An empirical malaria distribution map for West Africa

• Published in: Tropical medicine & international health Vol. 6; no. 10; pp. 779 - 786
• Main Authors: Kleinschmidt, Immo, Omumbo, Judy, Briët, Olivier, Van De Giesen, Nick, Sogoba, Nafomon, Mensah, Nathan Kumasenu, Windmeijer, Pieter, Moussa, Mahaman, Teuscher, Thomas
• Format: Journal Article
• Language: English
• Published: Oxford UK Blackwell Science Ltd 01.10.2001; Blackwell Science
• Subjects: Adolescent; Africa, Western - epidemiology; Afrika; Biological and medical sciences; Child; Child, Preschool; Demography; Female; Geographic Information Systems (GIS); Geography; Health Planning; Human protozoal diseases; Humans; Infant; infectieziekte; Infectious diseases; Malaria; Malaria - epidemiology; Malaria - prevention & control; malaria control; malaria prevalence; Male; mapping; Maps as Topic; Medical sciences; Models, Statistical; Parasitic diseases; Predictive Value of Tests; Prevalence; Protozoal diseases; spatial statistics; Topography, Medical; Tropical medicine; volksgezondheid; West Africa; Africa; Africa, Western; Infection; Human; Cartography; Protozoal disease; Malaria; Geographic distribution; Parasitosis; Epidemiology
• ISSN: 1360-2276; 1365-3156
• DOI: 10.1046/j.1365-3156.2001.00790.x

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.