In 13 villages in the savannah zone and 21 villages in the forest zone of Côte d'Ivoire, the biting density of the principal malaria vector, Anopheles gambiae, was studied as a function of rice cultivation in the inland valleys in a 2-km radius around each village. In the savannah villages, during the main season cropping period, surface water on rice-cultivated and to a lesser extent on uncultivated inland valleys seems to contribute strongly to the A. gambiae population density. For the off-season cropping period (which starts after the first light rains in the savannah zone), correlations were weaker. Breeding sites other than in inland valleys may play an important role in the savannah zone. In the forest zone, however, the A. gambiae population density was strongly correlated with the surface water availability (SWA) in the rice-cultivated inland valleys, whereas the correlation with the SWA in other (uncultivated) inland valleys was weak. The requirement of sunlit breeding sites for A. gambiae might explain this difference between zones. In the forest zone, only inland valleys cleared for rice cultivation meet this requirement, whereas all other inland valleys are covered with dense vegetation. In the savannah zone, however, most undergrowth is burnt during the dry season, which permits sunlight to reach puddles resulting from the first rains.@en

The objective of this study was to produce a malaria distribution map that would constitute a useful tool for development and health planners in West Africa. The recently created continental database of malaria survey results (MARA/ARMA 1998) provides the opportunity for producing empirical models and maps of malaria distribution at a regional and eventually at a continental level. This paper reports on the mapping of malaria distribution for sub-Saharan West Africa based on these data. The strategy was to undertake a spatial statistical analysis of malaria parasite prevalence in relation to those potential bio-physical environmental factors involved in the distribution of malaria transmission intensity which are readily available at any map location. The resulting model was then used to predict parasite prevalence for the whole of West Africa. We also produced estimates of the proportion of population of each country in the region exposed to various categories of risk to show the impact that malaria is having on individual countries. The data represent a very large sample of children in West Africa. It constitutes a first attempt to produce a malaria risk map of the West African region, based entirely on malariometric data. We anticipate that it will provide useful additional guidance to control programme managers, and that it can be refined once sufficient additional data become available.

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