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Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China

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  • Yingnan Niu

    (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
    College of Earth and Planetary Sciences, 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)

  • 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)

  • Xingjian Xu

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

  • Duan Huang

    (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
    College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yubing Qu

    (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
    College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

This study compared changes in the spatial clustering of schistosomiasis in Jianghan Plain, China by applying Kulldorff’s spatial scan statistic. The Geodetector software was employed to detect the environmental determinants of schistosomiasis annually from 2007 to 2012. The most likely spatial cluster in 2007 covered the north-central part of Jianghan Plain, whereas those observed from 2008 to 2012 were toward the south, with extended coverage in generally the same areas across various periods, and some variation nevertheless in precise locations. Furthermore, the 2007 period was more likely to be clustered than any other period. We found that temperature, land use, and soil type were the most critical factors associated with infection rates in humans. In addition, land use and soil type had the greatest impact on the prevalence of schistosomiasis in 2009, whereas this effect was minimal in 2007. The effect of temperature on schistosomiasis prevalence reached its maximum in 2010, whereas in 2008, this effect was minimal. Differences observed in the effects of those two factors on the spatial distribution of human schistosomiasis were inconsistent, showing statistical significance in some years and a lack thereof in others. Moreover, when two factors operated simultaneously, a trend of enhanced interaction was consistently observed. High-risk areas with strong interactions of affected factors should be targeted for disease control interventions.

Suggested Citation

  • Yingnan Niu & Rendong Li & Juan Qiu & Xingjian Xu & Duan Huang & Yubing Qu, 2018. "Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China," IJERPH, MDPI, vol. 15(7), pages 1-16, July.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1481-:d:157737
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    References listed on IDEAS

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    1. Yi Hu & Chenglong Xiong & Zhijie Zhang & Can Luo & Ted Cohen & Jie Gao & Lijuan Zhang & Qingwu Jiang, 2014. "Changing Patterns of Spatial Clustering of Schistosomiasis in Southwest China between 1999–2001 and 2007–2008: Assessing Progress toward Eradication after the World Bank Loan Project," IJERPH, MDPI, vol. 11(1), pages 1-12, January.
    2. Yan-Yan Chen & Xi-Bao Huang & Ying Xiao & Yong Jiang & Xiao-wei Shan & Juan Zhang & Shun-Xiang Cai & Jian-Bing Liu, 2015. "Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-14, April.
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