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The Spatial Analysis on Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China Based on Geographic Information System

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Listed:
  • Changjun Bao
  • Wanwan Liu
  • Yefei Zhu
  • Wendong Liu
  • Jianli Hu
  • Qi Liang
  • Yuejia Cheng
  • Ying Wu
  • Rongbin Yu
  • Minghao Zhou
  • Hongbing Shen
  • Feng Chen
  • Fenyang Tang
  • Zhihang Peng

Abstract

Background: Hemorrhagic fever with renal syndrome (HFRS) is endemic in mainland China, accounting for 90% of total reported cases worldwide, and Jiangsu is one of the most severely affected provinces. In this study, the authors conducted GIS-based spatial analyses in order to determine the spatial distribution of the HFRS cases, identify key areas and explore risk factors for public health planning and resource allocation. Methods: Interpolation maps by inverse distance weighting were produced to detect the spatial distribution of HFRS cases in Jiangsu from 2001 to 2011. Spatio-temporal clustering was applied to identify clusters at the county level. Spatial correlation analysis was conducted to detect influencing factors of HFRS in Jiangsu. Results: HFRS cases in Jiangsu from 2001 to 2011 were mapped and the results suggested that cases in Jiangsu were not distributed randomly. Cases were mainly distributed in northeastern and southwestern Jiangsu, especially in Dafeng and Sihong counties. It was notable that prior to this study, Sihong county had rarely been reported as a high-risk area of HFRS. With the maximum spatial size of 50% of the total population and the maximum temporal size of 50% of the total population, spatio-temporal clustering showed that there was one most likely cluster (LLR = 624.52, P

Suggested Citation

  • Changjun Bao & Wanwan Liu & Yefei Zhu & Wendong Liu & Jianli Hu & Qi Liang & Yuejia Cheng & Ying Wu & Rongbin Yu & Minghao Zhou & Hongbing Shen & Feng Chen & Fenyang Tang & Zhihang Peng, 2014. "The Spatial Analysis on Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China Based on Geographic Information System," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-8, September.
    • Handle: RePEc:plo:pone00:0083848
    DOI: 10.1371/journal.pone.0083848
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    Cited by:

    1. Liang Ge & Youlin Zhao & Zhongjie Sheng & Ning Wang & Kui Zhou & Xiangming Mu & Liqiang Guo & Teng Wang & Zhanqiu Yang & Xixiang Huo, 2016. "Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) ," IJERPH, MDPI, vol. 13(11), pages 1-14, October.
    2. Kaili She & Chunyu Li & Chang Qi & Tingxuan Liu & Yan Jia & Yuchen Zhu & Lili Liu & Zhiqiang Wang & Ying Zhang & Xiujun Li, 2021. "Epidemiological Characteristics and Regional Risk Prediction of Hemorrhagic Fever with Renal Syndrome in Shandong Province, China," IJERPH, MDPI, vol. 18(16), pages 1-12, August.

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