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Caractérisation des zones et périodes à risque de la Fièvre de la Vallée du Rift au Sénégal par télédétection et modélisation éco-épidémiologique

Abstract : The Rift Valley fever (RVF) is an arboviral zoonosis, first identified in Kenya in 1930, which has spread over many African countries. The RVF virus (RVFV) is a mosquito-borne virus member of the family Bunyaviridae, genus Phlebovirus. Statistical models that are used for predicting RVF outbreaks in East Africa do not work in West Africa where the factors and processes involved are still not well described. The aim of this thesis is to identify the factors and epidemiological processes that explain the emergence of RFV outbreaks in Senegal. To achieve that, we have chosen an eco-epidemiological approach targeted on the main candidate mosquito vectors of the RFV virus. By using the environmental and climatic variables and by their exploitation in mathematical models, we tried to answer two major epidemiological questions: (1) where are the potential zones at risk? And, (2) when are the periods favourable to RFV outbreaks?The study has been carried out at a local scale, in an area of about 10 km2 centred on the village of Barkedji in the pastoral Ferlo region in northern Senegal.When identifying risk areas for virus transmission, we used remote sensing and landscape analysis to characterize favourable environments fot the two main candidate vectors, Aedes vexans and Culex poicilipes (Diptera: Culicidae). For predicting risk of RVF outbreaks, we developed a mosquito population model for the two vector species taking into account the dynamics of the ponds as breeding sites. The results of the simulation have been validated with captured mosquito field data. This required the prior development of a temporary pond dynamics model that was calibrated and validated with field and remote sensing data.The results of the landscape analysis confirmed that favourable environments for the mosquito vectors of the RVF could be characterised by remote sensing. The importance of the ponds and the surrounding vegetation density was also highlighted, allowing to map the spatial heterogeneity of RVF circulation risk. The results of the mosquito model simulations showed that years of active virus circulation matched the years when both vector species were densely present. Indeed, the simulations showed high mosquito densities in 1987 and 2003, which correspond to the most important epidemic and epizootic events in that region.
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Valérie Soti. Caractérisation des zones et périodes à risque de la Fièvre de la Vallée du Rift au Sénégal par télédétection et modélisation éco-épidémiologique. Médecine humaine et pathologie. AgroParisTech, 2011. Français. ⟨NNT : 2011AGPT0022⟩. ⟨pastel-00727693⟩

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