نبذة مختصرة : Rift valley fever (RVF) is an emerging zoonotic arbovirose, mainly affecting man and ruminants. Predicting high risk areas is an important stake of this disease's control, as neither specific treatments nor efficient prevention programs exist. In the agropastoral sahelian area of Senegal, the rainy season is the high-risk period, when hosts and vectors gather around temporary flooded ponds. Virus transmission mechanisms are complex, since they imply at least two different vector species with particular ecologies (Aedes vexans and Culex poicilipes), and sedentary or transhumant hosts. The Barkedji district is an enzootic area. In order to assess the risk level, defined as host-vector contact intensity during the rainy season, we set up a model predicting livestock herds spatial distribution, from satellite and field data. Then temporary ponds, the vectors' biotope, were detected on a series of SPOT5 images and used to assess relative vector abundance. Those data were then assembled in a model, allotting to each pixel of the study zone a relative risk level, accounting to herds density, vector abundance and vegetation cover. Our results are encouraging, although the model has to be improved and validated. The main interest of our study is to present a specific methodological approach, applied to health-environment matters and based on the study of the interactions between the epidemiological cycle elements and the environment. We also hope that, in a close future, it will become helpful to the senegalese RVF monitoring network. ; La fièvre de la vallée du Rift (FVR) est une arbovirose zoonotique émergente, touchant principalement l'homme et les ruminants. En l'absence de traitement spécifique et de moyen de prévention efficace, la prédiction des lieux à risque est un enjeu important de la lutte contre cette maladie. En milieu agropastoral sahélien du Sénégal, la période à risque est la saison des pluies, lorsque hôtes et vecteurs se rencontrent autour de mares temporairement inondées. La transmission du virus est ...
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