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The Relationship between the Migrant Population’s Migration Network and the Risk of COVID-19 Transmission in China—Empirical Analysis and Prediction in Prefecture-Level Cities

Author

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  • Chenjing Fan

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
    School of Architecture, Tsinghua University, Beijing 100084, China)

  • Tianmin Cai

    (Department of Health Care & Medical Technology, Nanjing Benq Medical Center, Nanjing 210037, China)

  • Zhenyu Gai

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

  • Yuerong Wu

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

Abstract

The outbreak of COVID-19 in China has attracted wide attention from all over the world. The impact of COVID-19 has been significant, raising concerns regarding public health risks in China and worldwide. Migration may be the primary reason for the long-distance transmission of the disease. In this study, the following analyses were performed. (1) Using the data from the China migrant population survey in 2017 (Sample size = 432,907), a matrix of the residence–birthplace (R-B matrix) of migrant populations is constructed. The matrix was used to analyze the confirmed cases of COVID-19 at Prefecture-level Cities from February 1–15, 2020 after the outbreak in Wuhan, by calculating the probability of influx or outflow migration. We obtain a satisfactory regression analysis result ( R 2 = 0.826–0.887, N = 330). (2) We use this R-B matrix to simulate an outbreak scenario in 22 immigrant cities in China, and propose risk prevention measures after the outbreak. If similar scenarios occur in the cities of Wenzhou, Guangzhou, Dongguan, or Shenzhen, the disease transmission will be wider. (3) We also use a matrix to determine that cities in Henan province, Anhui province, and Municipalities (such as Beijing, Shanghai, Guangzhou, Shenzhen, Chongqing) in China will have a high risk level of disease carriers after a similar emerging epidemic outbreak scenario due to a high influx or outflow of migrant populations.

Suggested Citation

  • Chenjing Fan & Tianmin Cai & Zhenyu Gai & Yuerong Wu, 2020. "The Relationship between the Migrant Population’s Migration Network and the Risk of COVID-19 Transmission in China—Empirical Analysis and Prediction in Prefecture-Level Cities," IJERPH, MDPI, vol. 17(8), pages 1-11, April.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:8:p:2630-:d:344350
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    References listed on IDEAS

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    1. Lin Wang & Xiang Li & Yi-Qing Zhang & Yan Zhang & Kan Zhang, 2011. "Evolution of Scaling Emergence in Large-Scale Spatial Epidemic Spreading," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
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    Cited by:

    1. Qiang Yao & Chaojie Liu & Ju Sun, 2020. "Inequality in Health Services for Internal Migrants in China: A National Cross-Sectional Study on the Role of Fund Location of Social Health Insurance," IJERPH, MDPI, vol. 17(17), pages 1-22, August.
    2. Giulia Menculini & Francesco Bernardini & Luigi Attademo & Pierfrancesco Maria Balducci & Tiziana Sciarma & Patrizia Moretti & Alfonso Tortorella, 2021. "The Influence of the Urban Environment on Mental Health during the COVID-19 Pandemic: Focus on Air Pollution and Migration—A Narrative Review," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
    3. Xiaoru Xie & Liman Huang & Jun (Justin) Li & Hong Zhu, 2020. "Generational Differences in Perceptions of Food Health/Risk and Attitudes toward Organic Food and Game Meat: The Case of the COVID-19 Crisis in China," IJERPH, MDPI, vol. 17(9), pages 1-17, April.
    4. Junjian Gu, 2020. "Risk Assessment on Continued Public Health Threats: Evidence from China’s Stock Market," IJERPH, MDPI, vol. 17(20), pages 1-30, October.
    5. Yanting Zheng & Jinyuan Huang & Qiuyue Yin, 2021. "What Are the Reasons for the Different COVID-19 Situations in Different Cities of China? A Study from the Perspective of Population Migration," IJERPH, MDPI, vol. 18(6), pages 1-16, March.

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