ArticlePloS one2023
Modelling the historical distribution of schistosomiasis-transmitting snails in South Africa using ecological niche models.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Modeling the current spatial distribution of snail intermediate hosts of schistosomiasis using Maxent software in the Volta Basin (Burkina Faso).Parasite epidemiology and control · 2026Article
- Potential of machine learning for prevention and control of neglected tropical diseases: a scoping review.Communications medicine · 2026Article
- Economic Evaluation of Multi-Objective Schistosomiasis Control Through Systemic Causality: Theoretical Advances and Governance Implications.Tropical medicine and infectious disease · 2026Review
- Freshwater Snails at the Biodiversity-Climate-Health Nexus: A Call to Recognize Neglected Models for Eco-Evolutionary and One Health Research.Ecology and evolution · 2026Article
- Global research trends at the intersection of climate change and parasitic diseases: a systematic bibliometric research (2000-2025).Frontiers in cellular and infection microbiology · 2026Article
- Article
- Epidemiology and Current Challenges of Human Schistosomiasis Along the Shabelle River, Somali Regional State, Eastern Ethiopia.Acta parasitologica · 2025Article
- Impact of Climate Change on Schistosomiasis Transmission and Distribution-Scoping Review.International journal of environmental research and public health · 2025Article
- Distribution Patterns ofEcology and evolution · 2025Article
- Predicting the potential distribution of 12 threatened medicinal plants on the Qinghai-Tibet Plateau, with a maximum entropy model.Ecology and evolution · 2024Article
- Species distribution modeling for disease ecology: A multi-scale case study for schistosomiasis host snails in Brazil.PLOS global public health · 2024Article
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7 authors.
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Abstract
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 Biomphalaria pfeifferi, Bulinus globosus and Bulinus africanus. In 2003, a predicted prevalence of 70% was reported in tropical climates in SA. Temperature and rainfall variability can alter schistosomiasis-transmitting snails' 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° x 0.5°. Multicollinearity was reduced by calculating the Variance Inflation Factor Core (VIF), and highly correlated variables (> 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 B. africanus, precipitation-related variables contributed to determining the suitability for schistosomiasis. Temperature and precipitation-related variables influenced the distribution of B. globosus in all three models. Biomphalaria pfeifferi 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 Schistosoma in SA based on climate scenarios.
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