A climate-based malaria transmission model with seasonal optimal control and cost-effective analysis

Malaria transmission is strongly influenced by the seasonal dynamics of mosquito populations. However, existing climate-based malaria models do not include humidity or seasonal optimal control to guide timely interventions. We present a climate-based, non-autonomous malaria transmission model that incorporates temperature, rainfall, and humidity-dependent parameters. Analysis of the autonomous version exhibits a backward bifurcation, implying that reducing R0 below unity does not guarantee malaria elimination. In the non-autonomous framework, we establish that the disease-free equilibrium is globally attractive for R0(t)<1, while R0(t)>1 guarantees at least one positive periodic sustained transmission. The model is fitted using real climate and epidemiological data from Kolkata, India. We propose a season-based optimal control model and analyze seven intervention strategies combining bed nets, treatment, and insecticide spraying. The single-control strategy with bed nets is the least expensive, but the combined strategy reduces infections by 96.98%. The findings emphasize the importance of synchronizing intervention intensity with seasonal and climatic variations, offering a quantitative framework to inform region-specific malaria control policies and efficient resource allocation.