Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries

Nazrul Islam, Stephen J Sharp, Gerardo Chowell, Sharmin Shabnam, Ichiro Kawachi, Ben Lacey, Joseph M Massaro, Ralph B D'Agostino Sr, Martin White, Nazrul Islam, Stephen J Sharp, Gerardo Chowell, Sharmin Shabnam, Ichiro Kawachi, Ben Lacey, Joseph M Massaro, Ralph B D'Agostino Sr, Martin White

Abstract

Objective: To evaluate the association between physical distancing interventions and incidence of coronavirus disease 2019 (covid-19) globally.

Design: Natural experiment using interrupted time series analysis, with results synthesised using meta-analysis.

Setting: 149 countries or regions, with data on daily reported cases of covid-19 from the European Centre for Disease Prevention and Control and data on the physical distancing policies from the Oxford covid-19 Government Response Tracker.

Participants: Individual countries or regions that implemented one of the five physical distancing interventions (closures of schools, workplaces, and public transport, restrictions on mass gatherings and public events, and restrictions on movement (lockdowns)) between 1 January and 30 May 2020.

Main outcome measure: Incidence rate ratios (IRRs) of covid-19 before and after implementation of physical distancing interventions, estimated using data to 30 May 2020 or 30 days post-intervention, whichever occurred first. IRRs were synthesised across countries using random effects meta-analysis.

Results: On average, implementation of any physical distancing intervention was associated with an overall reduction in covid-19 incidence of 13% (IRR 0.87, 95% confidence interval 0.85 to 0.89; n=149 countries). Closure of public transport was not associated with any additional reduction in covid-19 incidence when the other four physical distancing interventions were in place (pooled IRR with and without public transport closure was 0.85, 0.82 to 0.88; n=72, and 0.87, 0.84 to 0.91; n=32, respectively). Data from 11 countries also suggested similar overall effectiveness (pooled IRR 0.85, 0.81 to 0.89) when school closures, workplace closures, and restrictions on mass gatherings were in place. In terms of sequence of interventions, earlier implementation of lockdown was associated with a larger reduction in covid-19 incidence (pooled IRR 0.86, 0.84 to 0.89; n=105) compared with a delayed implementation of lockdown after other physical distancing interventions were in place (pooled IRR 0.90, 0.87 to 0.94; n=41).

Conclusions: Physical distancing interventions were associated with reductions in the incidence of covid-19 globally. No evidence was found of an additional effect of public transport closure when the other four physical distancing measures were in place. Earlier implementation of lockdown was associated with a larger reduction in the incidence of covid-19. These findings might support policy decisions as countries prepare to impose or lift physical distancing measures in current or future epidemic waves.

Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: NI receives salary support from the Nuffield Department of Population Health, University of Oxford; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Fig 1
Fig 1
Physical distancing policies implemented by countries globally. Country codes used are based on the Alpha-3 codes by International Organization for Standardization (see appendix, pp4-5)
Fig 2
Fig 2
Pairwise meta-analysis on the association between physical distancing interventions and change in incidence of coronavirus disease 2019. Effects are reported as incidence rate ratios (95% confidence intervals). I2=an estimate of the percentage of total variation across the countries that is due to heterogeneity rather than chance. Country codes used are based on the Alpha-3 codes by International Organization for Standardization (see appendix, pp4-5)
Fig 3
Fig 3
Association between the combinations of physical distancing interventions and change in incidence of coronavirus disease 2019. I2=an estimate of the percentage of total variation across the countries that is due to heterogeneity rather than chance
Fig 4
Fig 4
Association between the sequence of physical distancing interventions and change in incidence of coronavirus disease 2019. I2=an estimate of the percentage of total variation across the countries that is due to heterogeneity rather than chance

