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.

Congcong Xia,Si Li,Shizhu Li,Jian Hu,Shuang Xiao,Henry Lynn,Chengfang Lu,Ying Liu,Zhijie Zhang,Michael P Ward,Yi Hu,Jun Zhang,Song Liang

doi:10.1371/journal.pntd.0007386

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/SignificanceThis 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.

Highlights

Schistosomiasis japonica, a water-borne parasitic disease, has long been prevalent in 12 provinces located along the Yangtze River in China
Oncomelania hupensis is the sole intermediate host of Schistosoma japonicum and it is critical for the long-term sustainable control and elimination of schistosomiasis
We suggest a new analytical framework to predict high-risk snail habitats based on ecological models

Summary

Introduction

Schistosomiasis japonica, a water-borne parasitic disease, has long been prevalent in 12 provinces located along the Yangtze River in China. It is caused by infection with the parasite Schistosoma japonicum, which has a unique intermediate host, Oncomelania hupensis. It is alarming that the area of snail habitat in some regions (e.g. Hubei, Hunan, Jiangxi and Anhui) are still extensive and new or infective snail habitats are still being discovered, especially in these lake and marshland regions (e.g. Dongting Lake and Poyang Lake regions)[3] This represents a serious challenge for preventing a rebound in prevalence and spread of schistosomiasis in China. 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

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