Integrated Disease Surveillance to Reduce Data Fragmentation – An Application to Malaria Control

Abstract

Objective Driven by the need to bring malaria surveillance data from different sources together to support evidence-based decision making, we are conducting the “Scalable Data Integration for Disease Surveillance” (SDIDS) project. This project aims to foster the integration of existing surveillance data to support evidence-based decision-making in malaria… (More)

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