GIS-based prediction of malaria risk in Egypt.
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.
Hassan
A N
AN
Institute of Environmental Studies and Research, Ain Shams University, Cairo, Egypt.
Kenawy
M A
MA
Kamal
H
H
Abdel Sattar
A A
AA
Sowilem
M M
MM
D000383:Agriculture; D000818:Animals; D000852:Anopheles / Q000145:classification / Q000469:parasitology; D002980:Climate; D003710:Demography; D016002:Discriminant Analysis; D004534:Egypt; D004812:Epidemiologic Methods; D005618:Fresh Water; D040362:Geographic Information Systems / Q000458:organization & administration*; D006801:Humans; D007303:Insect Vectors / Q000145:classification / Q000469:parasitology; D008288:Malaria / Q000453:epidemiology* / Q000209:etiology / Q000469:parasitology / Q000635:transmission; D020380:Needs Assessment; D011159:Population Surveillance; D011237:Predictive Value of Tests; D015995:Prevalence; D018570:Risk Assessment / Q000458:organization & administration*; D012307:Risk Factors; D012959:Socioeconomic Factors; D012987:Soil; D014507:Urbanization
D012987:Soil