[1] We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semiarid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations that lead to variations in malaria transmission. Using a highresolution, small-scale distributed hydrology model that incorporates remotely sensed data for land cover and topography, we simulate the formation and persistence of the pools constituting the primary breeding habitat of Anopheles gambiae s.l. mosquitoes, the principal regional malaria vector mosquitoes. An agent-based mosquito population model is coupled to the distributed hydrology model, with aquatic-stage and adult-stage components. Through a dependence of aquatic-stage mosquito development and adult emergence on pool persistence, we model small-scale hydrology as a dominant control of mosquito abundance. For each individual adult mosquito, the model tracks attributes relevant to population dynamics and malaria transmission, which are updated as mosquitoes interact with their environment, humans, and animals.
Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the withinseason temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns can also affect mosquito population dynamics in water-limited environments. Here, using a numerical simulation, I show that intraseasonal rainfall pattern accounts for 39% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal. I apply a field validated coupled hydrology and entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling using topography to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in simulated mosquito abundance from a mechanistic model, and time-integrated surface area of pools persisting longer than 7 days explains 82% of the variance. Correlations using the hydrology model output explain more variance in mosquito abundance than the 60% from rainfall totals. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.
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