Endemic-epidemic modelling of school closure to prevent spread of COVID-19 in Switzerland

The goal of this work was to quantify the effect of school closure during the first year of coronavirus disease 2019 (COVID-19) pandemic in Switzerland. This allowed us to determine the usefulness of school closures as a pandemic countermeasure for emerging coronaviruses in the absence of pharmaceutical interventions. The use of multivariate endemic-epidemic modelling enabled us to analyse disease spread between age groups which we believe is a necessary inclusion in any model seeking to achieve our goal. Sophisticated time-varying contact matrices encapsulating four different contact settings were included in our complex statistical modelling approach to reflect the amount of school closure in place on a given day. Using the model, we projected case counts under various transmission scenarios (driven by implemented social distancing policies). We compared these counterfactual scenarios against the true levels of social distancing policies implemented, where schools closed in the spring and reopened in the autumn. We found that if schools had been kept open, the vast majority of additional cases would be expected among primary school-aged children with a small fraction of cases filtering into other age groups following the contact matrix structure. Under this scenario where schools were kept open, the cases were highly concentrated among the youngest age group. In the scenario where schools had remained closed, most reduction would also be expected in the lowest age group with less effects seen in other groups.

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Publication Details

Journal
BMC Infectious Diseases
Published
2024-12-02
DOI
https://doi.org/10.1186/s12879-024-09674-6
Citations
3
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.19

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article

Endemic-epidemic modelling of school closure to prevent spread of COVID-19 in Switzerland

Maria Bekker‐Nielsen Dunbar, Sebastian Meyer, Felix Hofmann, Leonhard Held
3 citations
BMC Infectious Diseases
COVID-19 epidemiological studies
1.19
article

Endemic-epidemic modelling of school closure to prevent spread of COVID-19 in Switzerland

Maria Bekker‐Nielsen Dunbar, Sebastian Meyer, Felix Hofmann, Leonhard Held
article en
3 citations

Abstract

The goal of this work was to quantify the effect of school closure during the first year of coronavirus disease 2019 (COVID-19) pandemic in Switzerland. This allowed us to determine the usefulness of school closures as a pandemic countermeasure for emerging coronaviruses in the absence of pharmaceutical interventions. The use of multivariate endemic-epidemic modelling enabled us to analyse disease spread between age groups which we believe is a necessary inclusion in any model seeking to achieve our goal. Sophisticated time-varying contact matrices encapsulating four different contact settings were included in our complex statistical modelling approach to reflect the amount of school closure in place on a given day. Using the model, we projected case counts under various transmission scenarios (driven by implemented social distancing policies). We compared these counterfactual scenarios against the true levels of social distancing policies implemented, where schools closed in the spring and reopened in the autumn. We found that if schools had been kept open, the vast majority of additional cases would be expected among primary school-aged children with a small fraction of cases filtering into other age groups following the contact matrix structure. Under this scenario where schools were kept open, the cases were highly concentrated among the youngest age group. In the scenario where schools had remained closed, most reduction would also be expected in the lowest age group with less effects seen in other groups.

BMC Infectious DiseasesVol. 24(1)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), University of Zurich (CH), Prevention Institute (US)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Good health and well-being
Openalex Percentile: Top 22%
COVID-19 epidemiological studies
1.19
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