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

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 and Zhihang Peng

PLOS ONE, 2014, vol. 9, issue 9, 1-8

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

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0083848

DOI: 10.1371/journal.pone.0083848

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