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Prediction of Epidemic Spread of the 2019 Novel Coronavirus Driven by Spring Festival Transportation in China: A Population-Based Study

Author

Listed:
  • Changyu Fan

    (School of Sociology, Central China Normal University, Wuhan 430079, Hubei Province, China)

  • Linping Liu

    (School of Public Administration, Hangzhou Normal University, Hangzhou 311121, Zhejiang Province, China
    School of Social and Behavioral Sciences, Nanjing University, Nanjing 210046, Jiangsu Province, China)

  • Wei Guo

    (School of Social and Behavioral Sciences, Nanjing University, Nanjing 210046, Jiangsu Province, China)

  • Anuo Yang

    (School of Social and Behavioral Sciences, Nanjing University, Nanjing 210046, Jiangsu Province, China)

  • Chenchen Ye

    (School of Social and Behavioral Sciences, Nanjing University, Nanjing 210046, Jiangsu Province, China)

  • Maitixirepu Jilili

    (School of Social and Behavioral Sciences, Nanjing University, Nanjing 210046, Jiangsu Province, China)

  • Meina Ren

    (School of Social and Behavioral Sciences, Nanjing University, Nanjing 210046, Jiangsu Province, China)

  • Peng Xu

    (School of Sociology, Wuhan University, Wuhan 430072, Hubei Province, China)

  • Hexing Long

    (School of Economics, Minzu University of China, Beijing 100081, China)

  • Yufan Wang

    (School of Sociology, Central China Normal University, Wuhan 430079, Hubei Province, China)

Abstract

After the 2019 novel coronavirus (2019-nCoV) outbreak, we estimated the distribution and scale of more than 5 million migrants residing in Wuhan after they returned to their hometown communities in Hubei Province or other provinces at the end of 2019 by using the data from the 2013–2018 China Migrants Dynamic Survey (CMDS). We found that the distribution of Wuhan’s migrants is centred in Hubei Province (approximately 75%) at a provincial level, gradually decreasing in the surrounding provinces in layers, with obvious spatial characteristics of circle layers and echelons. The scale of Wuhan’s migrants, whose origins in Hubei Province give rise to a gradient reduction from east to west within the province, and account for 66% of Wuhan’s total migrants, are from the surrounding prefectural-level cities of Wuhan. The distribution comprises 94 districts and counties in Hubei Province, and the cumulative percentage of the top 30 districts and counties exceeds 80%. Wuhan’s migrants have a large proportion of middle-aged and high-risk individuals. Their social characteristics include nuclear family migration (84%), migration with families of 3–4 members (71%), a rural household registration (85%), and working or doing business (84%) as the main reason for migration. Using a quasi-experimental analysis framework, we found that the size of Wuhan’s migrants was highly correlated with the daily number of confirmed cases. Furthermore, we compared the epidemic situation in different regions and found that the number of confirmed cases in some provinces and cities in Hubei Province may be underestimated, while the epidemic situation in some regions has increased rapidly. The results are conducive to monitoring the epidemic prevention and control in various regions.

Suggested Citation

  • Changyu Fan & Linping Liu & Wei Guo & Anuo Yang & Chenchen Ye & Maitixirepu Jilili & Meina Ren & Peng Xu & Hexing Long & Yufan Wang, 2020. "Prediction of Epidemic Spread of the 2019 Novel Coronavirus Driven by Spring Festival Transportation in China: A Population-Based Study," IJERPH, MDPI, vol. 17(5), pages 1-27, March.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:5:p:1679-:d:328489
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    Citations

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    Cited by:

    1. Chun Li & Jianhua He & Xingwu Duan, 2020. "The Relationship Exploration between Public Migration Attention and Population Migration from a Perspective of Search Query," IJERPH, MDPI, vol. 17(7), pages 1-18, April.
    2. Guixian Wu & Wenling Tian & Li Zhang & Haiyan Yang, 2022. "The Chinese Spring Festival Impact on Air Quality in China: A Critical Review," IJERPH, MDPI, vol. 19(15), pages 1-9, July.
    3. Hsiao-Yu Yang & Jason Kai Wei Lee, 2021. "The Impact of Temperature on the Risk of COVID-19: A Multinational Study," IJERPH, MDPI, vol. 18(8), pages 1-10, April.
    4. Changyu Fan & Min Li & Xueyan Li & Miao Zhu & Ping Fu, 2021. "Who Got Infected with COVID-19? A Study of College Students in Wuhan (China)," IJERPH, MDPI, vol. 18(5), pages 1-15, March.
    5. Ziheng Shangguan & Mark Yaolin Wang & Wen Sun, 2020. "What Caused the Outbreak of COVID-19 in China: From the Perspective of Crisis Management," IJERPH, MDPI, vol. 17(9), pages 1-16, May.
    6. Azzeddine Madani & Saad Eddine Boutebal & Christopher Robin Bryant, 2020. "The Psychological Impact of Confinement Linked to the Coronavirus Epidemic COVID-19 in Algeria," IJERPH, MDPI, vol. 17(10), pages 1-13, May.
    7. 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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