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Strengthening health and disease modelling for public health decision making

In plain English

AI plain-English summary

Malaria 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.

View original technical description
Malaria is a major cause of ill health and death in children, particularly in Africa. Chemoprevention and vaccination are thus highly recommended to protect young children from malaria infection in endemic countries. About 40 countries in Africa have shown interest in rolling out malaria vaccines with the ambition of reaching the global target of reducing malaria cases by 90% by 2030. We will model different combinations of seasonal, perennial, and post- discharge malaria chemoprevention strategies and vaccination to understand how they complement or create redundancies in terms of impact, and cost- effectiveness at different vaccine uptake levels. Our aims are i) to generate scientific evidence for optimal deployment of existing and novel malaria interventions at sub-national levels in high-burden high-impact countries, and ii) to strengthen modeling capacity and the use of modeling by decision-makers in Africa. Our consortium consists of three institutions in East Africa, and two in Europe, which will collaborate with other modeling units, national malaria and vaccination programs, and international agencies supporting malaria control programs. Our team is multidisciplinary with experienced mathematical and economic modelers, social scientists, epidemiologists, and policymakers. Keywords: malaria, vaccine, chemoprevention, cost-effectiveness, modeling

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Researchers

Amani Mori (EPMC Awardee)Andrew Mhale Yona Kitua (EPMC Awardee)Esther Ngadaya (EPMC Awardee)Jesse Gitaka (EPMC Awardee)Thumbi Mwangi (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Optimising seasonal malaria chemoprevention and seasonal vaccination in childhood to address the resurgent malaria burden in Africa
Modelling for Decisions in a Dynamic Africa
Maximising the impact of chemoprevention on the malaria burden in children in areas of seasonal transmission
Developing model applications to support national malaria elimination strategies
Modelling the Public Health Impact of Second Generation Malaria Vaccines

Original classification

Strengthening health and disease modelling for public health decision making

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