{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T09:45:47Z","timestamp":1788601547503,"version":"build-2803163510"},"reference-count":81,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004424","name":"Water Research Commission","doi-asserted-by":"publisher","award":["127549"],"award-info":[{"award-number":["127549"]}],"id":[{"id":"10.13039\/501100004424","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Schistosomiasis is a vector-borne disease transmitted by freshwater snails and is prevalent in rural areas with poor sanitation and no access to tap water. Three snail species are known to transmit schistosomiasis in South Africa (SA), namely <jats:italic>Biomphalaria pfeifferi<\/jats:italic>, <jats:italic>Bulinus globosus<\/jats:italic> and <jats:italic>Bulinus africanus<\/jats:italic>. In 2003, a predicted prevalence of 70% was reported in tropical climates in SA. Temperature and rainfall variability can alter schistosomiasis-transmitting snails\u2019 development by increasing or decreasing their abundance and geographical distribution. This study aimed to map the historical distribution of schistosomiasis from 1950 to 2006 in SA. The snail sampling data were obtained from the historical National Snail Freshwater Collection (NFSC). Bioclimatic variables were extracted using ERA 5 reanalysis data provided by the Copernicus Climate Change Service. In this study, we used 19 bioclimatic and four soil variables. The temporal aggregation was the mean climatological period pre-calculated over the 40-year reference period with a spatial resolution of 0.5\u00b0 x 0.5\u00b0. Multicollinearity was reduced by calculating the Variance Inflation Factor Core (VIF), and highly correlated variables (&gt; 0.85) were excluded. To obtain an \"ensemble\" and avoid the integration of weak models, we averaged predictions using the True Skill Statistical (TSS) method. Results showed that the ensemble model achieved the highest Area Under the Curve (AUC) scores (0.99). For <jats:italic>B<\/jats:italic>. <jats:italic>africanus<\/jats:italic>, precipitation-related variables contributed to determining the suitability for schistosomiasis. Temperature and precipitation-related variables influenced the distribution of <jats:italic>B<\/jats:italic>. <jats:italic>globosus<\/jats:italic> in all three models. <jats:italic>Biomphalaria pfeifferi<\/jats:italic> showed that Temperature Seasonality (bio4) contributed the most (47%) in all three models. According to the models, suitable areas for transmitting schistosomiasis were in the eastern regions of South Africa. Temperature and rainfall can impact the transmission and distribution of schistosomiasis in SA. The results will enable us to develop future projections for <jats:italic>Schistosoma<\/jats:italic> in SA based on climate scenarios.<\/jats:p>","DOI":"10.1371\/journal.pone.0295149","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T19:10:20Z","timestamp":1701371420000},"page":"e0295149","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":17,"title":["Modelling the historical distribution of schistosomiasis-transmitting snails in South Africa using ecological niche models"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9616-6395","authenticated-orcid":true,"given":"Nisa","family":"Ayob","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roelof P.","family":"Burger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Monray D.","family":"Belelie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ncobile C.","family":"Nkosi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henno","family":"Havenga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lizaan","family":"de Necker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dirk P.","family":"Cilliers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,11,30]]},"reference":[{"issue":"2","key":"pone.0295149.ref001","first-page":"1","article-title":"Predictive risk mapping of schistosomiasis in Madagascar using ecological niche modeling and precision mapping","volume":"7","author":"MA Deka","year":"2022","journal-title":"Tropical Medicine and Infectious Disease"},{"key":"pone.0295149.ref002","volume-title":"Accelerating Work to Overcome the Global Impact of Neglected Tropical Diseases","author":"L Savioli","year":"2012"},{"key":"pone.0295149.ref003","doi-asserted-by":"crossref","first-page":"43","DOI":"10.12980\/APJTB.4.2014C831","article-title":"Novel antipathy for schistosomiasis\u2013the most lethal ailment of the tropical region","volume":"4","author":"R. 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