Social distancing to slow the US COVID-19 epidemic: Longitudinal pretest–posttest comparison group study

Autoři: Mark J. Siedner aff001;  Guy Harling aff003;  Zahra Reynolds aff001;  Rebecca F. Gilbert aff001;  Sebastien Haneuse aff008;  Atheendar S. Venkataramani aff009;  Alexander C. Tsai aff001
Působiště autorů: Massachusetts General Hospital, Boston, Massachusetts, United States of America aff001;  Harvard Medical School, Boston, Massachusetts, United States of America aff002;  Africa Health Research Institute, KwaZulu-Natal, South Africa aff003;  University College London, London, United Kingdom aff004;  MRC/Wits Agincourt Unit, Rural Public Health and Health Transitions Research Unit, University of the Witwatersrand, Johannesburg, South Africa aff005;  Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America aff006;  Harvard Center for Population and Development Studies, Cambridge, Massachusetts, United States of America aff007;  Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America aff008;  Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America aff009;  Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America aff010
Vyšlo v časopise: Social distancing to slow the US COVID-19 epidemic: Longitudinal pretest–posttest comparison group study. PLoS Med 17(8): e1003244. doi:10.1371/journal.pmed.1003244
Kategorie: Research Article



Social distancing measures to address the US coronavirus disease 2019 (COVID-19) epidemic may have notable health and social impacts.

Methods and findings

We conducted a longitudinal pretest–posttest comparison group study to estimate the change in COVID-19 case growth before versus after implementation of statewide social distancing measures in the US. The primary exposure was time before (14 days prior to, and through 3 days after) versus after (beginning 4 days after, to up to 21 days after) implementation of the first statewide social distancing measures. Statewide restrictions on internal movement were examined as a secondary exposure. The primary outcome was the COVID-19 case growth rate. The secondary outcome was the COVID-19-attributed mortality growth rate. All states initiated social distancing measures between March 10 and March 25, 2020. The mean daily COVID-19 case growth rate decreased beginning 4 days after implementation of the first statewide social distancing measures, by 0.9% per day (95% CI −1.4% to −0.4%; P < 0.001). We did not observe a statistically significant difference in the mean daily case growth rate before versus after implementation of statewide restrictions on internal movement (0.1% per day; 95% CI −0.04% to 0.3%; P = 0.14), but there is substantial difficulty in disentangling the unique associations with statewide restrictions on internal movement from the unique associations with the first social distancing measures. Beginning 7 days after social distancing, the COVID-19-attributed mortality growth rate decreased by 2.0% per day (95% CI −3.0% to −0.9%; P < 0.001). Our analysis is susceptible to potential bias resulting from the aggregate nature of the ecological data, potential confounding by contemporaneous changes (e.g., increases in testing), and potential underestimation of social distancing due to spillover effects from neighboring states.


Statewide social distancing measures were associated with a decrease in the COVID-19 case growth rate that was statistically significant. Statewide social distancing measures were also associated with a decrease in the COVID-19-attributed mortality growth rate beginning 7 days after implementation, although this decrease was no longer statistically significant by 10 days.

Klíčová slova:

COVID 19 – Death rates – SARS – Social epidemiology – Socioeconomic aspects of health – United States – Virus testing – Social distancing


1. Kissler SM, Tedijanto C, Goldstein E, Grad YH, Lipsitch M. Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science. 2020;368(6493):860–8. doi: 10.1126/science.abb5793 32291278

2. Markel H, Lipman HB, Navarro JA, Sloan A, Michalsen JR, Stern AM, et al. Nonpharmaceutical interventions implemented by US cities during the 1918–1919 influenza pandemic. JAMA. 2007;298(6):644–54. doi: 10.1001/jama.298.6.644 17684187

3. Bootsma MC, Ferguson NM. The effect of public health measures on the 1918 influenza pandemic in U.S. cities. Proc Natl Acad Sci U S A. 2007;104(18):7588–93. doi: 10.1073/pnas.0611071104 17416677

4. Ferguson NM, Cummings DA, Cauchemez S, Fraser C, Riley S, Meeyai A, et al. Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature. 2005;437(7056):209–14. doi: 10.1038/nature04017 16079797

5. Taubenberger JK, Morens DM. 1918 influenza: the mother of all pandemics. Emerg Infect Dis. 2006;12(1):15–22. doi: 10.3201/eid1201.050979 16494711

