The long range goal of this proposed work is to utilize geographic information system (GIS) methods and data from sensor systems on earth-observing satellites to develop practical disease prediction and control models for schistosomiasis. GIS methods will be used to evaluate the relative suitability of climate and surface hydrology at different sites and regions for parasite life cycle development and disease propagation. Thermal-moisture domains will be identified using satellite-based diurnal temperature difference and vegetation index maps and then analyzed in the GIS for spatial correlation to map data on prevalence surveys and digital databases from the Food and Agriculture Organization of the United Nations on climate, soils and crop production system zone features. The """"""""Climate Based Parasite Forecast System"""""""" previously developed for Fasciola will be adapted for Schistosoma mansoni and S. haematobium based on available prevalence data, the growing degree day concept and the modified Penman water budget. Patterns will be validated by field surveys of human infection prevalence in 5 GIS-derived thermal-moisture domains (10 villages each) and snail population bionomics and seasonal infection patterns at representative transmission sites in 5 villages in each of the thermal-moisture zones. GIS model output will consist of 30-year-average and annual risk maps based on climate, relevant agroecologic factors, satellite data and the environmental preferences and limits of tolerance of S. mansoni and S. haematobium. The GIS model will be used to develop more targeted Ministry of Health treatment and control programs.
| Malone, J B; McNally, K L; McCarroll, J C et al. (2004) Modeling the biocoenose of parasitic diseases using remote sensing and geographic information systems. Parassitologia 46:59-61 |
| Malone, J B; Yilma, J M; McCarroll, J C et al. (2001) Satellite climatology and the environmental risk of Schistosoma mansoni in Ethiopia and east Africa. Acta Trop 79:59-72 |
