RESUMEN
Remote sensing and geographic information system [GIS] technologies were used to discriminate between 130 villages in the Nile Delta, at high and low risk for filariasis, as defined by microfilarial prevalence. Landsat Thematic Mapper [TM] data were digitally processed to generate a map of land-cover as well as spectral indices such as NDVI and moisture index. A Tasseled Cap transformation was also carried out on the TM data which produced 3 more indices [brightness, greenness and wetness]. GIS functions were used to extract information on land-cover and spectral indices within 1 km buffers around the study villages. The relationship between satellite data and prevalence was investigated using discriminant analysis. The analysis indicated that the most important landscape elements associated with prevalence were water and marginal vegetation, while wetness and moisture index were the most important indices. Discriminant functions generated for these variables were able to predict correctly 80% and 74% of high and low prevalence villages, respectively, with an overall accuracy of 77%. The present approach provided a promising tool for regional filariasis surveillance and helps direct control efforts