Abstract
Background: Rift Valley fever (RVF) is a zoonotic arboviral disease that causes significant livestock and human health impacts across Africa, with outbreaks often linked to climatic anomalies. The Sahel region is particularly vulnerable due to its reliance on pastoralism and limited adaptive capacity. Understanding how climate change may alter RVF outbreak risk is critical for early warning and preparedness.Methods: We developed a spatially explicit risk model integrating historical RVF outbreak data (1998–2022), satellite-derived environmental variables (rainfall, temperature, vegetation indices), and future climate projections under Representative Concentration Pathways (RCPs) 4.5 and 8.5 for the 2050s and 2080s. Logistic regression and random forest models were used to identify key climatic drivers and map current and future risk across six Sahelian countries.Results: Rainfall anomalies and vegetation greenness were the strongest predictors of outbreaks. Under RCP 8.5, the area at high risk for RVF is projected to expand by 34% by 2080, with increased risk in northern latitudes where transmission was historically limited. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.89 during validation.Conclusions: Climate change is likely to increase RVF outbreak risk in the Sahel, particularly in regions undergoing ecological transition. These findings underscore the need for climate-adaptive surveillance and vaccination strategies tailored to changing risk landscapes.