6. Teslya A, Pham TM, Godijk NG, Kretzschmar ME, Bootsma MCJ, Rozhnova G. Impact of self-imposed prevention measures and short-term government-imposed social distancing on mitigating and delaying a COVID-19 epidemic: a modelling study. PLoS Med 17(7): e1003166. doi: 10.1371/journal.pmed.1003166

7. Andersen M. Early evidence on social distancing in response to COVID-19 in the United States. SSRN Working Paper No. 3569368 [preprint]. Amsterdam: Elsevier; 2020 [cited 2020 Jun 2]. Available from:

8. Abouk R, Heydari B. The immediate effect of COVID-19 policies on social distancing behavior in the United States. medRxiv [preprint]. 2020 Apr 28. doi: 10.1101/2020.04.07.20057356

9. Courtemanche C, Garuccio J, Le A, Pinkston J, Yelowitz A. Strong social distancing measures in the United States reduced the COVID-19 growth rate. Health Aff (Millwood). 2020 May 14. doi: 10.1377/hlthaff.2020.00608 32407171

10. Dave DM, Friedson AI, Matsuzawa K, Sabia JJ. When do shelter-in-place orders fight COVID-19 best? Policy heterogeneity across states and adoption time. NBER Working Paper No. 27091 [preprint]. Cambridge: National Bureau of Economic Research; 2020 [cited 2020 Jun 2]. Available from:

11. Hsiang S, Allen D, Annan-Phan S, Bell K, Bolliger I, Chong T, et al. The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Nature. 2020 Jun 8. doi: 10.1038/s41586-020-2404-8 32512578

12. Bayham J, Fenichel EP. Impact of school closures for COVID-19 on the US health-care workforce and net mortality: a modelling study. Lancet Public Health. 2020;5(5):e271–78. doi: 10.1016/S2468-2667(20)30082-7 32251626

13. Eichenbaum MS, Rebelo S, Trabandt M. The macroeconomics of epidemics. NBER Working Paper No. 26882 [preprint]. Cambridge: National Bureau of Economic Research; 2020 [cited 2020 Jun 2]. Available from:

14. Petherick A, Hale T, Phillips T, Webster S. Variation in government responses to COVID-19. Blavatnik School Working Paper [preprint]. Oxford: University of Oxford Blavatnik School of Government; 2020 [cited 2020 Jun 2]. Available from:

15. Council of State and Territorial Epidemiologists. Standardized surveillance case definition and national notification for 2019 novel coronavirus disease (COVID-19). Washington (DC): Office of the Assistant Secretary for Preparedness and Response; 2020 [cited 2020 Jun 2]. Available from:

16. Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Ann Intern Med. 2020;172(9):577–82. doi: 10.7326/M20-0504 32150748

17. Backer JA, Klinkenberg D, Wallinga J. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020. Euro Surveill. 2020;25(5):2000062.

18. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708–20. doi: 10.1056/NEJMoa2002032 32109013

19. COVID-19 Surveillance Group. Characteristics of COVID-19 patients dying in Italy. Report based on available data on March 20th, 2020 [preprint]. Rome: Istituto Superiore di Sanità; 2020 [cited 2020 Apr 12]. Available from:

20. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054–62. doi: 10.1016/S0140-6736(20)30566-3 32171076

21. Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis. 2020;20(6):669–77. doi: 10.1016/S1473-3099(20)30243-7 32240634

22. Wu JT, Leung K, Bushman M, Kishore N, Niehus R, de Salazar PM, et al. Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China. Nat Med. 2020;26(4):506–10. doi: 10.1038/s41591-020-0822-7 32284616

23. Siedner MJ, Harling G, Reynolds Z, Gilbert RF, Venkataramani A, Tsai AC. Social distancing to slow the U.S. COVID-19 epidemic: an interrupted time-series analysis. medRxiv [preprint]. 2020 Apr 8. doi: 10.1101/2020.04.03.20052373

24. Lee VJ, Aguilera X, Heymann D, Wilder-Smith A, Lancet Infectious Diseases Commission. Preparedness for emerging epidemic threats: a Lancet Infectious Diseases Commission. Lancet Infect Dis. 2020;20(1):17–9. doi: 10.1016/S1473-3099(19)30674-7 31876487

25. Grassly NC, Fraser C. Mathematical models of infectious disease transmission. Nature Rev Microbiol. 2008;6(6):477–87.

