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Article

Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis

1
Key Laboratory of Monitoring and Estimate for Environment and Disaster of Hubei Province, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China
2
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
3
Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(12), 2206; https://doi.org/10.3390/ijerph16122206
Received: 10 April 2019 / Revised: 11 June 2019 / Accepted: 18 June 2019 / Published: 21 June 2019
(This article belongs to the Section Environmental Health)
Schistosomiasis is a snail-borne parasitic disease endemic to the tropics and subtropics, whose distribution depends on snail prevalence as determined by climatic and environmental factors. Here, dynamic spatial and temporal patterns of Oncomelania hupensis distributions were quantified using general statistics, global Moran’s I, and standard deviation ellipses, with Maxent modeling used to predict the distribution of habitat areas suitable for this snail in Gong’an County, a severely affected region of Jianghan Plain, China, based on annual average temperature, humidity of the climate, soil type, normalized difference vegetation index, land use, ditch density, land surface temperature, and digital elevation model variables; each variable’s contribution was tested using the jackknife method. Several key results emerged. First, coverage area of O. hupensis had changed little from 2007 to 2012, with some cities, counties, and districts alternately increasing and decreasing, with ditch and bottomland being the main habitat types. Second, although it showed a weak spatial autocorrelation, changing negligibly, there was a significant east–west gradient in the O. hupensis habitat area. Third, 21.9% of Gong’an County’s area was at high risk of snail presence; and ditch density, temperature, elevation, and wetting index contributed most to their occurrence. Our findings and methods provide valuable and timely insight for the control, monitoring, and management of schistosomiasis in China. View Full-Text
Keywords: spatiotemporal changes; Maxent; suitable habitats; Oncomelania hupensis spatiotemporal changes; Maxent; suitable habitats; Oncomelania hupensis
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MDPI and ACS Style

Niu, Y.; Li, R.; Qiu, J.; Xu, X.; Huang, D.; Shao, Q.; Cui, Y. Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis. Int. J. Environ. Res. Public Health 2019, 16, 2206. https://doi.org/10.3390/ijerph16122206

AMA Style

Niu Y, Li R, Qiu J, Xu X, Huang D, Shao Q, Cui Y. Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis. International Journal of Environmental Research and Public Health. 2019; 16(12):2206. https://doi.org/10.3390/ijerph16122206

Chicago/Turabian Style

Niu, Yingnan, Rendong Li, Juan Qiu, Xingjian Xu, Duan Huang, Qihui Shao, and Ying Cui. 2019. "Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis" International Journal of Environmental Research and Public Health 16, no. 12: 2206. https://doi.org/10.3390/ijerph16122206

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