Spatial patterns of urinary schistosomiasis infection in a highly endemic area of coastal Kenya

Abstract

Urinary schistosomiasis remains a major contributor to the disease burden along the southern coast of Kenya. Selective identification of transmission hot spots offers the potential for more effective, highly-focal snail control and human chemotherapy to reduce Schistosoma haematobium transmission. In the present study, a geographic information system was used to integrate demographic, parasitologic, and household location data for an endemic village and neighboring households with the biotic, abiotic, and location data for snail collection/water contact sites. A global spatial statistic was used to detect area-wide trends of clustering for human infection at the household level. Local spatial statistics were then applied to detect specific household clusters of infection, and, as a focal spatial statistic, to evaluate clustering of infection around a putative transmission site. High infection intensities were clustered significantly around a water contact site with high numbers of snails shedding S. haematobium cercariae. When age was considered, clustering was found to be significant at different distances for different age groups.