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

BMJ 2020; 370 doi: (Published 15 July 2020) Cite this as: BMJ 2020;370:m2743

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  1. Nazrul Islam, research fellow1 2,
  2. Stephen J Sharp, senior statistician2,
  3. Gerardo Chowell, professor of mathematical epidemiology3,
  4. Sharmin Shabnam, doctoral candidate4,
  5. Ichiro Kawachi, professor of social epidemiology5,
  6. Ben Lacey, senior clinical research fellow1,
  7. Joseph M Massaro, professor of biostatistics, mathematics, and statistics6,
  8. Ralph B D’Agostino Sr, professor of mathematics and statistics7,
  9. Martin White, professor of population health research2
  1. 1Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford OX3 7LF, UK
  2. 2MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
  3. 3Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA
  4. 4Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, USA
  5. 5Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA
  6. 6Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
  7. 7Department of Mathematics and Statistics, Boston University, Boston, MA, USA
  1. Correspondence to: N Islam nazrul.islam{at}
  • Accepted 8 July 2020


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.


  • Contributors: NI and MW conceptualised the study with input from the co-authors. NI, SJS, and SS did the statistical analysis, with mathematical and statistical inputs and oversight from MW, JMM, and RBD. All authors are guarantors for the study. All authors revised the manuscript, provided critical scholarly feedback, and approved the final version of the manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

  • Funding: NI receives salary support from the Nuffield Department of Population Health, University of Oxford. Employers/sponsors had no role in the design, analysis, or dissemination of the study. The views expressed in this article are those of the authors and not necessarily those of the entities the authors are affiliated with or supported by, or both.

  • Competing interests: All authors have completed the ICMJE uniform disclosure form at 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.

  • Ethical approval: Not required as data are anonymised, aggregated without any personal information, and publicly available.

  • Data sharing: All the data used in this study are publicly available and properly cited. However, all the data used in this study will be made publicly available on the GitHub repository ( upon publication of the study.

  • The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

  • Dissemination to participants and related patient and public communities: We will widely disseminate the main findings to members of the public through official (press release, institutional websites, and repositories), personal, and social media.

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