Using Remote Sensing Methodologies to Combat Schistosomiasis in Northern Senegal
Schistosomiasis is a neglected tropical disease (NTD) associated with poverty, a lack of clean water and sanitation, caused by the Schistosoma parasite affecting more than 240 million people a year. It is transmitted through snail vector (Bulinus and Biomphalaria spp.) and mass drug administration (MDA) to control disease costs ~$100 million annually. In Senegal, WHO estimates MDA coverage of the at-risk population <10%. Previously, teams in Ghana and Morocco demonstrated that removal of certain aquatic vegetation decreased the prevalence of schistosomiasis in nearby villages.
Literature indicates certain types of vegetation are significantly associated with snail presence – this held true in northern Senegal data. Ceratophyllum was the most significant environmental predictor of snail presence among lake and river water access sites, followed by Ludwigia. Visible and NIR proxy biosignature scores of three vegetation types present in water access points with and without snail habitats did not indicate significantly different NDVI scores, but did provide direction on future analyses using NDVI measures.
The methods proposed here serve as a targeted approach to supplementing and strengthening existing control efforts in communities already overburdened by NTDs.
Next steps: to investigate the environmental characteristics at the site level, including vegetation, water quality, topography, and surrounding land use land cover by comparing drone imagery collected at the same time the satellite imagery was obtained to determine what imagery components best represent the environmental parameters of interest. By identifying significant environmental parameters, moving forward we will determine the unique sub-pixel makeup of the image at the locations of the parameters of interest. These signatures will be locally validated among known sites before field validation in previously untested areas in northern Senegal, which will occur this summer.