Background: Schistosomiasis prevalence is high in southwestern Nigeria and planorbids of the genus Bulinus had been implicated in the transmission of the disease in the area. The knowledge of species distribution in relation to environmental variables will be auspicious in planning control strategies.
Methods: Satellite imagery and geographic information system (GIS) were used to develop models for predicting the habitats suitable for bulinid species. Monthly snail sample collection was done in twenty-three randomly selected water contact sites using standard method for a period of two years. Remotely sensed variables such as Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) were extracted from Landsat TM, ETM+; Slope and Elevation were obtained from digital elevation model (DEM) while Rainfall was retrieved from European Meteorology Research Program. These environmental factors and snail species were integrated into GIS to predict the potential habitats of different bulinid species using exploratory regression models.
Results: The following environmental variables: flat-moderate slope (0.01-15.83), LST (21.1oC-23.4oC), NDVI (0.19-0.52), spatial rainfall (> 1,569.34 mm) and elevation (1-278 meters) all contributed to the model used in predicting habitat suitable for bulinids snail intermediate hosts. Exploratory regression models showed that LST, NDVI and slope were predictors of B. globosus and B. jousseaumei; elevation, LST, Rainfall and slope were predictors of B. camerunensis; spatial rainfall, NDVI and slope were predictors of B. senegalensis while NDVI and slope were predictors of B. forskalii in the area. Bulinids in the forskalii group showed clustering in middle belt and south. The predictive risk map of B. jousseaumei was similar to the pattern described for B. globosus, but with a high R-square value of 81%.
Conclusion: The predictive risk models of bulinid species in this study provided a robust output for the study area which could be used as base-line for other areas in that ecological zone. It will be useful in appropriate allocation of scares resources in the control of schistosomiasis in that environment.