A Review of Malaria Transmission Models: Integrating Diabetes Comorbidity and Climate Change

Abstract

Malaria and type 2 diabetes represent two grow- ing global health challenges that are increasingly intersecting in tropical and subtropical regions. Climate change further complicates this scenario by expanding mosquito habitats and worsening metabolic complications in diabetic individuals. Re- search shows that diabetic patients face 46 percent higher malaria infection risk and significantly elevated mortality rates compared to non-diabetic individuals. This review examines the evolution of mathematical models for malaria transmission over the past century, from the foundational Ross model (1911) to contemporary frameworks incorporating climate forcing and host heterogeneity. We trace how successive generations of models have added biological realism through
compartmental structures, age-dependent immunity, vector population dynamics, and environmental factors. Despite substantial progress, current models largely assume uniform host susceptibility and recovery rates, overlooking the profound impact of metabolic disorders on infection dynamics. We identify critical research gaps and emphasise the urgent need for integrated modelling approaches that explicitly account for differential transmission probabilities and recovery rates in diabetic versus non-diabetic populations under climate change scenarios. Such models are essential for protecting vulnerable communities facing the converging threats of infectious and chronic diseases in a warming world.