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Identifying Determinants of Oncomelania hupensis Habitats and Assessing the Effects of Environmental Control Strategies in the Plain Regions with the Waterway Network of China at the Microscale

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  • Juan Qiu

    (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
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Rendong Li

    (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)

  • Xingjian Xu

    (Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, Hubei Province, China)

  • Chuanhua Yu

    (School of Public Health & Global Health Institute, Wuhan University, Wuhan 430072, Hubei Province, China)

  • Xin Xia

    (Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, Hubei Province, China)

  • Xicheng Hong

    (Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, Hubei Province, China)

  • Bianrong Chang

    (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
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Fengjia Yi

    (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
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yuanyuan Shi

    (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
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

This study aims to identify the landscape ecological determinants related to Oncomelania hupensis distribution, map the potential high risk of O. hupensis habitats at the microscale, and assess the effects of two environmental control strategies. Sampling was performed on 242 snail sites and 726 non-snail sites throughout Qianjiang City, Hubei Province, China. An integrated approach of landscape pattern analysis coupled with multiple logistic regression modeling was applied to investigate the effects of environmental factors on snail habitats. The risk probability of snail habitats positively correlated with patch fractal dimension (FD), paddy farm land proportion, and wetness index but inversely correlated with categorized normalized difference vegetation index (NDVI) and elevation. These findings indicate that FD can identify irregular features (e.g., irrigation ditches) in plain regions and that a moderate NDVI increases the microscale risk probability. Basing on the observed determinants, we predicted a map showing high-risk areas of snail habitats and simulated the effects of conduit hardening and paddy farming land rotation to dry farming land. The two approaches were confirmed effective for snail control. These findings provide an empirical basis for health professionals in local schistosomiasis control stations to identify priority areas and promising environmental control strategies for snail control and prevention.

Suggested Citation

  • Juan Qiu & Rendong Li & Xingjian Xu & Chuanhua Yu & Xin Xia & Xicheng Hong & Bianrong Chang & Fengjia Yi & Yuanyuan Shi, 2014. "Identifying Determinants of Oncomelania hupensis Habitats and Assessing the Effects of Environmental Control Strategies in the Plain Regions with the Waterway Network of China at the Microscale," IJERPH, MDPI, vol. 11(6), pages 1-15, June.
  • Handle: RePEc:gam:jijerp:v:11:y:2014:i:6:p:6571-6585:d:37387
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    Citations

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    Cited by:

    1. Yuanyuan Shi & Juan Qiu & Rendong Li & Qiang Shen & Duan Huang, 2017. "Identification of Potential High-Risk Habitats within the Transmission Reach of Oncomelania hupensis after Floods Based on SAR Techniques in a Plane Region in China," IJERPH, MDPI, vol. 14(9), pages 1-13, August.
    2. Juan Qiu & Rendong Li & Ying Xiao & Jing Xia & Hong Zhu & Yingnan Niu & Duan Huang & Qihui Shao & Ying Cui & Yong Wang, 2019. "Spatiotemporal Heterogeneity in Human Schistosoma japonicum Infection at Village Level in Hubei Province, China," IJERPH, MDPI, vol. 16(12), pages 1-11, June.

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