Mathematical Modeling of Rift Valley Fever in the Sahelian Zone

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Abstract We develop a mathematical model of Rift Valley Fever integrating mosquito vectors, ruminants, and humans, based on an SEIR -type structure with vertical transmission in vectors. Local data from the Sudanian and especially the Sahelian zones are used to capture the impact of climatic variations on mosquito population dynamics. The mathematical analysis establishes the model’s positivity, determines the basic reproduction number R 0 , and demonstrates the local and global stability of the disease-free equilibrium. Sensitivity analysis (PRCC) highlights the most influential parameters, while the stochastic approach using a continuous-time Markov chain confirms the major role of seasonal rainfall. Numerical simulations reveal a peak in animal and human infections around the 9 th month, correlating with periods of heavy rainfall. This model provides a relevant tool for surveillance and prevention within a “One Health” approach in Chad.

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