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Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China

Author

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  • Yebin Chen

    (School of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, China
    Research Institute of Smart City, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Zhigang Zhao

    (Research Institute of Smart City, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Zhichao Li

    (Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China)

  • Weihong Li

    (School of Geography, South China Normal University, Guangzhou 510631, China)

  • Zhipeng Li

    (Institute of Digital Agriculture Research, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China)

  • Renzhong Guo

    (School of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, China
    Research Institute of Smart City, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Zhilu Yuan

    (Research Institute of Smart City, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

Abstract

Dengue fever is one of the most common vector-borne diseases in the world and is mainly affected by the interaction of meteorological, human and land-use factors. This study aims to identify the impact of meteorological, human and land-use factors on dengue fever cases, involving the interplay between multiple factors. The analyses identified the statistically significant determinants affecting the transmission of dengue fever, employing cross-correlation analysis and the geo-detector model. This study was conducted in Guangzhou, China, using the data of confirmed cases of dengue fever, daily meteorological records, population density distribution and land-use distribution. The findings highlighted that the dengue fever hotspots were mainly distributed in the old city center of Guangzhou and were significantly shaped by meteorological, land-use and human factors. Meteorological factors including minimum temperature, maximum temperature, atmospheric pressure and relative humidity were correlated with the transmission of dengue fever. Minimum temperature, maximum temperature and relative humidity presented a statistically significant positive correlation with dengue fever cases, while atmospheric pressure presented statistically significant negative correlation. Minimum temperature, maximum temperature, atmospheric pressure and humidity have lag effects on the transmission of dengue fever. The population, community age, subway network density, road network density and ponds presented a statistically significant positive correlation with the number of dengue fever cases, and the interaction among land-use and human factors could enhance dengue fever transmission. The ponds were the most important interaction factors, which might strengthen the influence of other factors on dengue fever transmission. Our findings have implications for pre-emptive dengue fever control.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:14:p:2486-:d:247815
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    References listed on IDEAS

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    2. Hai-Yan Xu & Xiuju Fu & Lionel Kim Hock Lee & Stefan Ma & Kee Tai Goh & Jiancheng Wong & Mohamed Salahuddin Habibullah & Gary Kee Khoon Lee & Tian Kuay Lim & Paul Anantharajah Tambyah & Chin Leong Lim, 2014. "Statistical Modeling Reveals the Effect of Absolute Humidity on Dengue in Singapore," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 8(5), pages 1-11, May.
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    Cited by:

    1. Zhichao Li & Helen Gurgel & Nadine Dessay & Luojia Hu & Lei Xu & Peng Gong, 2020. "Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation," IJERPH, MDPI, vol. 17(12), pages 1-29, June.
    2. Yuqi Zhang & Hongyan Ren & Runhe Shi, 2022. "Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    3. 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.

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