Numerical Simulation of Climate-Driven Malaria Transmission Dynamics Using a Vector–Host Model

Climate variability continues to influence the spatial and temporal dynamics of infectious diseases, particularly in tropical and subtropical regions. This study presents a mathematical framework for analysing climate-driven malaria transmission using a coupled vector–host model. The human population is divided into susceptible, infected, and recovered compartments, while the mosquito population is classified into susceptible and infected classes. Climate forcing is incorporated through temperature- and rainfall-dependent transmission parameters, allowing the model to capture seasonal and environmental effects on disease spread. The governing nonlinear differential equations are non-dimensionalised, and the basic reproduction number is derived to determine threshold conditions for disease persistence. Numerical simulations are performed using a forward Euler scheme to examine the impact of climate variability on infection dynamics. The results were simulated using MATLAB software. The results demonstrate that increased temperature and rainfall significantly amplify transmission intensity and outbreak magnitude. The model highlights the critical role of climatic factors in shaping malaria dynamics and provides a quantitative framework for evaluating climate-sensitive intervention strategies.