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Modelling the historical distribution of schistosomiasis-transmitting snails in South Africa using ecological niche models

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Nisa Ayob, Roelof Petrus Burger, Monray D. Belelie, Ncobile Nkosi, Henno Havenga, Lizaan de Necker, Dirk Cilliers

A disease carried by freshwater snails can move when the weather moves. By tracing where the snails could live, researchers mapped places in South Africa where infection may already be hiding, and where it could spread next.

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 schistosomiasistransmitting 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.

Transcript

A disease carried by freshwater snails can move when the weather moves. By tracing where the snails could live, researchers mapped places in South Africa where infection may already be hiding—and where it could spread next.

Schistosomiasis is widespread where sanitation is inadequate and clean water is lacking. In rural communities, farmers and fishermen can encounter snail-infested water during daily work. Communities without tap water may travel to snail-infested water for laundry, bathing, and cooking, increasing their chance of contracting the disease.

The central idea is like drawing a map of where a plant could grow: the model predicts distributions and maps using bioclimatic data, while identifying climatic and environmental variables that shape them. These models can predict where a species may occur and identify which climate and environmental conditions shape its distribution.

The study therefore used three approaches—Generalized Linear Model, Maximum Entropy, and Random Forest—to address the limitations identified for ecological niche models. One approach estimated distribution from the environmental conditions at current locations, while the three approaches were used to overcome their limitations.

So the predictions were combined into an ensemble model. The ensemble reached the highest score among the three approaches. The evaluation indicated that the ensemble model was based on competence rather than chance, giving confidence that it can examine areas at risk under current and future climates.

The recorded carrier snails cluster mainly across eastern South Africa and along parts of the coast, while much of the interior has few records. That uneven footprint matters because changing rainfall and temperature could expand where schistosomiasis can spread.

Here is the surprise: for one important snail, both temperature and rainfall strongly shaped its distribution in every model. Heavy rainfall can cause floods, allowing the snails to migrate into new habitats, and potential habitats can form nearby. The same snail preferred hotter conditions with less moderate rain than another disease-carrying snail.

Its suitability was also linked to temperature-related conditions. This means that rainfall does not simply add water to the landscape; it can change where suitable snail habitats appear. The maps suggest that conditions favouring this snail are concentrated across much of eastern and coastal South Africa, including parts of the Northern Cape despite no snails being sampled there.

That matters because climate change could shift where schistosomiasis transmission is possible. The study found that temperature and rainfall can affect the distribution of schistosomiasis in South Africa, so climate variability may influence its future distribution.

If temperatures and rainfall change substantially, the geographical distribution and severity of outbreaks could change as well. The models showed a shift in southern and southwestern parts of the Western Cape, even though no disease-carrying snails are known there because naturally acidic water may harm them.

The shift was likely linked to temperature and rainfall conditions considered suitable for transmission. The results can help identify additional places where disease-carrying snails may already exist but have not yet been discovered, as well as future areas where the disease may spread.

These results can help identify additional sites where Schistosoma-transmitting snails may already exist, as well as future areas where the disease is likely to spread. Temperature and rainfall help determine where disease-carrying snails can live, and combining several forecasts produced a dependable historical map.

That can help health workers look for overlooked sites and prepare for future changes.

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