Correction de l’effet du biais d’échantillonnage dans la modélisation de la qualité des habitats écologiques : application au principal vecteur du paludisme en Guyane française

Abstract : Species distribution models are identified as relevant to map and characterize the habitat quality of Anopheles genusmosquitoes, transmitting malaria, and thus to both participate in the estimation of the transmission risk of this disease and inthe definition of targeted vector control actions. The malaria transmission depends on the presence and distribution of thevectors, which are themselves dependent on the environmental conditions that define the quality of the ecological habitats of the Anopheles. However, in some areas, Anopheles collection data remain scarce, making it difficult to model these habitats. In addition, the collection of these data is very often subjected to significant sampling biases, due, in particular, to unequal accessibility to the entire study area. This thesis provides a solution to the mapping of malaria vectors, considering two very few studied aspects in modeling: the low number of available presence sites and the existence of a sampling bias. An original method for correcting the effect of the sampling bias is proposed and then applied to presence data of Anopheles darlingi species - the main vector of malaria in South America - in French Guiana. Then, a distribution model of An. darlingi was built to obtain a map of habitat quality consistent with entomologists’ knowledge and providing high prediction performances. The proposed correction method was then compared to existing methods in an application context characterized by the scarcity of the species occurence data and the presence of a sampling bias. The results show that the developed method is adapted to cases where the number of sites of presence is low. This thesis contributes, on the one hand, to fill theoretical and applicability lacuna of current methods intended to correct the effect of the sampling bias and, on the other hand, to supplement the knowledge on both the spatial distribution and the bio-ecology of the main malaria vector in French Guiana.
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Yi Moua. Correction de l’effet du biais d’échantillonnage dans la modélisation de la qualité des habitats écologiques : application au principal vecteur du paludisme en Guyane française. Maladies infectieuses. Université de Guyane, 2017. Français. ⟨NNT : 2017YANE0002⟩. ⟨tel-01547595⟩

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