International audience INTRODUCTIONIf taken independently from each other, entomological variables and human socio-economic characteristics have clarified the risk of malaria infection in urban area with its uneven spatial distribution, their common explanatory share remains to investigate. Indeed, there is often a lack of simultaneous consideration of the factors responsible for the transmission of parasites. This work, result of collaboration between two teams each specialized in one of the dimension; examines interactions between the entomological profile of urban under-spaces and their socio-economical characterization.DATA AND METHODAt the aggregated scale, precise and localized data have been extrapolated in order to give a model of the number of anopheles bites by person and by night (the Entomological Inoculated Rate) in Dakar’s urban area (Machault et al.,2012). They have been compared to the 2002 census data which has enabled to construct an index of social vulnerability (Borderon,2013). These two indicators of malaria infection exposition have been confronted by the BiLISA method (Anselin, 1995). These results are completed by the assessment of the co-localization existing between entomological profile of census districts and their social vulnerability profile.DISCUSSIONHigh co-localization between the evaluated EIR and the socio-economical profile of the inhabitant is unlighted. Likewise, at the superior scale, an average EIR can be explained for a large part (43%) by an average social profile of nearby census districts. The spatial coherence which exists between profiles leads to several interpretations. The notion of “poverty traps” for example can be a good summary of the places of accumulation of vulnerabilities, where people with “limited capabilities” live in some areas which border high EIR (Borderon et al., 2013). Restricted to areas where landscapes are "pathogens", people may have no choice or no control of their environment. In contrast, the city dwellers with a low vulnerability reside mainly in the center of the peninsula and are farther from Anopheles bites.APPLICATIONTherefore, in the current context of pre-elimination of malaria in Senegal, these results are fundamental. If malaria in urban areas is quite low (in 2008, for example, with a minimal prevalence rate of 2%) (Diallo et al., 2012), it is nonetheless very unevenly distributed in space where some poverty traps concentrate the meeting places between the three hosts of malaria pathogen complex. Thus, taking the logic of "target programs” of the protocol of Hyogo, it is interesting to accurately locate these areas, high circulation locations of the parasite.REFERENCESAnselin L. (1995) "Local indicators of spatial association – LISA". Geographical Analysis, 27, 93-115.Borderon M. (2013) “Why here and not there? Developing a spatial risk model for malaria in Dakar, Senegal” in SOURCE, ‘Studies Of the University: Research, Counsel, Education’, Publication Series of the United Nations University Institute for Environment and Human Security (UNU-EHS), No. 17/2012.Borderon M. Oliveau S. (2013) « Le territoire comme support de populations vulnérables et acteur des vulnérabilités individuelles », XVIe Colloque National de Démographie – Les populations vulnérables, CUDEP, Aix-en-Provence du 28 au 31 MAI 2013, 19p. Diallo A. and al. (2012) “Asymptomatic Carriage of Plasmodium in Urban Dakar: The Risk of Malaria Should Not Be Underestimated”, PLoS ONE 7(2): e31100. doi:10.1371/journal.pone.0031100.Machault V. and al. (2012)”Risk Mapping of Anopheles gambiae s.l. Densities Using Remotely-Sensed Environmental and Meteorological Data in an Urban Area: Dakar, Senegal”. PLoS ONE 7(11): e50674. doi:10.1371/journal.pone.0050674.