Evidence-based decision making for malaria elimination applying the Freedom From Infection statistical framework in five malaria eliminating countries: an observational study

Abstract

Routine surveillance is a pillar of malaria programmes, and the primary source of data used for decision making. However, any inference when relying on routine data to inform decision making is limited by how effective the system is at measuring the actual malaria burden. Here, we aimed to extend the Freedom From Infection (FFI) framework to produce species-specific estimates of surveillance system sensitivity and probability of freedom from malaria, combine multiple surveillance components including community case management and active case detection, and apply the FFI model in five malaria eliminating settings.