Strengthening health and disease modelling for public health decision making
In plain English
AI plain-English summaryAround 40 African countries plan to roll out malaria vaccines, but no one knows the best way to combine them with existing chemoprevention drugs to maximise impact and value for money. This matters because malaria remains a leading killer of young children in Africa, and the global target of a 90% reduction in cases by 2030 demands that limited resources—vaccines and drugs—be deployed as effectively as possible. Currently, decision-makers lack the evidence to choose between seasonal, perennial, or post-discharge chemoprevention strategies alongside vaccination, or to predict how different uptake levels affect cost-effectiveness. The consortium—three East African institutions and two European partners—will build mathematical and economic models that simulate these combinations at sub-national levels in high-burden countries. If successful, the research will give national malaria programmes and international agencies a practical tool to tailor intervention packages to local conditions, avoiding wasteful redundancy and maximising lives saved. It will also strengthen local modelling capacity, so African decision-makers can run their own analyses rather than relying on external experts. The work is applied, not fundamental science: its direct purpose is to inform real-world public health policy.
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