”High burden to high impact” is a country-led response – catalyzed by WHO and the RBM Partnership – to reignite the pace of progress in the global malaria fight. It calls upon countries to move away from a ‘one-size-fits-all’ approach and utlise country owned data to better guide the deployment of malaria control tools for maximum impact.
A foundational requirement for such an approach is a robust understanding of spatial and temporal variation in malaria risk in each country. Malaria case data from routine surveillance systems provides one crucial source of insight, but incompleteness and partial care seeking means they do not on their own provide a full picture. Leveraging the complimentary strengths of cross-sectional infection prevalence data and the temporal richness of routine case information from health systems, our team has built state of the art semi-mechanistic approaches that are designed to learn bespoke relationships between these two key metrics allowing for more robust risk maps that better represent community malaria risk. Our new methods are built around the underlying epidemiological processes of malaria transmission and adjust for the cascade of events from initial infection, to development of clincal malaria, and subsequent care seeking, health system access, diagnosis and treatment.
This approach yields detailed risk maps that are informed by multiple data sources, reconciling the longitudinal trends captured by surveillance data with the cross-sectional snapshots given by prevalence surveys. The outputs represent both spatial granularity in risk as well as providing detailed seasonal profiles.
All work is conducted under the leadership of National Malaria Programs and WHO-GMP. This work serves to support their decision making and guide policies and strategies.