Use of satellite remote sensing and geographic information systems to model the distribution and abundance of snail intermediate hosts in Africa: a preliminary model for Biomphalaria pfeifferi in Ethiopia.

Geographic information system (GIS) risk models for the snail-borne diseases caused by Schistosoma spp. and Fasciola spp. have recently been developed based on climate and satellite-retrieved data on temperature and vegetation coverage. By using these models, it was possible to describe a relationship between vegetation index (Normalized Differences Vegetation Index (NDVI)), land surface temperature (T(max)) and disease prevalence, but little reference was made to the distribution of the corresponding intermediate host snail. Presence of the intermediate host snail is a key factor determining distribution of the disease in sub-Saharan Africa and a good snail distribution mode would probably mirror the endemic area of schistosomiasis. In the present analysis, it was shown that snail distribution data corresponds with schistosomiasis prevalence data in relation to a forecast model based on NDVI and T(max) data derived from the Advanced Very High Resolution Radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration satellite series. The 'best fit' model included NDVI values from 125 to 145 and a T(max) data range of 10-32 degrees C. This model included 92.3, 90.4 and 94.6% of the positive snail sample sites in GIS query overlay areas extracted from annual, dry season and wet season composite maps, respectively. For other sites in Africa, other NDVI and T(max) ranges may be more appropriate, depending on the species of snail present, a topic that will be examined in further studies.