26. Lewis MD, Pavlin JA, Mansfield JL, O’Brien S, Boomsma LG, Elbert Y, et al. Disease outbreak detection system using syndromic data in the greater Washington DC area. Am J Prev Med. 2002;23(3):180–6. doi: 10.1016/s0749-3797(02)00490-7 12350450

27. Buckingham-Jeffery E, Morbey R, House T, Elliot AJ, Harcourt S, Smith GE. Correcting for day of the week and public holiday effects: improving a national daily syndromic surveillance service for detecting public health threats. BMC Public Health. 2017;17(1):477. doi: 10.1186/s12889-017-4372-y 28525991

28. Hatchett RJ, Mecher CE, Lipsitch M. Public health interventions and epidemic intensity during the 1918 influenza pandemic. Proc Natl Acad Sci U S A. 2007;104(18):7582–7. doi: 10.1073/pnas.0610941104 17416679

29. Sullivan D, von Wachter T. Job displacement and mortality: an analysis using administrative data. Q J Econ. 2009;124(3):1265–306.

30. Jacobson L, LaLonde RJ, Sullivan DG. Earnings losses of displaced workers. Am Econ Rev. 1993;83(4):685–709.

31. Goodman-Bacon A. Difference-in-differences with variation in treatment timing. NBER Working Paper No. 25018 [preprint]. Cambridge: National Bureau of Economic Research; 2018 [cited 2020 Jun 2]. Available from:

32. Bertrand M, Duflo E, Mullainathan S. How much should we trust differences-in-differences estimates? Q J Econ. 2004;119(1):249–75.

33. Brzezinski A, Deiana G, Kecht V, Van Dijcke D. The COVID-19 pandemic: government versus community action across the United States. COVID Econ. 2020;7:115–156. Available from:

34. Weinberger DM, Chen J, Cohen T, Crawford FW, Mostashari F, Olson D, et al. Estimation of excess deaths associated with the COVID-19 pandemic in the United States, March to May 2020. JAMA Intern Med. 2020 Jul 1. doi: 10.1001/jamainternmed.2020.3391 32609310

35. Rivera R, Rosenbaum J, Quispe W. Excess mortality in the United States during the peak of the COVID-19 pandemic. medRxiv [preprint]. 2020 Jun 27. doi: 10.1101/2020.05.04.20090324

36. Lu FS, Nguyen AT, Link N, Santillana M. Estimating the prevalence of COVID-19 in the United States: three complementary approaches. medRxiv [preprint]. 2020 Jun 18. doi: 10.1101/2020.04.18.20070821 32587997

37. Cowling BJ, Ali ST, Ng TWY, Tsang TK, Li JCM, Fong MW, 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(5):e279–88. doi: 10.1016/S2468-2667(20)30090-6 32311320

38. Lewnard JA, Liu VX, Jackson ML, Schmidt MA, Jewell BL, Flores JP, et al. Incidence, clinical outcomes, and transmission dynamics of severe coronavirus disease 2019 in California and Washington: prospective cohort study. BMJ. 2020;369:m1923. doi: 10.1136/bmj.m1923 32444358

39. Case A, Deaton A. Deaths of despair and the future of capitalism. Princeton: Princeton University Press; 2020.

40. Venkataramani AS, Bair EF, O’Brien RL, Tsai AC. Association between automotive assembly plant closures and opioid overdose mortality in the United States: a difference-in-differences analysis. JAMA Intern Med. 2020;180(2):254–62.

41. Muennig PA, Reynolds M, Fink DS, Zafari Z, Geronimus AT. America’s declining well-being, health, and life expectancy: not just a white problem. Am J Public Health. 2018;108(12):1626–31. doi: 10.2105/AJPH.2018.304585 30252522

42. Chin T, Kahn R, Li R, Chen JT, Krieger N, Buckee CO, et al. U.S. county-level characteristics to inform equitable COVID-19 response. medRxiv [preprint]. 2020 Apr 11. doi: 10.1101/2020.04.08.20058248 32511610

43. Unequal protection: American inequality meets covid-19. The Economist. 2020 Apr 18.

44. Fritze J. Authority to reopen U.S. for business in question. USA Today. 2020 Apr 14.

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