GIS-based prediction of malaria risk in Egypt

Abstract

Environmental variables in a malaria geographic information system (GIS) database were analysed to discriminate between governorates at high and low risk of malaria. Only Fayoum governorate was categorized as a high risk area for malaria during the last 2 decades. Discriminant models correctly classified 96.3% of the risk categories and indicated that the most important predictor of risk is hydrogeology. Further GIS spatial analysis indicated that the high malaria risk in Fayoum is associated with a unique environmental envelope of biotic (presence of both efficient malaria vectors) and abiotic (hydrogeology and soil) variables. Recommendations for surveillance and control are discussed.