COVID-19 cluster size and transmission rates in schools from crowdsourced case reports

  1. Paul Tupper  Is a corresponding author
  2. Shraddha Pai
  3. COVID Schools Canada
  4. Caroline Colijn  Is a corresponding author
  1. Simon Fraser University, Canada
  2. University of Toronto, Canada

Abstract

The role of schools in the spread of SARS-CoV-2 is controversial, with some claiming they are an important driver of the pandemic and others arguing that transmission in schools is negligible. School cluster reports that have been collected in various jurisdictions are a source of data about transmission in schools. These reports consist of the name of a school, a date, and the number of students known to be infected. We provide a simple model for the frequency and size of clusters in this data, based on random arrivals of index cases at schools who then infect their classmates with a highly variable rate, fitting the overdispersion evident in the data. We fit our model to reports from four Canadian provinces, providing estimates of mean and dispersion for cluster size, as well as the distribution of the instantaneous transmission parameter β, whilst factoring in imperfect ascertainment. According to our model with parameters estimated from the data, in all four provinces i) more than 65% of non-index cases occur in the 20% largest clusters, and ii) reducing instantaneous transmission rate and the number of contacts a student has at any given time are effective in reducing the total number of cases, whereas strict bubbling (keeping contacts consistent over time) does not contribute much to reduce cluster sizes. We predict strict bubbling to be more valuable in scenarios with substantially higher transmission rates.

Data availability

Code and data have been deposited in GitHub https://github.com/PaulFredTupper/covid-19-clusters-in-schools and Zenodo https://zenodo.org/record/7117270#.YzM0E-zMKjA

Article and author information

Author details

  1. Paul Tupper

    Department of Mathematics, Simon Fraser University, Burnaby, Canada
    For correspondence
    pft3@sfu.ca
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4340-4481
  2. Shraddha Pai

    The Donnelly Centre, University of Toronto, Toronto, Canada
    Competing interests
    No competing interests declared.
  3. COVID Schools Canada

  4. Caroline Colijn

    Department of 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

Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-06911)

  • Paul Tupper

Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-06624)

  • 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. Joshua T Schiffer, Fred Hutchinson Cancer Research Center, United States

Version history

  1. Received: December 7, 2021
  2. Preprint posted: December 8, 2021 (view preprint)
  3. Accepted: October 20, 2022
  4. Accepted Manuscript published: October 21, 2022 (version 1)
  5. Version of Record published: November 30, 2022 (version 2)

Copyright

© 2022, Tupper 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. Paul Tupper
  2. Shraddha Pai
  3. COVID Schools Canada
  4. Caroline Colijn
(2022)
COVID-19 cluster size and transmission rates in schools from crowdsourced case reports
eLife 11:e76174.
https://doi.org/10.7554/eLife.76174

Share this article

https://doi.org/10.7554/eLife.76174

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