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Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia

Author

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  • Siqin Wang

    (School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia)

  • Yan Liu

    (School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia)

  • Tao Hu

    (Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA)

Abstract

The policy induced decline of human mobility has been recognised as effective in controlling the spread of COVID-19, especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling the data of confirmed COVID-19 cases with the Google mobility data in Australia, we present a state-level empirical study to: (1) inspect the temporal variation of the COVID-19 spread and the change of human mobility adherent to social restriction policies; (2) examine the extent to which different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and (3) analyse the time lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time lag effect on the growth rates of COVID-19, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between human mobility and COVID-19 spread varies across space and time and is subject to the types of mobility. Thus, it is important for government to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.

Suggested Citation

  • Siqin Wang & Yan Liu & Tao Hu, 2020. "Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia," IJERPH, MDPI, vol. 17(21), pages 1-17, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:21:p:7930-:d:436588
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    References listed on IDEAS

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    1. Prentice, Catherine & Chen, Jinyan & Stantic, Bela, 2020. "Timed intervention in COVID-19 and panic buying," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    2. Sumedha Gupta & Thuy D. Nguyen & Felipe Lozano Rojas & Shyam Raman & Byungkyu Lee & Ana Bento & Kosali I. Simon & Coady Wing, 2020. "Tracking Public and Private Responses to the COVID-19 Epidemic: Evidence from State and Local Government Actions," NBER Working Papers 27027, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Tao Hu & Han Yue & Changzhen Wang & Bing She & Xinyue Ye & Regina Liu & Xinyan Zhu & Weihe Wendy Guan & Shuming Bao, 2020. "Racial Segregation, Testing Site Access, and COVID-19 Incidence Rate in Massachusetts, USA," IJERPH, MDPI, vol. 17(24), pages 1-18, December.
    2. Artur Strzelecki & Ana Azevedo & Mariia Rizun & Paulina Rutecka & Kacper Zagała & Karina Cicha & Alexandra Albuquerque, 2022. "Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal," IJERPH, MDPI, vol. 19(21), pages 1-25, November.

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