  Malaria remains endemic in tropical areas, especially in Africa. For the
evaluation of new tools and to further ourunderstanding of host-parasite
interactions, knowing the environmental risk of transmission-even at a very
local scale-isessential. The aim of this study was to assess how malaria
transmission is influenced and can be predicted by local climaticand
environmental factors. As the entomological part of a cohort study of 650
newborn babies in nine villages in the ToriBossito district of Southern Benin
between June 2007 and February 2010, human landing catches were performed to
assessthe density of malaria vectors and transmission intensity. Climatic
factors as well as household characteristics were recordedthroughout the study.
Statistical correlations between Anopheles density and environmental and
climatic factors weretested 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 belargely explained by factors associated with
the house's immediate surroundings, namely soil type, vegetation index andthe
proximity of a watercourse. Based on these results, a predictive regression
model was developed using a leave-one-outmethod, to predict the spatiotemporal
variability of malaria transmission in the nine villages. This study points up
theimportance of local environmental factors in malaria transmission and
describes a model to predict the transmission risk ofindividual children, based
on environmental and behavioral characteristics.
