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That there are so few examples of the use of epidemiological maps in malaria control may be explained by the lack of suitable, spatially defined data and of an understanding of how epidemiological variables relate to disease outcome. However, recent evidence suggests that the clinical outcomes of infection are determined by the intensity of parasite exposure, and developments in geographical information systems (GIS) provide new ways to represent epidemiological data spatially. In the present study, parasitological data from 682 cross-sectional surveys conducted in Kenya were abstracted and spatially defined. Risks of infection with Plasmodium falciparum among Kenyan children, estimated from combinations of parasitological, geographical, demographic and climatic data in a GIS platform, appear to be low for 2.9 million, stable but low for another 1.3 million, moderate for 3.0 million and high for 0.8 million. (Estimates were not available for 1.4 million children.) Whilst the parasitological data were obtained from a variety of sources across different age-groups and times, these markers of endemicity remained relatively stable within the broad definitions of high, moderate and low transmission intensity. Models relating ecological and climatic features to malaria intensity and improvements in our understanding of the relationships between parasite exposure and disease outcome will hopefully provide a more rational basis for malaria control in the near future.


Journal article


Ann Trop Med Parasitol

Publication Date





7 - 21


Climate, Cross-Sectional Studies, Geography, Health Surveys, Humans, Kenya, Malaria, Falciparum