ArticlePLoS neglected tropical diseases2019
Identification of high-risk habitats of Oncomelania hupensis, the intermediate host of schistosoma japonium in the Poyang Lake region, China: A spatial and ecological analysis.
Article in PLoS neglected tropical diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- Impact of climate warming on Oncomelania hupensis in China: multi-scale evidence.Infectious diseases of poverty · 2026Article
- A county-level indicator framework for assessing schistosomiasis transmission risk in post-transmission-interruption China.Infectious diseases of poverty · 2026Article
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- Proliferation of MDSCs may indicate a lowerParasite (Paris, France) · 2024Article
- From Perpetual Wetness to Soil Chemistry: Enumerating Environmental and Physicochemical Factors FavoringTropical medicine and infectious disease · 2023Article
- Influence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year's longitudinal surveillance data: a spatio-temporal modelling study.Infectious diseases of poverty · 2023Article
- Article
- Global Distribution ofInternational journal of environmental research and public health · 2023Article
- Prediction of the Risk Distributions for Anopheles sinensis, a Vector for Malaria in Shanghai, China.The American journal of tropical medicine and hygiene · 2023Article
- Schistosomiasis and Soil-transmitted Helminthiasis Morbidity Control in Selected Communities in Eastern Visayas, Philippines: Post-Haiyan.Acta medica Philippina · 2023Article
- Transmission Risk Predicting for Schistosomiasis in Mainland China by Exploring Ensemble Ecological Niche Modeling.Tropical medicine and infectious disease · 2022Article
- Identifying the Determinants of Distribution ofPathogens (Basel, Switzerland) · 2022Article
- Identification of the high-risk area for schistosomiasis transmission in China based on information value and machine learning: a newly data-driven modeling attempt.Infectious diseases of poverty · 2021Article
- Risk prediction of two types of potential snail habitats in Anhui Province of China: Model-based approaches.PLoS neglected tropical diseases · 2020Article
- Assessment of vector-host-pathogen relationships using data mining and machine learning.Computational and structural biotechnology journal · 2020Review
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Authors and funding
12 authors.
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Abstract
backgroundIdentifying and eliminating snail habitats is the key measure for schistosomiasis control, critical for the nationwide strategy of eliminating schistosomiasis in China. Here, our aim was to construct a new analytical framework to predict high-risk snail habitats based on a large sample field survey for Oncomelania hupensis, providing guidance for schistosomiasis control and prevention. METHODOLOGY/PRINCIPAL
findingsTen ecological models were constructed based on the occurrence data of Oncomelania hupensis and a range of variables in the Poyang Lake region of China, including four presence-only models (Maximum Entropy Models, Genetic Algorithm for rule-set Production, Bioclim and Domain) and six presence-absence models (Generalized Linear Models, Multivariate Adaptive Regression Splines, Flexible Discriminant Analysis, as well as machine algorithmic models-Random Forest, Classification Tree Analysis, Generalized Boosted Model), to predict high-risk snail habitats. Based on overall predictive performance, we found Presence-absence models outperformed the presence-only models and the models based on machine learning algorithms of classification trees showed the highest accuracy. The highest risk was located in the watershed of the River Fu in Yugan County, as well as the watershed of the River Gan and the River Xiu in Xingzi County, covering an area of 52.3 km2. The other high-risk areas for both snail habitats and schistosomiasis were mainly concentrated at the confluence of Poyang Lake and its five main tributaries. CONCLUSIONS/SIGNIFICANCE: This study developed a new distribution map of snail habitats in the Poyang Lake region, and demonstrated the critical role of ecological models in risk assessment to directing local field investigation of Oncomelania hupensis. Moreover, this study could also contribute to the development of effective strategies to prevent further spread of schistosomiasis from endemic areas to non-endemic areas.
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