sources such as phones could enhance aid distribution in times of crisis.

Cover image: GiveDirectly

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