MAPPING MALARIA TRANSMISSION INTENSITY USING GEOGRAPHICAL INFORMATION-SYSTEMS (GIS) - AN EXAMPLE FROM KENYA

That there are so few examples of the use of epidemiological maps in m alaria control may be explained by the lack of suitable, spatially def ined data and of an understanding of how epidemiological variables rel ate to disease outcome. However, recent evidence suggests that the cli nical outcomes of infection are determined by the intensity of parasit e 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 c onducted in Kenya were abstracted and spatially defined. Risks of infe ction with Plasmodium falciparum among Kenyan children, estimated from combinations of parasitological, geographical, demographic and climat ic data in a GIS platform, appear to be low for 2.9 million, stable bu t 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.) W hilst the parasitological data were obtained from a variety of sources across different age-groups and times, these markers of endemicity re mained relatively stable within the broad definitions of high, moderat e and low transmission intensity. Models relating ecological and clima tic features to malaria intensity and improvements in our understandin g of the relationships between parasite exposure and disease outcome w ill hopefully provide a more rational basis for malaria control in the near future.