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Framework to Guide the Use of Mathematical Modelling in Evidence-based Policy Decision-making

dc.contributor.authorOliwa J.
dc.contributor.authorGuleid F. H.
dc.contributor.authorOwek C. J.
dc.contributor.authorMaluni J.
dc.contributor.authorJepkosgei J.
dc.contributor.authorNzinga J.
dc.contributor.authorWere V. O.
dc.contributor.authorSim S. Y.
dc.contributor.authorWalekhwa A. W.
dc.contributor.authorClapham H.
dc.contributor.authorDabak S.
dc.contributor.authorKc S.
dc.contributor.authorHadley L.
dc.contributor.authorUndurraga E.
dc.contributor.authorHagedorn B. L.
dc.contributor.author& Hutubessy R. C
dc.date.accessioned2025-07-24T07:23:19Z
dc.date.available2025-07-24T07:23:19Z
dc.date.issued2025
dc.identifier.urihttps://doi.org/10.1136/bmjopen-2024-093645
dc.identifier.urihttp://knowhub.aphrc.org/handle/123456789/2411
dc.description.abstractThis study develops a comprehensive framework to guide the use of mathematical modeling in evidence-based policy decision-making, especially in low- and middle-income countries (LMICs). Drawing from COVID-19 pandemic experiences, it emphasizes the integration of modellers and policymakers, identifies enablers like funding and data infrastructure, and presents a policy roadmap to build sustainable modeling capacity. Targeted at both modellers and decision-makers, the framework is disease-agnostic and aims to embed modeling within routine public health practice.
dc.publisherBMJ (British Medical Journal)
dc.subjectMathematical Modeling II Evidence-Informed Policy II Capacity Building II Knowledge Translation II Public Health Modeling II LMICs
dc.titleFramework to Guide the Use of Mathematical Modelling in Evidence-based Policy Decision-making


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