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Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013

Author

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  • Yan-Yan Chen
  • Xi-Bao Huang
  • Ying Xiao
  • Yong Jiang
  • Xiao-wei Shan
  • Juan Zhang
  • Shun-Xiang Cai
  • Jian-Bing Liu

Abstract

Background: Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions. Methods: In this study, spatial autocorrelation methodologies, including global Moran’s I and local Getis–Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time. Results: The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran’s I > 0, P

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0118362
    DOI: 10.1371/journal.pone.0118362
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    References listed on IDEAS

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    1. Júlia Viladomat & Rahul Mazumder & Alex McInturff & Douglas J. McCauley & Trevor Hastie, 2014. "Assessing the significance of global and local correlations under spatial autocorrelation: A nonparametric approach," Biometrics, The International Biometric Society, vol. 70(2), pages 409-418, June.
    2. Darren J Gray & Gail M Williams & Yuesheng Li & Honggen Chen & Simon J Forsyth & Robert S Li & Adrian G Barnett & Jiagang Guo & Allen G Ross & Zheng Feng & Donald P McManus, 2009. "A Cluster-Randomised Intervention Trial against Schistosoma japonicum in the Peoples' Republic of China: Bovine and Human Transmission," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-7, June.
    3. Brady J Mattsson & Elise F Zipkin & Beth Gardner & Peter J Blank & John R Sauer & J Andrew Royle, 2013. "Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-12, February.
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    Cited by:

    1. Hua Gu & Congcong Yan & Zhenggang Jiang & Xiuyang Li & Enfu Chen & Jianmin Jiang & Qingwu Jiang & Yibiao Zhou, 2018. "Epidemiological Trend of Typhoid and Paratyphoid Fevers in Zhejiang Province, China from 1953 to 2014," IJERPH, MDPI, vol. 15(11), pages 1-13, November.
    2. 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.

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