References

    1. Mossong J, Hens N, Jit M, et al. Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med 2008;5:e74. 10.1371/journal.pmed.0050074.
    1. Ferguson NM, Laydon D, Nedjati-Gilani G, et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College London, 2020.
    1. Koo JR, Cook AR, Park M, et al. Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study. Lancet Infect Dis 2020;20:678-88. 10.1016/S1473-3099(20)30162-6.
    1. Prem K, Liu Y, Russell TW, et al. Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health 2020;5:e261-70. 10.1016/S2468-2667(20)30073-6.
    1. Lewnard JA, Lo NC. Scientific and ethical basis for social-distancing interventions against COVID-19. Lancet Infect Dis 2020;20:631-3. 10.1016/S1473-3099(20)30190-0.
    1. Nussbaumer-Streit B, Mayr V, Dobrescu AI, et al. Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review. Cochrane Database Syst Rev 2020;4:CD013574. 10.1002/14651858.CD013574.
    1. Pandemic Influenza Preparedness Team Scientific summary of pandemic influenza & its mitigation: scientific evidence base review. Department of Health, 2011.
    1. Pan A, Liu L, Wang C, et al. Association of public health interventions with the epidemiology of the covid-19 outbreak in Wuhan, China. JAMA 2020;10. 10.1001/jama.2020.6130.
    1. Cowling BJ, Ali ST, Ng TWY, et al. Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study. Lancet Public Health 2020;5:e279-88. 10.1016/S2468-2667(20)30090-6.
    1. Hale T, Petherick A, Phillips T, et al. Variation in government responses to COVID-19. Blavatnik School of Government, 2020.
    1. European Centre for Disease Prevention and Control. Geographic distribution of COVID-19 cases worldwide. 2020.
    1. World Bank. World population prospects: 2019 revision. 2020.
    1. International Monetary Fund. IMF data mapper. 2020.
    1. Johns Hopkins Center for Health Security, The Economist Intelligence Unit. Global Health Security Index. 2019.
    1. Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 2017;46:348-55. 10.1093/ije/dyw098.
    1. Lauer SA, Grantz KH, Bi Q, et al. The incubation period of coronavirus disease 2019 (covid-19) from publicly reported confirmed cases: estimation and application. Ann Intern Med 2020;172:577-82. 10.7326/M20-0504.
    1. de Figueiredo AM, Codina AD, Figueiredo D, et al. Impact of lockdown on COVID-19 incidence and mortality in China: an interrupted time series study. Bull World Health Organ 2020. 10.2471/BLT.20.256701.
    1. Rabe-Hesketh S, Everitt B. A handbook of statistical analyses using Stata. 4th ed Chapman & Hall/CRC, 2007.
    1. McCullagh P, Nelder JA. Generalized linear models. 2nd ed Chapman & Hall/CRC, 1998.
    1. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177-88. 10.1016/0197-2456(86)90046-2.
    1. Platt L, Ross W. Are some ethnic groups more vulnerable to COVID-19 than others? Institute for Fiscal Studies, 2020.
    1. Garg S, Kim L, Whitaker M, et al. Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed coronavirus disease 2019 — covid-NET, 14 states, March 1-30, 2020. MMWR Morb Mortal Wkly Rep 2020;69:458-64. 10.15585/mmwr.mm6915e3.
    1. Docherty AB, Harrison EM, Green CA, et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BMJ 2020;369:m1985 10.1136/bmj.m1985.
    1. StataCorp. Stata statistical software: release 14. 2015.
    1. Python Software Foundation. Python Language Reference, version 2.7. Available at
    1. Tobías A. Evaluation of the lockdowns for the SARS-CoV-2 epidemic in Italy and Spain after one month follow up. Sci Total Environ 2020;725:138539. 10.1016/j.scitotenv.2020.138539.
    1. Markel H, Lipman HB, Navarro JA, et al. Nonpharmaceutical interventions implemented by US cities during the 1918-1919 influenza pandemic. JAMA 2007;298:644-54. 10.1001/jama.298.6.644.
    1. Correia S, Luck S, Verner E. Pandemics depress the economy, public health interventions do not: evidence from the 1918 flu. Social Science Research Network, 2020, 10.2139/ssrn.3561560.
    1. Viner RM, Russell SJ, Croker H, et al. School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review. Lancet Child Adolesc Health 2020;4:397-404. 10.1016/S2352-4642(20)30095-X.
    1. Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? Lancet 2020;395:1225-8. 10.1016/S0140-6736(20)30627-9.
    1. Legido-Quigley H, Asgari N, Teo YY, et al. Are high-performing health systems resilient against the COVID-19 epidemic? Lancet 2020;395:848-50. 10.1016/S0140-6736(20)30551-1.
    1. Ranney ML, Griffeth V, Jha AK. Critical supply shortages — the need for ventilators and personal protective equipment during the covid-19 pandemic. N Engl J Med 2020;382:e41. 10.1056/NEJMp2006141.
    1. Leung NHL, Chu DKW, Shiu EYC, et al. Respiratory virus shedding in exhaled breath and efficacy of face masks [correction in: Nat Med 2020;26:981]. Nat Med 2020;26:676-80. 10.1038/s41591-020-0843-2.
    1. Leung CC, Lam TH, Cheng KK. Mass masking in the COVID-19 epidemic: people need guidance. Lancet 2020;395:945. 10.1016/S0140-6736(20)30520-1.
    1. Chu DK, Akl EA, Duda S, Solo K, Yaacoub S, Schünemann HJ, COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet 2020;395:1973-87. 10.1016/S0140-6736(20)31142-9.
    1. Tian H, Liu Y, Li Y, et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 2020;368:638-42. 10.1126/science.abb6105.
    1. Buckee CO, Balsari S, Chan J, et al. Aggregated mobility data could help fight COVID-19. Science 2020;368:145-6. 10.1126/science.abb8021.
    1. BioRISC. Informing management of lockdowns and a phased return to normality: a Solution Scan of non-pharmaceutical options to reduce SARS-CoV-2 transmission. 2020.
    1. Ing E, Xu AQ, Salimi A. Physician deaths from corona virus disease (covid-19). Social Science Research Network, 2020. 10.2139/ssrn.3566141.
    1. Kupferschmidt K. Ending coronavirus lockdowns will be a dangerous process of trial and error. Science 2020;14 10.1126/science.abc2507.
    1. Leung K, Wu JT, Liu D, Leung GM. First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment. Lancet 2020;395:1382-93. 10.1016/S0140-6736(20)30746-7.
    1. Xu S, Li Y. Beware of the second wave of COVID-19. Lancet 2020;395:1321-2. 10.1016/S0140-6736(20)30845-X.
    1. Razai MS, Oakeshott P, Kankam H, Galea S, Stokes-Lampard H. Mitigating the psychological effects of social isolation during the covid-19 pandemic. BMJ 2020;369:m1904. 10.1136/bmj.m1904.
    1. Venkatesh A, Edirappuli S. Social distancing in covid-19: what are the mental health implications? BMJ 2020;369:m1379. 10.1136/bmj.m1379.
    1. Gray NA, Back AL. Covid-19 communication aids. BMJ 2020;369:m2255. 10.1136/bmj.m2255.

Source: PubMed

3
Abonneren