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Impact of the COVID-19 Epidemic on Population Mobility Networks in the Beijing–Tianjin–Hebei Urban Agglomeration from a Resilience Perspective

Author

Listed:
  • Xufang Mu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Chuanglin Fang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhiqi Yang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xiaomin Guo

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

As an important symbol and carrier of regional social and economic activities, population mobility is a vital force to promote the re-agglomeration and diffusion of social and economic factors. An accurate and timely grasp on the impact of the COVID-19 epidemic on population mobility between cities is of great significance for promoting epidemic prevention and control and economic and social development. This study proposes a theoretical framework for resilience assessment, using centrality and nodality, hierarchy and matching, cluster, transmission, and diversity to measure the impact of the COVID-19 epidemic on population mobility in the Beijing–Tianjin–Hebei (BTH) urban agglomeration in 2020–2022, based on the migration data of AutoNavi and social network analysis. The results show that the COVID-19 epidemic had different impacts on the population network resilience of the BTH urban agglomeration based on the scale and timing. During the full-scale outbreak of the epidemic, strict epidemic prevention and control measures were introduced. The measures, such as social distancing and city and road closure, significantly reduced population mobility in the BTH urban agglomeration, and population mobility between cities decreased sharply. The population mobility network’s cluster, transmission, and diversity decreased significantly, severely testing the network resilience. Due to the refinement of the epidemic control measures over time, when a single urban node was impacted, the urban node did not completely fail, and consequently it had little impact on the overall cluster, transmission, and diversity of the population mobility network. Urban nodes at different levels of the population mobility network were not equally affected by the COVID-19 epidemic. The findings can make references for the coordination of epidemic control measures and urban development. It also provides a new perspective for the study of network resilience, and provides scientific data support and a theoretical basis for improving the resilience of BTH urban agglomeration and promoting collaborative development.

Suggested Citation

  • Xufang Mu & Chuanglin Fang & Zhiqi Yang & Xiaomin Guo, 2022. "Impact of the COVID-19 Epidemic on Population Mobility Networks in the Beijing–Tianjin–Hebei Urban Agglomeration from a Resilience Perspective," Land, MDPI, vol. 11(5), pages 1-23, May.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:5:p:675-:d:807512
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    References listed on IDEAS

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    1. Wenwen Xu & Chunrui Song & Dongqi Sun & Baochu Yu, 2021. "Spatiotemporal Differentiation of the School-Age Migrant Population in Liaoning Province, China, and Its Driving Factors," Land, MDPI, vol. 10(10), pages 1-13, October.
    2. Sheng Wei & Lei Wang, 2020. "Examining the population flow network in China and its implications for epidemic control based on Baidu migration data," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-10, December.
    3. Honghu Sun & Xianfu Cheng & Mengqin Dai, 2016. "Regional flood disaster resilience evaluation based on analytic network process: a case study of the Chaohu Lake Basin, Anhui Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 39-58, May.
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    Cited by:

    1. Junuo Zhou & Lin Yang, 2022. "Network-Based Research on Organizational Resilience in Wuhan Thunder God Mountain Hospital Project during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(16), pages 1-23, August.

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