Strengthening health and disease modelling for public health decision making
In plain English
AI plain-English summaryMalaria kills a child every minute in Africa, and this project will use computer models to work out how best to combine vaccines with preventive drugs to stop those deaths. The problem is that countries now have several powerful tools against malaria—seasonal, perennial, and post-discharge chemoprevention, plus vaccines—but no clear evidence on how to use them together. Giving children both a vaccine and a drug might save more lives, or it might waste resources if the effects overlap. With around 40 African countries planning to roll out malaria vaccines, and a global target to cut cases by 90% by 2030, decision-makers need to know which combinations work best and where. The consortium, which includes modelling teams in East Africa and Europe, will simulate different intervention mixes at sub-national levels in high-burden countries. If successful, the research will produce cost-effectiveness data that national malaria programmes can use immediately to allocate limited budgets. It will also strengthen local modelling capacity, so African policymakers can run their own analyses rather than relying on outside experts. The result could be more children protected for every pound spent, and a faster path toward eliminating malaria as a major cause of childhood death.
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