The control of arthropod disease vectors using chemical insecticides is vital in combating malaria, however the increasing insecticide resistance (IR) poses a challenge. Furthermore, climate variability affects mosquito population dynamics and subsequently IR propagation. We present a mathematical model to decipher the relationship between IR in Anopheles gambiae populations and climate variability. By adapting the susceptible-infected-resistant (SIR) framework and integrating temperature and rainfall data, our model examines the connection between mosquito dynamics, IR, and climate. Model validation using field data achieved 92% accuracy, and the sensitivity of model parameters on the transmission potential of IR was elucidated (e.g. μPRCC = 0.85958, p-value < 0.001). In this study, the integration of high-resolution covariates with the SIR model had a significant impact on the spatial and temporal variation of IR among mosquito populations across Africa. Importantly, we demonstrated a clear association between climatic variability and increased IR (width = [0-3.78], α = 0.05). Regions with high IR variability, such as western Africa, also had high malaria incidences thereby corroborating the World Health Organization Malaria Report 2021. More importantly, this study seeks to bolster global malaria combat strategies by highlighting potential IR 'hotspots' for targeted intervention by National malria control programmes.
Keywords: Decision making; Insecticide resistant malaria vector; Spatial modelling; Susceptible-infected-resistant.
© 2024. The Author(s).