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 disease s caused by Schistosoma spp. and Fasciola spp. have recently been developed based on climate and satellite-retrieved data on temperature and vegetatio n coverage. By using these models, it was possible to describe a relationsh ip between vegetation index (Normalized Differences Vegetation Index (NDVI) ), land surface temperature (T-max) and disease prevalence, but little refe rence was made to the distribution of the corresponding intermediate host s nail. Presence of the intermediate host snail is a kev factor determining d istribution of the disease in sub-Saharan Africa and a good snail distribut ion mode would probably mirror the endemic area of schistosomiasis. In the present analysis, it was shown that snail distribution data corresponds wit h schistosomiasis prevalence data in relation to a forecast model based on NDVI and T-max data derived from the Advanced Very High Resolution Radiomet er (AVHRR) onboard the National Oceanic and Atmospheric Administration sate llite series. The 'best fit model included NDVI values from 125 to 145 and a T,,, data range of 10-32 degreesC. 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 ot her sites in Africa, other NDVI and T-max ranges may be more appropriate, d epending on the species of snail present, a topic that will be examined in further studies. (C) 2001 Elsevier Science B.V. All rights reserved.