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Geographic pattern of human mobility and COVID-19 before and after Hubei lockdown

  • T. Edwin Chow*
  • , Yusik Choi
  • , Mei Yang
  • , David Mills
  • , Ricci Yue
  • *Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    70 Downloads (CityUHK Scholars)

    Abstract

    This research investigates how travel restrictions affect the spatiotemporal pattern of human mobility and COVID-19 confirmed cases. Based on recorded movement and Baidu mobility index, in- and out-migration were estimated to examine the geographic pattern of human mobility across many Chinese cities from Jan 1–Feb 11 of 2020. In addition to the baseline model of city lockdown, this study also explored the time lag effect of COVID-19 incubation period before/after Jan 28 (i.e. 5 days) and Feb 6 (i.e. 2 weeks) as well. Full factorial Analysis of Variance (ANOVA) tests reviewed significant differences of migration pattern by lockdown and origin/destination, which are also significantly associated with the confirmed cases of COVID-19 as well. Specifically, human mobility dropped proportionally after the lockdown regardless of origin location, but Hubei destination was significantly lower than non-Hubei destination. The model assuming an incubation period of 5 days differentiated the differences of COVID-19 cases better than the baseline and 14 days model. Spatiotemporal cluster analysis identified multiple space-time windows that were related to migration trajectory assuming a 5–14 days incubation period. The pre-lockdown clusters due to traveler’s outflow from Wuhan to those megacities were the pathways for international transmission of COVID-19, whereas the post-lockdown clusters were partially related to the migration pattern especially within the eastern part of Hubei around Wuhan. The geographic pattern revealed from this study confirmed the presence of super spreaders that were responsible for regional spreading at the early stage and caused local outbreaks in the latter stage.
    Original languageEnglish
    Pages (from-to)127-138
    Number of pages13
    JournalAnnals of GIS
    Volume27
    Issue number2
    Online published11 Nov 2020
    DOIs
    Publication statusPublished - 2021

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Research Keywords

    • migration
    • non-pharmaceutical intervention
    • spatiotemporal cluster analysis
    • travel pattern
    • Wuhan lockdown

    Publisher's Copyright Statement

    • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

    Policy Impact

    • Cited in Policy Documents

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