ArticleParasitology research2022
Predicting the habitat suitability of Schistosoma intermediate host Bulinus truncatus, its predatory aquatic insect Odonata nymph, and the associated aquatic plant Ceratophyllum demersum using MaxEnt.
Article in Parasitology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software.PLoS neglected tropical diseases · 2025Pooled it
- Temporal modelling of Lymnaea natalensis (Krauss, 1848) in tropical aquatic habitats.The Onderstepoort journal of veterinary research · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Schistosomiasis is one of the most important parasitic diseases in tropical and subtropical areas. Its prevalence is associated with the distribution of freshwater snails, which are their intermediate hosts. Thus, control of freshwater snails is the solution to reduce the transmission of this disease. This will be achieved by understanding the relationship between the snails and their habitats including natural enemies and associated aquatic plants as well as the factors affecting their distribution. In this study, Maximum Entropy model (MaxEnt) was used for mapping and predicting the possible geographic distribution of Bulinus truncatus snail (the intermediate host of Schistosoma haematobium), Odonata nymph (predatory aquatic insect), and Ceratophyllum demersum (the associated aquatic plant) in Egypt based on topographic and climatic factors. The models of the investigated species were evaluated using the area under receiver operating characteristic curve. The results showed that the potential risk areas were along the banks of the Nile River and its irrigation canals. In addition, the MaxEnt models revealed some similarities in the distribution pattern of the vector, the predator, and the aquatic plant. It is obvious that the predictive distribution range of B. truncatus was affected by altitude, precipitation seasonality, isothermality, and mean temperature of warmest quarter. The presence of B. truncatus decreases with the increase of altitude and precipitation seasonality values. It could be concluded that the MaxEnt model could help introducing a predictive risk map for Schistosoma haematobium prevalence and performing better management strategies for schistosomiasis.
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