Skip directly to site content Skip directly to page options Skip directly to A-Z link Skip directly to A-Z link Skip directly to A-Z link
Volume 26, Number 9—September 2020
Research Letter

Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China

Author affiliations: The University of Texas at Austin, Austin, Texas, USA (Z. Du, S.J. Fox, L.A. Meyers); Dalian Minzu University, Dalian, China (X. Xu); University of Cambridge, Cambridge, UK (L. Wang); The University of Hong Kong, Hong Kong, China (B.J. Cowling); Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, Connecticut, USA (A.P. Galvani); Santa Fe Institute, Santa Fe, New Mexico, USA (L.A. Meyers)

Cite This Article

Abstract

Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97–3.86) days.

On December 31, 2019, a cluster of atypical pneumonia in Wuhan, China, was reported to the regional office of the World Health Organization (WHO). Its etiology was later identified as the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus disease (COVID-19) spread rapidly across China and internationally (1); as of April 9, 2020, a total of 1,436,198 confirmed cases and 85,522 deaths had been reported in 209 countries (2). In the absence of pharmaceutical prophylactic options, the primary means of COVID-19 control are social distancing interventions, including school closures, work restrictions, shelter-in-place measures, and travel bans.

In late January, reported COVID-19 cases rose steeply in Hubei Province, and imported cases sparked outbreaks in many other cities throughout China. By February 14, 2020, the government had limited the movement of >500 million persons across 80 cities, many of which rapidly enacted multiple social distancing orders to slow the local spread of the virus, including restricting nonessential services and public transit (36). Given the substantial economic and societal costs of such measures (7), estimates of their effectiveness can serve as critical evidence for intervention policy decisions worldwide (8).

Figure

Thumbnail of Coronavirus disease (COVID-19) introductions, transmission, and containment for 2 provincial capitals, China, before February 15, 2020. A) Estimated daily incidence of COVID-19 cases and the implementation of local social distancing measures in Xi’an. B) Estimated daily incidence of COVID-19 cases and the implementation of local social distancing measures in Nanjing. C, D) Estimated daily time-varying reproduction numbers (Rt). Green line indicates the median and gray shading 95% CI

Figure. Coronavirus disease (COVID-19) introductions, transmission, and containment for 2 provincial capitals, China, before February 15, 2020. A) Estimated daily incidence of COVID-19 cases and the implementation of local social distancing measures...

Using case data from online reports published by the Chinese Center for Disease Control and health commissions (Appendix Table 4), we estimated the time elapsed between the first reported case in a city and successful containment of the outbreak (χ). Technically, we consider an outbreak contained when the 95% CI of the instantaneous reproduction number (Rt) drops below 1. We analyzed the speed of COVID-19 containment for 58 cities in mainland China outside of Huebei Province that had >20 confirmed cases by February 14, 2020 (Figure; Appendix Tables 2, 3). Collectively, these cities deployed 7 different types of interventions over the course of their epidemics (9): bans on entertainment and public gatherings; broad restrictions on public service including healthcare, schooling, shopping, and restaurants; initiation of a level 1 response entailing systematic testing and isolation of confirmed cases; suspension of intracity public transport; suspension of travel between cities; reporting of confirmed cases; recruitment of governmental staff and volunteers to enforce quarantine and social distancing. The mean (+ SD) time between the first confirmed case and the implementation of the first social distancing measure was 13 (+ 4.7) days. By the time these measures were enacted, the median cumulative reported cases in a city was 40, but the range was 9–248 across the 58 cities. The mean time until successful containment was 21 (+ 7) days after the first reported case and 8 (+ 6.8) days following the initiation of interventions. During the period of containment, the reproduction number (Rt) declined by an average of 54.3% (+ 17.6%) (Appendix Figure 2).

