Integrated multisource modeling dataset on schistosome snail hosts in west Uganda: snail occurrence, environmental, geomorphological, and detection variables

The ATRAP (Action Towards Reducing Aquatic Snail Parasitic Diseases) project engaged 25 citizen scientists in western Uganda to sample 76 water contact sites weekly from March 2020 to February 2023, with sampling frequency remaining voluntary. The water sites were chosen based on a preliminary survey that identified areas with frequent risky water practices, such as swimming, water-fetching, washing, and bathing, along with sites where <i>Biomphalaria</i> snails were or were not initially detected. The citizen scientists (CS) submitted reports containing photographs of freshwater snails, including <i>Biomphalaria, Bulinus, Radix</i>, and a "pool" category for other species, with counts per genus/category after about 30 minutes of sampling. These reports were validated by a researcher, and a malacologist (the expert) sampled the same sites monthly from July 2020 to May 2022. The study focused on Biomphalaria spp., the only known intermediate host for <i>Schistosoma mansoni,</i> responsible for human schistosomiasis in Uganda. The presence of these snails is considered a strong indicator of potential schistosomiasis risk. A total of 6570 CS reports were submitted, with filters excluding invalid or incomplete data, leaving 3631 valid reports from 62 water contact sites. The expert submitted 1382 reports, which were also filtered to ensure consistency, resulting in 1073 valid reports from 56 common sites. Geomorphological variables such as elevation, slope steepness, flow accumulation, and topographic index were derived from the Copernicus GLO-30 DEM, while environmental variables like precipitation, surface temperature, and NDVI were calculated using various datasets including CHIRPS, MODIS, and Planet imagery. Temporal gaps in environmental variables were addressed using interpolation methods. Additionally, detection variables were incorporated to assess factors influencing snail detection, such as citizen scientist consistency, sampling time, duration, cumulative sampling frequency, and sampling density. These variables were intended to better model and understand the relationship between snail presence and environmental factors, with the goal of improving the accuracy of schistosomiasis risk assessments in the region.