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Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever

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  • Shuli Zhou

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
    Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou 510275, China)

  • Suhong Zhou

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
    Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou 510275, China)

  • Lin Liu

    (Center of Geo-Informatics for Public Security, School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China
    Department of Geography, University of Cincinnati, Cincinnati, OH 45221-0131, USA)

  • Meng Zhang

    (Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China)

  • Min Kang

    (Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China)

  • Jianpeng Xiao

    (Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China)

  • Tie Song

    (Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China)

Abstract

Environment and human mobility have been considered as two important factors that drive the outbreak and transmission of dengue fever (DF). Most studies focus on the local environment while neglecting environment of the places, especially epidemic areas that people came from or traveled to. Commuting is a major form of interactions between places. Therefore, this research generates commuting flows from mobile phone tracked data. Geographically weighted Poisson regression (GWPR) and analysis of variance (ANOVA) are used to examine the effect of commuting flows, especially those from/to epidemic areas, on DF in 2014 at the Jiedao level in Guangzhou. The results suggest that (1) commuting flows from/to epidemic areas affect the transmission of DF; (2) such effects vary in space; and (3) the spatial variation of the effects can be explained by the environment of the epidemic areas that commuters commuted from/to. These findings have important policy implications for making effective intervention strategies, especially when resources are limited.

Suggested Citation

  • Shuli Zhou & Suhong Zhou & Lin Liu & Meng Zhang & Min Kang & Jianpeng Xiao & Tie Song, 2019. "Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:24:p:5013-:d:296011
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    References listed on IDEAS

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    1. Zheng Cao & Tao Liu & Xing Li & Jin Wang & Hualiang Lin & Lingling Chen & Zhifeng Wu & Wenjun Ma, 2017. "Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis," IJERPH, MDPI, vol. 14(7), pages 1-14, July.
    2. Siong Choy Chong & Wendy Ming Yen Teoh* & Ye Qi, 2015. "Comparing customer satisfaction with China mobile and China telecom services: An empirical study," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(6), pages 247-262, Special I.
    3. Yebin Chen & Zhigang Zhao & Zhichao Li & Weihong Li & Zhipeng Li & Renzhong Guo & Zhilu Yuan, 2019. "Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 16(14), pages 1-14, July.
    4. Samir Bhatt & Peter W. Gething & Oliver J. Brady & Jane P. Messina & Andrew W. Farlow & Catherine L. Moyes & John M. Drake & John S. Brownstein & Anne G. Hoen & Osman Sankoh & Monica F. Myers & Dylan , 2013. "The global distribution and burden of dengue," Nature, Nature, vol. 496(7446), pages 504-507, April.
    5. Jayanthi Rajarethinam & Janet Ong & Shi-Hui Lim & Yu-Heng Tay & Wacha Bounliphone & Chee-Seng Chong & Grace Yap & Lee-Ching Ng, 2019. "Using Human Movement Data to Identify Potential Areas of Zika Transmission: Case Study of the Largest Zika Cluster in Singapore," IJERPH, MDPI, vol. 16(5), pages 1-13, March.
    6. Ben Adams & Durrell D Kapan, 2009. "Man Bites Mosquito: Understanding the Contribution of Human Movement to Vector-Borne Disease Dynamics," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-10, August.
    7. Chi-Chieh Huang & Tuen Yee Tiffany Tam & Yinq-Rong Chern & Shih-Chun Candice Lung & Nai-Tzu Chen & Chih-Da Wu, 2018. "Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness," IJERPH, MDPI, vol. 15(9), pages 1-12, August.
    8. Xiaopeng Qi & Yong Wang & Yue Li & Yujie Meng & Qianqian Chen & Jiaqi Ma & George F Gao, 2015. "The Effects of Socioeconomic and Environmental Factors on the Incidence of Dengue Fever in the Pearl River Delta, China, 2013," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(10), pages 1-13, October.
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