In-depth Correlation Analysis of SARS-CoV-2 Effective Reproduction Number and Mobility Patterns: Three Groups of Countries
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Objectives: Many governments have imposed—and are still imposing—mobility restrictions to contain the coronavirus disease 2019 (COVID-19) pandemic. However, there is no consensus on whether policy-induced reductions of human mobility effectively reduce the effective reproduction number (Rt) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several studies based on country-restricted data reported conflicting trends in the change of the SARS-CoV-2 Rt following mobility restrictions. The objective of this study was to examine, at the global scale, the existence of regional specificities in the correlations between Rt and human mobility. Methods: We computed the Rt of SARS-CoV-2 using data on worldwide infection cases reported by the Johns Hopkins University, and analyzed the correlation between Rt and mobility indicators from the Google COVID-19 Community Mobility Reports in 125 countries, as well as states/regions within the United States, using the Pearson correlation test, linear modeling, and quadratic modeling. Results: The correlation analysis identified countries where Rt negatively correlated with residential mobility, as expected by policymakers, but also countries where Rt positively correlated with residential mobility and countries with more complex correlation patterns. The correlations between Rt and residential mobility were non-linear in many countries, indicating an optimal level above which increasing residential mobility is counterproductive. Conclusions: Our results indicate that, in order to effectively reduce viral circulation, mobility restriction measures must be tailored by region, considering local cultural determinants and social behaviors. We believe that our results have the potential to guide differential refinement of mobility restriction policies at a country/regional resolution.
Abstract
Objectives: Many governments have imposed—and are still imposing—mobility restrictions to contain the coronavirus disease 2019 (COVID-19) pandemic. However, there is no consensus on whether policy-induced reductions of human mobility effectively reduce the effective reproduction number (Rt) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several studies based on country-restricted data reported conflicting trends in the change of the SARS-CoV-2 Rt following mobility restrictions. The objective of this study was to examine, at the global scale, the existence of regional specificities in the correlations between Rt and human mobility. Methods: We computed the Rt of SARS-CoV-2 using data on worldwide infection cases reported by the Johns Hopkins University, and analyzed the correlation between Rt and mobility indicators from the Google COVID-19 Community Mobility Reports in 125 countries, as well as states/regions within the United States, using the Pearson correlation test, linear modeling, and quadratic modeling. Results: The correlation analysis identified countries where Rt negatively correlated with residential mobility, as expected by policymakers, but also countries where Rt positively correlated with residential mobility and countries with more complex correlation patterns. The correlations between Rt and residential mobility were non-linear in many countries, indicating an optimal level above which increasing residential mobility is counterproductive. Conclusions: Our results indicate that, in order to effectively reduce viral circulation, mobility restriction measures must be tailored by region, considering local cultural determinants and social behaviors. We believe that our results have the potential to guide differential refinement of mobility restriction policies at a country/regional resolution.
참고문헌 (22)
- Dong E, "An interactive web-based dashboard to track COVID-19 in real time", Lancet Infect Dis, 20(5), pp.533~534 (2020)
- "COVID-19 community mobility report" (2020)[URL]
- Kuniya T, "Evaluation of the effect of the state of emergency for the first wave of COVID-19 in Japan", Infect Dis Model, 5, pp.580~587 (2020)
- Cauchemez S, "Real-time estimates in early detection of SARS", Emerg Infect Dis, 12(1), pp.110~113 (2006)
- Anderson RM, "Population biology of infectious diseases : part I", Nature, 280(5721), pp.361~367 (1979)
- Gostic KM, "Practical considerations for measuring the effective reproductive number, Rt", PLoS Comput Biol, 16(12), pp.e1008409~ (2020)
- Hasan Durmuş, "The Effectiveness of Community-based Social Distancing for Mitigating the Spread of the COVID-19 Pandemic in Turkey", 예방의학회지, 53(6), pp.397~404 (2020), 대한예방의학회[DOI]
- Noland RB, "Mobility and the effective reproduction rate of COVID-19", J Transp Health, 20, pp.101016~ (2021)
- Dainton C, "Quantifying the relationship between lockdowns, mobility, and effective reproduction number (Rt) during the COVID-19 pandemic in the Greater Toronto Area", BMC Public Health, 21(1), pp.1658~ (2021)
- Ryu S, "Transmission dynamics and control of two epidemic waves of SARS-CoV-2 in South Korea", BMC Infect Dis, 21(1), pp.485~ (2021)
- Wang S, "Examining the change of human mobility adherent to social restriction policies and its effect on COVID-19 cases in Australia", Int J Environ Res Public Health, 17(21), pp.7930~ (2020)
- Linka K, "The reproduction number of COVID-19 and its correlation with public health interventions", Comput Mech, 66(4), pp.1035~1050 (2020)
- Oh J, "Mobility restrictions were associated with reductions in COVID-19 incidence early in the pandemic : evidence from a real-time evaluation in 34 countries", Sci Rep, 11(1), pp.13717~ (2021)
- "Google COVID-19 community mobility reports: anonymization process description (version 1.1)" (2020)[URL]
- "EpiEstim: estimate time varying reproduction numbers from epidemic curve" (2020)[URL]
- Zhang T, "Estimation of incubation period and serial interval for SARS-CoV-2 in Jiangxi, China, and an updated meta-analysis", J Infect Dev Ctries, 15(3), pp.326~332 (2021)
- Lipsitch M, "Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China", JAMA (2020)[DOI]
- Durbin J, "Testing for serial correlation in least squares regression: I", Biometrika, 37(3, pp.4) (1950), 409~428
- Durbin J, "Testing for serial correlation in least squares regression. II", Biometrika, 38(1-2), pp.159~178 (1951)
- Cochrane D, "Application of least squares regression to relationships containing auto-correlated error terms", J Am Stat Assoc, 44(245), pp.32~61 (1949)
- Sorokowska A, "Preferred interpersonal distances : a global comparison", J Cross Cult Psychol, 48(4), pp.577~592 (2017)
- Lim JS, "Temporal changes in the risk of superspreading events of coronavirus disease 2019", Open Forum Infect Dis, 8(7), pp.ofab350~ (2019)[DOI]