Coronavirus disease 2019 outbreak in Beijing’s Xinfadi Market, China: a modeling study to inform future resurgence response

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Abstract

Background

A local coronavirus disease 2019 (COVID-19) case confirmed on June 11, 2020 triggered an outbreak in Beijing, China after 56 consecutive days without a newly confirmed case. Non-pharmaceutical interventions (NPIs) were used to contain the source in Xinfadi (XFD) market. To rapidly control the outbreak, both traditional and newly introduced NPIs including large-scale management of high-risk populations and expanded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-based screening in the general population were conducted in Beijing. We aimed to assess the effectiveness of the response to the COVID-19 outbreak in Beijing’s XFD market and inform future response efforts of resurgence across regions.

Methods

A modified susceptible–exposed–infectious–recovered (SEIR) model was developed and applied to evaluate a range of different scenarios from the public health perspective. Two outcomes were measured: magnitude of transmission (i.e., number of cases in the outbreak) and endpoint of transmission (i.e., date of containment). The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% Confidence Interval (CI).

Results

Our results indicated that a 3 to 14 day delay in the identification of XFD as the infection source and initiation of NPIs would have caused a 3 to 28-fold increase in total case number (31–77 day delay in containment). A failure to implement the quarantine scheme employed in the XFD outbreak for defined key population would have caused a fivefold greater number of cases (73 day delay in containment). Similarly, failure to implement the quarantine plan executed in the XFD outbreak for close contacts would have caused twofold greater transmission (44 day delay in containment). Finally, failure to implement expanded nucleic acid screening in the general population would have yielded 1.6-fold greater transmission and a 32 day delay to containment.

Conclusions

This study informs new evidence that in form the selection of NPI to use as countermeasures in response to a COVID-19 outbreak and optimal timing of their implementation. The evidence provided by this study should inform responses to future outbreaks of COVID-19 and future infectious disease outbreak preparedness efforts in China and elsewhere.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00843-2.

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Most cited references 19

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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

Derek K. Chu, Elie A. Akl, Stephanie Duda … (2020)

Summary Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and is spread person-to-person through close contact. We aimed to investigate the effects of physical distance, face masks, and eye protection on virus transmission in health-care and non-health-care (eg, community) settings. Methods We did a systematic review and meta-analysis to investigate the optimum distance for avoiding person-to-person virus transmission and to assess the use of face masks and eye protection to prevent transmission of viruses. We obtained data for SARS-CoV-2 and the betacoronaviruses that cause severe acute respiratory syndrome, and Middle East respiratory syndrome from 21 standard WHO-specific and COVID-19-specific sources. We searched these data sources from database inception to May 3, 2020, with no restriction by language, for comparative studies and for contextual factors of acceptability, feasibility, resource use, and equity. We screened records, extracted data, and assessed risk of bias in duplicate. We did frequentist and Bayesian meta-analyses and random-effects meta-regressions. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO, CRD42020177047. Findings Our search identified 172 observational studies across 16 countries and six continents, with no randomised controlled trials and 44 relevant comparative studies in health-care and non-health-care settings (n=25 697 patients). Transmission of viruses was lower with physical distancing of 1 m or more, compared with a distance of less than 1 m (n=10 736, pooled adjusted odds ratio [aOR] 0·18, 95% CI 0·09 to 0·38; risk difference [RD] −10·2%, 95% CI −11·5 to −7·5; moderate certainty); protection was increased as distance was lengthened (change in relative risk [RR] 2·02 per m; p interaction=0·041; moderate certainty). Face mask use could result in a large reduction in risk of infection (n=2647; aOR 0·15, 95% CI 0·07 to 0·34, RD −14·3%, −15·9 to −10·7; low certainty), with stronger associations with N95 or similar respirators compared with disposable surgical masks or similar (eg, reusable 12–16-layer cotton masks; p interaction=0·090; posterior probability >95%, low certainty). Eye protection also was associated with less infection (n=3713; aOR 0·22, 95% CI 0·12 to 0·39, RD −10·6%, 95% CI −12·5 to −7·7; low certainty). Unadjusted studies and subgroup and sensitivity analyses showed similar findings. Interpretation The findings of this systematic review and meta-analysis support physical distancing of 1 m or more and provide quantitative estimates for models and contact tracing to inform policy. Optimum use of face masks, respirators, and eye protection in public and health-care settings should be informed by these findings and contextual factors. Robust randomised trials are needed to better inform the evidence for these interventions, but this systematic appraisal of currently best available evidence might inform interim guidance. Funding World Health Organization.

