Barbara BOUFHAL, CNRS, France
Alexandre CEBEILLAC, CNRS, France
Richard PAUL, CNRS, France
Eric DAUDÉ, CNRS, France
Dengue fever is a vector-borne disease transmitted by mosquitoes (Aedes) which affects more than 100 million people annually, mainly in intertropical urban areas. Endemic in Bangkok, it infects tens of thousands of people each year. The fight against this disease, in the absence of a vaccine, essentially involves monitoring and controlling its vector.
The environmental determinants of mosquito development are known (Daudé et al., 2015). The female needs reservoirs of stagnant water to lay eggs, vegetated spaces to feed on nectar. Its level of activity is conditioned mainly by the temperature, and the extent of its movements, motivated by the search for blood meals, depends on the population density but also on the quality of the built environment (Maneerat , Daude, 2016). The amenities available to residents of the different neighborhoods can also contribute to the establishment of breeding sites (access to water, collection of household waste) and therefore to the development of mosquitoes. The urban environment presents a great heterogeneity of these factors and implies a permanent presence of vector control operators. To optimize and guide monitoring teams in the field, automated mapping methods with high spatial resolution of environmental risk are expected (WHO, 2017).
In this context, we present an extension of MODE (Misslin, Daudé, 2017), a spatial and temporal data processing chain that makes it possible to produce a synthetic indicator of environmental risk at high spatial resolution. Data of different kinds, combining remote sensing, GIS and census are used. Temperature and precipitation data are obtained by remote sensing (MODIS) and/or extrapolated from ground weather stations. Fine-scale building and vegetation information is extracted from high-resolution satellite images collected at ESRI. Finally, the socio-economic characteristics of the different neighborhoods come from the census. The synthetic indicators are then compared with entomological data.
Mots clés : vulnerability|mosquito|urban risk|indicator|Bangkok
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