Evidence map›Paper›PMID 39617920›Full record

ArticleBMC infectious diseases2024

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

M Bekker-Nielsen Dunbar, F Hofmann, S Meyer, L Held

Abstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

M Bekker-Nielsen DunbarEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001, Zurich, Switzerland. bl328@uni-heidelberg.de.ORCID http://orcid.org/0000-0002-7249-3524
F HofmannEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-3891-6239
S Meyer *Institute of Medical Informatics, Biometry, and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstraße 22, 91054, Erlangen, Germany.ORCID http://orcid.org/0000-0002-1791-9449
L Held *Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001, Zurich, Switzerland. leonhard.held@uzh.ch.ORCID http://orcid.org/0000-0002-8686-5325

Funding

Swiss National Science Foundation 196247
6 · The paper itself

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.

Indexed as

COVID-19SARS-CoV-2SchoolsAdolescentAdultChildChild, PreschoolFemaleHumansInfantMaleMiddle AgedModels, StatisticalPandemicsPhysical DistancingSwitzerlandCOVID-19Endemic–epidemic modellingSchool closureSocial contactsSurveillance data

Identifiers

PMID39617920
PMCPMC11610105

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.