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Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

Seth Flaxman, Swapnil Mishra, Axel Gandy … (2020)

Following the detection of the new coronavirus1 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (Rt). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that-for all of the countries we consider here-current interventions have been sufficient to drive Rt below 1 (probability Rt < 1.0 is greater than 99%) and achieve control of the epidemic. We estimate that across all 11 countries combined, between 12 and 15 million individuals were infected with SARS-CoV-2 up to 4 May 2020, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions-and lockdowns in particular-have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.

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An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China

Huaiyu Tian, Yonghong Liu, Yidan Li … (2020)

Responding to an outbreak of a novel coronavirus (agent of COVID-19) in December 2019, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. We investigated the spread and control of COVID-19 using a unique data set including case reports, human movement and public health interventions. The Wuhan shutdown was associated with the delayed arrival of COVID-19 in other cities by 2.91 days (95%CI: 2.54-3.29). Cities that implemented control measures pre-emptively reported fewer cases, on average, in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Suspending intra-city public transport, closing entertainment venues and banning public gatherings were associated with reductions in case incidence. The national emergency response appears to have delayed the growth and limited the size of the COVID-19 epidemic in China, averting hundreds of thousands of cases by 19 February (day 50).

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Author and article information

Contributors

Jing-Yuan Wang: jywang@buaa.edu.cn

Sheng-Jie Lai: shengjie.lai@soton.ac.uk

Chun Huang: huangch@bjcdc.on.ac.uk

Quan-Yi Wang:

ORCID: http://orcid.org/0000-0001-9552-2503

bjcdcxm@126.com

Journal

Journal ID (nlm-ta): Infect Dis Poverty

Journal ID (iso-abbrev): Infect Dis Poverty

Title: Infectious Diseases of Poverty

Publisher: BioMed Central (London )

ISSN (Print): 2095-5162

ISSN (Electronic): 2049-9957

Publication date (Electronic): 7 May 2021

Publication date PMC-release: 7 May 2021

Publication date Collection: 2021

Volume: 10

Electronic Location Identifier: 62

Affiliations

[1 ]GRID grid.418263.a, Beijing Research Center for Preventive Medicine, , Beijing Center for Disease Prevention and Control, ; Beijing, China

[2 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, School of Public Health, , Capital Medical University, ; Beijing, China

[3 ]Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China

[4 ]GRID grid.64939.31, ISNI 0000 0000 9999 1211, School of Computer Science and Engineering, , Beihang University, ; Beijing, China

[5 ]GRID grid.198530.6, ISNI 0000 0000 8803 2373, Chinese Center for Disease Control and Prevention, ; Beijing, China

[6 ]Yidu Cloud AI Lab, Yidu Cloud (Beijing) Technology Co., Ltd, Beijing, China

[7 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Johns Hopkins Bloomberg School of Public Health, , Johns Hopkins University, ; Baltimore, MD USA

[8 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, WorldPop, School of Geography and Environmental Science, , University of Southampton, ; Southampton, UK

[9 ]GRID grid.8547.e, ISNI 0000 0001 0125 2443, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, , Fudan University, ; Shanghai, China

Author information

Quan-Yi Wang http://orcid.org/0000-0001-9552-2503

Article

Publisher ID: 843

DOI: 10.1186/s40249-021-00843-2

PMC ID: 8103671

PubMed ID: 33962683

SO-VID: b0ece697-cb5d-4119-96ed-f50a1f1d059b

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 26 January 2021

Date accepted : 14 April 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100012401, Beijing Science and Technology Planning Project;

Award ID: Z201100005420010

Award Recipient : Peng Yang

Funded by: National Key R&D Program of China

Award ID: 2019YFB2102103

Award Recipient : Jing-Yuan Wang

Funded by: National Natural Science Foundation of China

Award ID: 92046010

Award ID: 82161148011

Award Recipient : Jing-Yuan Wang

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Keywords: public health,nonpharmaceutical intervention,covid-19,sars-cov-2,beijing

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Keywords: public health, nonpharmaceutical intervention, covid-19, sars-cov-2, beijing

Coronavirus disease 2019 outbreak in Beijing’s Xinfadi Market, China: a modeling study to inform future resurgence response

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Abstract

Background

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Results

Conclusions

Graphical abstract

Supplementary Information

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Novel Coronavirus Disease COVID-19

Most cited references 19

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

Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China

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