Evidence map›Paper›PMID 34404780›Full record

ArticleNature communications2021

High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions.

Ellen Brooks-Pollock, Hannah Christensen, Adam Trickey, Gibran Hemani, Emily Nixon, Amy C Thomas, Katy Turner, Adam Finn, Matt Hickman, Caroline Relton and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. The Risk from Reopening International Travel During a Disease X Pandemic: A Case Study of SARS-CoV-2.Risk analysis : an official publication of the Society for Risk Analysis · 2026
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  20. 'Whiteness is anHigher education · 2022
    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

11 authors.

Ellen Brooks-PollockBristol Veterinary School, University of Bristol, Langford, Bristol, UK. Ellen.Brooks-Pollock@bristol.ac.uk.ORCID 0000-0002-5984-4932
Hannah ChristensenPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Adam TrickeyPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Gibran HemaniPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.ORCID 0000-0003-0920-1055
Emily NixonSchool of Biological Sciences, University of Bristol, Bristol, Bristol, UK.ORCID 0000-0002-1626-9296
Amy C ThomasBristol Veterinary School, University of Bristol, Langford, Bristol, UK.
Katy TurnerBristol Veterinary School, University of Bristol, Langford, Bristol, UK.ORCID 0000-0002-8152-6017
Adam FinnBristol Children's Vaccine Centre, University of Bristol, Bristol, Bristol, UK.
Matt HickmanPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Caroline ReltonPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Leon DanonDepartment of Engineering Mathematics, University of Bristol, Bristol, Bristol, UK.

Funding

Department of HealthMedical Research Council MC/PC/19067Medical Research Council MC_PC_19067Medical Research Council MC_PC_19067/2Medical Research Council MC_UU_00011/5Medical Research Council MR/V028545/1Medical Research Council MR/V038613/1Wellcome Trust 208806/Z/17/ZWellcome Trust 217509/Z/19/Z
6 · The paper itself

Abstract

Controlling COVID-19 transmission in universities poses challenges due to the complex social networks and potential for asymptomatic spread. We developed a stochastic transmission model based on realistic mixing patterns and evaluated alternative mitigation strategies. We predict, for plausible model parameters, that if asymptomatic cases are half as infectious as symptomatic cases, then 15% (98% Prediction Interval: 6-35%) of students could be infected during the first term without additional control measures. First year students are the main drivers of transmission with the highest infection rates, largely due to communal residences. In isolation, reducing face-to-face teaching is the most effective intervention considered, however layering multiple interventions could reduce infection rates by 75%. Fortnightly or more frequent mass testing is required to impact transmission and was not the most effective option considered. Our findings suggest that additional outbreak control measures should be considered for university settings.

Indexed as

UniversitiesCOVID-19Disease OutbreaksHumansModels, BiologicalSARS-CoV-2StudentsSurveys and QuestionnairesUnited Kingdom

Identifiers

PMID34404780
PMCPMC8371131

What OpenQuestion holds

Textmetadata
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.