Multi-scale environmental analysis and prediction for insects vector of disease : application to malaria vectors of Southeast Asia

(eng) Malaria is a major vector-borne disease worldwide. Southeast Asia presents a high diversity of anopheles with major and potential malaria vectors. Each species has its own habitat and environment might influence vector status. Entomological dataset in the region include research data, literature records and monitoring data. The thesis investigated the optimal use of various types of entomological and environmental data for characterization of environmental influences and mapping of species distribution. Through the use of methods adapted to each type of dataset, the information is integrated in a multi-scale framework of analysis and a multi-scale GIS to optimize data analysis and improve accessibility to information for malaria control staff. Geo-referenced occurrence sites from the literature map known distribution for the Dirus complex and identify key environmental drivers. The species is then predicted on its entire range. Suitable areas are defined according to abiotic factors such as meteorology then further refined using fast changing biotic factors such as vegetation cover. This work produced a map for the species at continental level and laid down the basis for refining the distribution at finer scale. Identification of species association based on indirect clustering and canonical multivariate analysis defines four groups linked to particular habitats. Protocols and suggestions for further research are discussed.