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

Abstract

This 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.