The unmitigated profile of COVID-19 infectiousness

  1. Ron Sender
  2. Yinon Bar-On
  3. Sang Woo Park
  4. Elad Noor
  5. Jonathan Dushoff
  6. Ron Milo  Is a corresponding author
  1. Weizmann Institute of Science, Israel
  2. Princeton University, United States
  3. McMaster University, Canada

Abstract

Quantifying the temporal dynamics of infectiousness of individuals infected with SARS-CoV-2 is crucial for understanding the spread of COVID-19 and for evaluating the effectiveness of mitigation strategies. Many studies have estimated the infectiousness profile using observed serial intervals. However, statistical and epidemiological biases could lead to underestimation of the duration of infectiousness. We correct for these biases by curating data from the initial outbreak of the pandemic in China (when mitigation was minimal), and find that the infectiousness profile of the original strain is longer than previously thought. Sensitivity analysis shows our results are robust to model structure, assumed growth rate and potential observational biases. Although unmitigated transmission data is lacking for variants of concern (VOC), previous analyses suggest that the alpha and delta variants have faster within-host kinetics, which we extrapolate to crude estimates of variant-specific unmitigated generation intervals. Knowing the unmitigated infectiousness profile of infected individuals can inform estimates of the effectiveness of isolation and quarantine measures. The framework presented here can help design better quarantine policies in early stages of future epidemics.

Data availability

All study data are included in the article, SI appendix, and Dataset S1.All code is available in Jupyter notebooks found inhttps://gitlab.com/milo-lab-public/the-unmitigated-profile-of-covid-19-infectiousness

The following previously published data sets were used
    1. Wu et al
    (2020) Supplementary Table 8. Dates of symptom onset of infector-infectee pairs
    Supplementary Table 8. Dates of symptom onset of infector-infectee pairs.

Article and author information

Author details

  1. Ron Sender

    Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
    Competing interests
    The authors declare that no competing interests exist.
  2. Yinon Bar-On

    Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
    Competing interests
    The authors declare that no competing interests exist.
  3. Sang Woo Park

    Department of Ecology and Evolutionary, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Elad Noor

    Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8776-4799
  5. Jonathan Dushoff

    Department of Biology, McMaster University, Hamilton, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0506-4794
  6. Ron Milo

    Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
    For correspondence
    ron.milo@weizmann.ac.il
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1641-2299

Funding

Weizmann Institute of Science (The Weizmann CoronaVirus Fund)

  • Ron Milo

Weizmann Institute of Science (Weizmann Data Science Research Center,and by a research grant from the Estate of Tully and Michele)

  • Ron Sender

Canadian Institute for Health Research

  • Jonathan Dushoff

Ben B. and Joyce E. Eisenberg Foundation

  • Ron Milo

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

Reviewing Editor

  1. Katelyn Gostic, University of Chicago, United States

Publication history

  1. Received: March 31, 2022
  2. Accepted: July 27, 2022
  3. Accepted Manuscript published: August 1, 2022 (version 1)

Copyright

© 2022, Sender 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.

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  1. Ron Sender
  2. Yinon Bar-On
  3. Sang Woo Park
  4. Elad Noor
  5. Jonathan Dushoff
  6. Ron Milo
(2022)
The unmitigated profile of COVID-19 infectiousness
eLife 11:e79134.
https://doi.org/10.7554/eLife.79134

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