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The Impact of Policy Measures on Human Mobility, COVID-19 Cases, and Mortality in the US: A Spatiotemporal Perspective

Author

Listed:
  • Yun Li

    (Department of Geography and GeoInformation Science, George Mason University, Fairfax, VA 22030, USA
    NSF Spatiotemporal Innovation Center, George Mason University, Fairfax, VA 22030, USA)

  • Moming Li

    (Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA 94158, USA)

  • Megan Rice

    (Department of Chemistry, Carnegie Mellon University, Pittsburgh, PA 15213, USA)

  • Haoyuan Zhang

    (Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China)

  • Dexuan Sha

    (Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA 94158, USA)

  • Mei Li

    (Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China)

  • Yanfang Su

    (Department of Global Health, Washington University, Seattle, WA 98195, USA)

  • Chaowei Yang

    (Department of Geography and GeoInformation Science, George Mason University, Fairfax, VA 22030, USA
    NSF Spatiotemporal Innovation Center, George Mason University, Fairfax, VA 22030, USA)

Abstract

Social distancing policies have been regarded as effective in containing the rapid spread of COVID-19. However, there is a limited understanding of policy effectiveness from a spatiotemporal perspective. This study integrates geographical, demographical, and other key factors into a regression-based event study framework, to assess the effectiveness of seven major policies on human mobility and COVID-19 case growth rates, with a spatiotemporal emphasis. Our results demonstrate that stay-at-home orders, workplace closures, and public information campaigns were effective in decreasing the confirmed case growth rate. For stay-at-home orders and workplace closures, these changes were associated with significant decreases ( p < 0.05) in mobility. Public information campaigns did not see these same mobility trends, but the growth rate still decreased significantly in all analysis periods ( p < 0.01). Stay-at-home orders and international/national travel controls had limited mitigation effects on the death case growth rate ( p < 0.1). The relationships between policies, mobility, and epidemiological metrics allowed us to evaluate the effectiveness of each policy and gave us insight into the spatiotemporal patterns and mechanisms by which these measures work. Our analysis will provide policymakers with better knowledge regarding the effectiveness of measures in space–time disaggregation.

Suggested Citation

  • Yun Li & Moming Li & Megan Rice & Haoyuan Zhang & Dexuan Sha & Mei Li & Yanfang Su & Chaowei Yang, 2021. "The Impact of Policy Measures on Human Mobility, COVID-19 Cases, and Mortality in the US: A Spatiotemporal Perspective," IJERPH, MDPI, vol. 18(3), pages 1-23, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:996-:d:485674
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    References listed on IDEAS

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    Cited by:

    1. Melissa Silva & Iuria Betco & César Capinha & Rita Roquette & Cláudia M. Viana & Jorge Rocha, 2022. "Spatiotemporal Dynamics of COVID-19 Infections in Mainland Portugal," Sustainability, MDPI, vol. 14(16), pages 1-28, August.
    2. Joseph Zuccarelli & Laura Seaman & Kevin Rader, 2024. "Assessing the Impact of Non-Pharmaceutical Interventions on Consumer Mobility Patterns and COVID-19 Transmission in the US," IJERPH, MDPI, vol. 21(1), pages 1-16, January.
    3. Yun Li & Moming Li & Megan Rice & Yanfang Su & Chaowei Yang, 2021. "Phased Implementation of COVID-19 Vaccination: Rapid Assessment of Policy Adoption, Reach and Effectiveness to Protect the Most Vulnerable in the US," IJERPH, MDPI, vol. 18(14), pages 1-14, July.
    4. Bulut Boru & M. Emre Gursoy, 2022. "Forecasting Daily COVID-19 Case Counts Using Aggregate Mobility Statistics," Data, MDPI, vol. 7(11), pages 1-24, November.

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