A Climate‐Driven Spatial Ecoepidemiological Model of Malaria Transmission
Herieth RwezauraBackground
Malaria transmission is strongly influenced by environmental conditions that regulate mosquito biting, survival, development, and breeding habitat suitability. Temperature, rainfall, vegetation, and altitude interact nonlinearly to determine where and when transmission can be sustained, whereas developmental delays and mosquito dispersal can further shape temporal and spatial dynamics.
Objective
This study develops a climate‐driven spatial malaria transmission model to investigate how environmental variability, temperature‐dependent mosquito development, and vector dispersal jointly influence malaria persistence, recurrent outbreaks, and spatial spread across heterogeneous landscapes.
Methods
The model couples human infection dynamics with mosquito life cycle processes and incorporates temperature‐ and altitude‐dependent biting, rainfall‐driven habitat suitability, vegetation effects, temperature‐dependent developmental delays, and mosquito dispersal through diffusion. Analytical results characterize the transmission threshold and stability of endemic equilibria, whereas numerical simulations examine climate‐dependent transmission, delay‐induced oscillations, traveling waves, and spatial hotspots.
Findings
The simulated mosquito biting rate peaks at approximately 25°C and declines with increasing altitude, whereas habitat suitability is maximized at approximately 100 mm/month of rainfall. The climate‐dependent basic reproduction number, R 0 ( T , R , V ), identifies a transmission window of approximately 22°C–32°C and 60–160 mm/month under the parameterization considered. Along an altitudinal transect, low‐elevation regions remain above the R 0 = 1 threshold throughout the simulated seasonal cycle, whereas higher elevation regions cross the threshold during warmer and wetter periods. Temperature‐dependent developmental delays generate increasingly pronounced oscillations as the delay increases; sustained epidemic cycles emerge for delays of 30–40 days, with a numerically estimated critical delay of approximately 22–25 days. Spatial simulations show that increasing mosquito diffusion from D v = 0.02 to 0.10 km 2 /day accelerates the propagation of infection fronts, whereas heterogeneous environmental suitability produces persistent spatial hotspots rather than diffusion‐driven pattern formation.
Future Directions
Future research should incorporate finer scale hydrological and vegetation dynamics, remote‐sensing observations, stochastic environmental variability, and human mobility to improve local calibration and predictive performance. These extensions could support more detailed assessment of climate‐sensitive shifts in malaria transmission zones and the development of climate‐informed early warning and control strategies.