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2019 | OriginalPaper | Chapter

6. Pioneering Predictive Analytics for Decision-Making in Forced Displacement Contexts

Authors : Christopher Earney, Rebeca Moreno Jimenez

Published in: Guide to Mobile Data Analytics in Refugee Scenarios

Publisher: Springer International Publishing

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Abstract

UNHCR has been leading some of the most prominent efforts in research and operational applications of the use of nontraditional sources—including big data—in forced displacement settings. Pioneering the research on predictive analytics for population flow in emergencies, UNHCR created the Winter Cell, a cross-cutting, inter-divisional initiative established to respond to the 2015 Mediterranean refugee crisis. The project identified refugee population flow trends in the routes into Europe, using real-time data about weather conditions and its effects along the routes. Its predecessor, Project Jetson, an applied predictive analytics project, builds on this methodology by estimating the numbers of internally displaced people in Somalia and refugees in the south region of Ethiopia (Dollo Ado) with nontraditional data, including market prices and climate anomalies. This chapter describes the work of UNHCR Innovation in data science research to improve the work of UNHCR in advocacy, emergency preparedness, and operational response.

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Literature
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Metadata
Title
Pioneering Predictive Analytics for Decision-Making in Forced Displacement Contexts
Authors
Christopher Earney
Rebeca Moreno Jimenez
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-12554-7_6

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