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Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models

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  • Shujuan Li

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Beijing 100049, China)

  • Hongyan Ren

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China)

  • Wensheng Hu

    (Center for Health Statistics and Information, National Health and Family Planning Commission, No.38 Beilishi Road, Xicheng District, Beijing 100044, China)

  • Liang Lu

    (State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, 5 Changbai Road, Changping, Beijing 102206, China)

  • Xinliang Xu

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China)

  • Dafang Zhuang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China)

  • Qiyong Liu

    (State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, China CDC, 5 Changbai Road, Changping, Beijing 102206, China)

Abstract

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005–2012, this paper identified the spatiotemporal characteristics of HFRS distribution and the factors that impact this distribution. The results indicate that the spatial distribution of HFRS had a significant, positive spatial correlation. The spatiotemporal heterogeneity was affected by the temperature, precipitation, humidity, NDVI of January, NDVI of August for the previous year, land use, and elevation in 2005–2009. However, these factors did not explain the spatiotemporal heterogeneity of HFRS incidences in 2010–2012. Spatiotemporal heterogeneity of provincial HFRS incidences and its relation to environmental factors would provide valuable information for hygiene authorities to design and implement effective measures for the prevention and control of HFRS in China.

Suggested Citation

  • Shujuan Li & Hongyan Ren & Wensheng Hu & Liang Lu & Xinliang Xu & Dafang Zhuang & Qiyong Liu, 2014. "Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models," IJERPH, MDPI, vol. 11(12), pages 1-19, November.
    • Handle: RePEc:gam:jijerp:v:11:y:2014:i:12:p:12129-12147:d:42725
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    References listed on IDEAS

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    1. Qi Li & WenNa Zhao & YaMei Wei & Xu Han & ZhanYing Han & YanBo Zhang & ShunXiang Qi & YongGang Xu, 2014. "Analysis of Incidence and Related Factors of Hemorrhagic Fever with Renal Syndrome in Hebei Province, China," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-6, July.
    2. Hong Xiao & Hai-Ning Liu & Li-Dong Gao & Cun-Rui Huang & Zhou Li & Xiao-Ling Lin & Bi-Yun Chen & Huai-Yu Tian, 2013. "Investigating the Effects of Food Available and Climatic Variables on the Animal Host Density of Hemorrhagic Fever with Renal Syndrome in Changsha, China," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
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    Cited by:

    1. Shujuan Li & Lingli Zhu & Lidan Zhang & Guoyan Zhang & Hongyan Ren & Liang Lu, 2023. "Urbanization-Related Environmental Factors and Hemorrhagic Fever with Renal Syndrome: A Review Based on Studies Taken in China," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    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.
    3. Weizhen Ren & Zilong Zhang & Yueju Wang & Bing Xue & Xingpeng Chen, 2020. "Measuring Regional Eco-Efficiency in China (2003–2016): A “Full World” Perspective and Network Data Envelopment Analysis," IJERPH, MDPI, vol. 17(10), pages 1-15, May.
    4. 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.
    5. Krzysztof Rząsa & Mateusz Ciski, 2022. "Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic—Analysis of the Local Variations Using Geographically Weighted Regression," IJERPH, MDPI, vol. 19(19), pages 1-26, September.

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