Evidence for transmission of COVID-19 prior to symptom onset

  1. Lauren C Tindale
  2. Jessica E Stockdale
  3. Michelle Coombe
  4. Emma S Garlock
  5. Wing Yin Venus Lau
  6. Manu Saraswat
  7. Louxin Zhang
  8. Dongxuan Chen
  9. Jacco Wallinga
  10. Caroline Colijn  Is a corresponding author
  1. University of British Columbia, Canada
  2. Simon Fraser University, Canada
  3. National University of Singapore, Singapore
  4. National Institute for Public Health and the Environment, Netherlands
  5. Leiden University Medical Center, Netherlands

Abstract

We collated contact tracing data from COVID-19 clusters in Singapore and Tianjin, China and estimated the extent of pre-symptomatic transmission by estimating incubation periods and serial intervals. The mean incubation periods accounting for intermediate cases were 4.91 days (95%CI 4.35, 5.69) and 7.54 (95%CI 6.76, 8.56) days for Singapore and Tianjin, respectively. The mean serial interval was 4.17 (95%CI 2.44, 5.89) and 4.31 (95%CI 2.91, 5.72) days (Singapore, Tianjin). The serial intervals are shorter than incubation periods, suggesting that pre-symptomatic transmission may occur in a large proportion of transmission events (0.4-0.5 in Singapore and 0.6-0.8 in Tianjin, in our analysis with intermediate cases, and more without intermediates). Given the evidence for pre-symptomatic transmission it is vital that even individuals who appear healthy abide by public health measures to control COVID-19.

Data availability

Data are available on github at github.com/CSSEGISandData/COVID-19. Code to produce all analyses is also available there. Source data files of the Singapore and Tianjin clusters have been provided.

Article and author information

Author details

  1. Lauren C Tindale

    Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
    Competing interests
    No competing interests declared.
  2. Jessica E Stockdale

    Mathematics, Simon Fraser University, Burnaby, Canada
    Competing interests
    No competing interests declared.
  3. Michelle Coombe

    School of Population and Public Health, University of British Columbia, Vancouver, Canada
    Competing interests
    No competing interests declared.
  4. Emma S Garlock

    Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, Canada
    Competing interests
    No competing interests declared.
  5. Wing Yin Venus Lau

    Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, Canada
    Competing interests
    No competing interests declared.
  6. Manu Saraswat

    Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, Canada
    Competing interests
    No competing interests declared.
  7. Louxin Zhang

    Department of Mathematics, National University of Singapore, Singapore, Singapore
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0260-824X
  8. Dongxuan Chen

    Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands
    Competing interests
    No competing interests declared.
  9. Jacco Wallinga

    Faculteit Geneeskunde, Leiden University Medical Center, Leiden, Netherlands
    Competing interests
    Jacco Wallinga, Reviewing editor, eLife.
  10. Caroline Colijn

    Mathematics, Simon Fraser University, Burnaby, Canada
    For correspondence
    ccolijn@sfu.ca
    Competing interests
    Caroline Colijn, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6097-6708

Funding

Government of Canada (Canada 150 Research Chair program)

  • Caroline Colijn

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Marc Lipsitch, Harvard TH Chan School of Public Health, United States

Version history

  1. Received: March 23, 2020
  2. Accepted: June 21, 2020
  3. Accepted Manuscript published: June 22, 2020 (version 1)
  4. Version of Record published: July 28, 2020 (version 2)

Copyright

© 2020, Tindale et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 15,115
    Page views
  • 1,013
    Downloads
  • 196
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Lauren C Tindale
  2. Jessica E Stockdale
  3. Michelle Coombe
  4. Emma S Garlock
  5. Wing Yin Venus Lau
  6. Manu Saraswat
  7. Louxin Zhang
  8. Dongxuan Chen
  9. Jacco Wallinga
  10. Caroline Colijn
(2020)
Evidence for transmission of COVID-19 prior to symptom onset
eLife 9:e57149.
https://doi.org/10.7554/eLife.57149

Share this article

https://doi.org/10.7554/eLife.57149

Further reading

    1. Ecology
    2. Epidemiology and Global Health
    Aleksandra Kovacevic, David RM Smith ... Lulla Opatowski
    Research Article

    Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

    1. Epidemiology and Global Health
    Olivera Djuric, Elisabetta Larosa ... The Reggio Emilia Covid-19 Working Group
    Research Article

    Background:

    The aim of our study was to test the hypothesis that the community contact tracing strategy of testing contacts in households immediately instead of at the end of quarantine had an impact on the transmission of SARS-CoV-2 in schools in Reggio Emilia Province.

    Methods:

    We analysed surveillance data on notification of COVID-19 cases in schools between 1 September 2020 and 4 April 2021. We have applied a mediation analysis that allows for interaction between the intervention (before/after period) and the mediator.

    Results:

    Median tracing delay decreased from 7 to 3.1 days and the percentage of the known infection source increased from 34–54.8% (incident rate ratio-IRR 1.61 1.40–1.86). Implementation of prompt contact tracing was associated with a 10% decrease in the number of secondary cases (excess relative risk –0.1 95% CI –0.35–0.15). Knowing the source of infection of the index case led to a decrease in secondary transmission (IRR 0.75 95% CI 0.63–0.91) while the decrease in tracing delay was associated with decreased risk of secondary cases (1/IRR 0.97 95% CI 0.94–1.01 per one day of delay). The direct effect of the intervention accounted for the 29% decrease in the number of secondary cases (excess relative risk –0.29 95%–0.61 to 0.03).

    Conclusions:

    Prompt contact testing in the community reduces the time of contact tracing and increases the ability to identify the source of infection in school outbreaks. Although there are strong reasons for thinking it is a causal link, observed differences can be also due to differences in the force of infection and to other control measures put in place.

    Funding:

    This project was carried out with the technical and financial support of the Italian Ministry of Health – CCM 2020 and Ricerca Corrente Annual Program 2023.