%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Cottrell, Gilles
%A Kouwaye, Bienvenue
%A Pierrat, Charlotte
%A Le Port, Agnès
%A Bouraima, A.
%A Fonton, N.
%A Hounkonnou, M. N.
%A Massougbodji, A.
%A Corbel, Vincent
%A Garcia, André
%T Modeling the influence of local environmental factors on malaria transmission in Benin and its implications for cohort study
%D 2012
%L fdi:010055688
%G ENG
%J Plos One
%@ 1932-6203
%K BENIN
%M ISI:000301070200012
%N 1
%P e28812
%R 10.1371/journal.pone.0028812
%U https://www.documentation.ird.fr/hor/fdi:010055688
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers17-09/010055688.pdf
%V 7
%W Horizon (IRD)
%X Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission-even at a very local scale-is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors. As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages. This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.
%$ 052