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Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic

Author

Listed:
  • Ganna Rozhnova

    (University Medical Center Utrecht, Utrecht University
    Universidade de Lisboa)

  • Christiaan H. Dorp

    (Los Alamos National Laboratory)

  • Patricia Bruijning-Verhagen

    (University Medical Center Utrecht, Utrecht University)

  • Martin C. J. Bootsma

    (University Medical Center Utrecht, Utrecht University
    Utrecht University)

  • Janneke H. H. M. Wijgert

    (University Medical Center Utrecht, Utrecht University
    University of Liverpool)

  • Marc J. M. Bonten

    (University Medical Center Utrecht, Utrecht University
    University Medical Center Utrecht)

  • Mirjam E. Kretzschmar

    (University Medical Center Utrecht, Utrecht University)

Abstract

The role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. We use an age-structured transmission model fitted to age-specific seroprevalence and hospital admission data to assess the effects of school-based measures at different time points during the COVID-19 pandemic in the Netherlands. Our analyses suggest that the impact of measures reducing school-based contacts depends on the remaining opportunities to reduce non-school-based contacts. If opportunities to reduce the effective reproduction number (Re) with non-school-based measures are exhausted or undesired and Re is still close to 1, the additional benefit of school-based measures may be considerable, particularly among older school children. As two examples, we demonstrate that keeping schools closed after the summer holidays in 2020, in the absence of other measures, would not have prevented the second pandemic wave in autumn 2020 but closing schools in November 2020 could have reduced Re below 1, with unchanged non-school-based contacts.

Suggested Citation

  • Ganna Rozhnova & Christiaan H. Dorp & Patricia Bruijning-Verhagen & Martin C. J. Bootsma & Janneke H. H. M. Wijgert & Marc J. M. Bonten & Mirjam E. Kretzschmar, 2021. "Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21899-6
    DOI: 10.1038/s41467-021-21899-6
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    Cited by:

    1. Arnab K Ghosh & Sara Venkatraman & Evgeniya Reshetnyak & Mangala Rajan & Anjile An & John K Chae & Mark A Unruh & David Abramson & Charles DiMaggio & Nathaniel Hupert, 2022. "Association between city-wide lockdown and COVID-19 hospitalization rates in multigenerational households in New York City," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-13, March.
    2. Trystan Leng & Edward M. Hill & Alex Holmes & Emma Southall & Robin N. Thompson & Michael J. Tildesley & Matt J. Keeling & Louise Dyson, 2022. "Quantifying pupil-to-pupil SARS-CoV-2 transmission and the impact of lateral flow testing in English secondary schools," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Christiaan H. van Dorp & Emma E. Goldberg & Nick Hengartner & Ruian Ke & Ethan O. Romero-Severson, 2021. "Estimating the strength of selection for new SARS-CoV-2 variants," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    4. Otilia Boldea & Adriana Cornea-Madeira & João Madeira, 2023. "Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: a dynamic intensity model," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 444-466.
    5. Maira Aguiar & Giovanni Dosi & Damian A. Knopoff & Maria Enrica Virgillito, 2021. "A multiscale network-based model of contagion dynamics: heterogeneity, spatial distancing and vaccination," LEM Papers Series 2021/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

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