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A Spatiotemporal Recommendation Engine for Malaria Control

Brian Reich of North Carolina State University in the U.S. will develop a software model to measure the risk of local malaria outbreaks in real-time in the Democratic Republic of Congo and identify treatment strategies for control efforts to more effectively allocate their limited resources. They will build this "recommendation engine" using demographic health survey data from household surveys on disease incidence and types of treatment used, and devise a simple mathematical formula that calculates priority scores, defined by user-specified risk factors, for different regions, which can be easily interpreted by stakeholders.

More information about Design New Analytics Approaches for Malaria Elimination (Round 17)