High resolution physically based modelling reveals malaria incidence reduction by vector control measures

Abstract

Abstract Malaria continues to cause over 600,000 deaths annually in sub-Saharan Africa, disproportionately affecting children under five. Despite sustained control efforts, transmission remains highly sensitive to local environmental and climatic variability, underscoring the need for physically grounded models capable of capturing these dynamics. To address this challenge, we developed a high-resolution hybrid modeling framework linking WRF/WRF-Hydro and VECTRI. The framework integrates atmospheric, hydrological, ecological, and intervention processes at 1 km and 50 m resolutions and includes a new compartment for insecticide-treated net (ITN) coverage. Using data from 2007–2022 in western Kenya, a period of large-scale ITN deployment, the model reproduced observed malaria trends with a mean monthly deviation of ±100–150 cases. Simulations showed that ITN coverage reduced the entomological inoculation rate and malaria incidence by 58% and 41%, respectively, with the highest efficacy under warm ( $$\approx 29^\circ$$ C) and moderately wet (150–250 mm) conditions. The findings suggest that integrating environmental process modeling with optimized, targeted control strategies provides a cost-effective and operationally relevant framework for sustainable malaria management under changing climatic conditions.