Using a combination of linear regression and best-subsets model selection (10), we found that the timing of the first intervention and the initiation of level 1 response significantly predicted the speed of containment across the 36 cities that deployed all 7 interventions (R2 = 0.27; p<0.001) (Appendix Figure 1). A delay of 1 day in implementing the first intervention is expected to prolong an outbreak by 2.41 (95% CI 0.96–3.86) days. In contrast, the timing of the level 1 response was inversely related to the speed of containment. Level 1 responses were initiated by the central government across mainland China over the course of 1 week, starting with the hardest hit areas in and near Hubei Province on the first day and working outwards toward more distant cities. Thus, the day of level 1 initiation within this 1-week period is a likely indicator for the initial severity of an outbreak and the corresponding difficulty of containment.

We have estimated the value of proactive social distancing interventions in terms of a reduction in days until successful containment. However, because most cities implemented multiple measures quickly and simultaneously, we are unable to disentangle the efficacies of individual modes of social distancing. We note that our estimates of Rt may be biased by the limited case report data available before February 14, 2020; we lack information about testing rates and priorities in China before February 14. As public health agencies around the globe struggle to determine when to implement potentially costly social distancing measures, these estimates highlight the potential long-term benefits of early and decisive action.

Dr. Du is a postdoctoral researcher in the Department of Integrative Biology at the University of Texas at Austin. He develops mathematical models to elucidate the transmission dynamics, surveillance, and control of infectious diseases.

Top

Acknowledgments

We thank Simon Cauchemez for helpful discussions.

Financial support was provided by US National Institutes of Health (grant no. U01 GM087719), the National Natural Science Foundation of China (grant no. 61773091), and Tito’s Handmade Vodka.

Top

References

  1. Chen  S, Yang  J, Yang  W, Wang  C, Bärnighausen  T. COVID-19 control in China during mass population movements at New Year. Lancet. 2020;395:7646. DOIPubMedGoogle Scholar
  2. World Health Organization. Coronavirus disease 2019 (‎COVID-19)‎: situation report 80. 2020 [cited 2020 Apr 9]. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200409-sitrep-80-covid-19.pdf
  3. Chan  JF-W, Yuan  S, Kok  K-H, To  KK-W, Chu  H, Yang  J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395:51423. DOIPubMedGoogle Scholar
  4. Kraemer  MUG, Yang  C-H, Gutierrez  B, Wu  C-H, Klein  B, Pigott  DM, et al. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science. 2020 Mar 25 [cited 2020 Mar 26]. https://science.sciencemag.org/content/early/2020/03/25/science.abb4218
  5. Chinazzi  M, Davis  JT, Ajelli  M, Gioannini  C, Litvinova  M, Merler  S, et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science. 2020;368:395400. DOIPubMedGoogle Scholar
  6. Wu  Z, McGoogan  JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72,314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323:123942. DOIPubMedGoogle Scholar
  7. Ayittey  FK, Ayittey  MK, Chiwero  NB, Kamasah  JS, Dzuvor  C. Economic impacts of Wuhan 2019-nCoV on China and the world. J Med Virol. 2020;92:4735. DOIPubMedGoogle Scholar
  8. 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;395:138293. DOIPubMedGoogle Scholar
  9. Tian  H, Liu  Y, Li  Y, Wu  C-H, Chen  B, Kraemer  MUG, et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science. 2020;368:63842. DOIPubMedGoogle Scholar
  10. Yang  H. The case for being automatic: introducing the automatic linear modeling (LINEAR) procedure in SPSS statistics. Multiple Linear Regression Viewpoints. 2013;39:2737.

Top

Figure

Top

Cite This Article

DOI: 10.3201/eid2609.201932

Original Publication Date: June 09, 2020

Table of Contents – Volume 26, Number 9—September 2020

EID Search Options
presentation_01 Advanced Article Search – Search articles by author and/or keyword.
presentation_01 Articles by Country Search – Search articles by the topic country.
presentation_01 Article Type Search – Search articles by article type and issue.

Top

Comments

Please use the form below to submit correspondence to the authors or contact them at the following address:

Lauren Ancel Meyers, Department of Integrative Biology, The University of Texas at Austin, 1 University Station C0990, Austin, TX 78712, USA

Send To

10000 character(s) remaining.

Top

Page created: June 03, 2020
Page updated: August 20, 2020
Page reviewed: August 20, 2020
The conclusions, findings, and opinions expressed by authors contributing to this journal do not necessarily reflect the official position of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.
file_external