On the road to recovery from COVID-19, many countries lack reliable and up-to-date information about economic conditions on the ground and have no way of collecting it during a pandemic. Traditional aid modalities relying on in-person enrollment and delivery are no longer safe or scalable, with governments and non-governmental organisations lacking personnel and relief taking weeks to arrive.
GiveDirectly and the Center for Effective Global Action at University of California Berkeley are addressing this challenge by developing and testing a new model for humanitarian support that enables cash transfers to be deployed effectively, accurately, and at scale to those people in Togo who need them most. In the country in West Africa over 50% of the population lives in poverty.
The project incorporates new data and computational technologies to identify people and places in economic distress and integrating data from mobile phones, satellite imagery, and traditional surveys.
Thanks to the use of data science, the innovative social assistance programme can help the government prioritise the families with the greatest needs and take important steps towards eradicating poverty (SDG 1 – No Poverty).
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- The story was first published on the data.org blog
