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Modelling SARS-CoV-2 transmission in a UK university setting

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Hill, Edward M., Atkins, Benjamin D., Keeling, Matt J., Tildesley, Michael J. and Dyson, Louise (2021) Modelling SARS-CoV-2 transmission in a UK university setting. Epidemics, 36 . 100476. doi:10.1016/j.epidem.2021.100476

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Official URL: http://dx.doi.org/10.1016/j.epidem.2021.100476

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Abstract

round 40% of school leavers in the UK attend university and individual universities generally host thousands of students each academic year. Bringing together these student communities during the COVID-19 pandemic may require strong interventions to control transmission. Prior modelling analyses of SARS-CoV-2 transmission within universities using compartmental modelling approaches suggest that outbreaks are almost inevitable.

We constructed a network-based model to capture the interactions of a student population in different settings (housing, social and study). For a single academic term of a representative campus-based university, we ran a susceptible–latent–infectious–recovered type epidemic process, parameterised according to available estimates for SARS-CoV-2. We investigated the impact of: adherence to (or effectiveness of) isolation and test and trace measures; room isolation of symptomatic students; and supplementary mass testing.

With all adhering to test, trace and isolation measures, we found that 22% (7%–41%) of the student population could be infected during the autumn term, compared to 69% (56%–76%) when assuming zero adherence to such measures. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared to students resident off-campus. Room isolation generated minimal benefits. Regular mass testing, together with high adherence to isolation and test and trace measures, could substantially reduce the proportion infected during the term compared to having no testing.

Our findings suggest SARS-CoV-2 may readily transmit in a university setting if there is limited adherence to nonpharmaceutical interventions and/or there are delays in receiving test results. Following isolation guidance and effective contact tracing curbed transmission and reduced the expected time an adhering student would spend in isolation.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science > Life Sciences (2010- )
Faculty of Science > Mathematics
Library of Congress Subject Headings (LCSH): COVID-19 (Disease) , COVID-19 (Disease) -- Epidemiology -- Great Britain -- Mathematical models , COVID-19 (Disease) -- Forecasting -- Great Britain -- Mathematical models , COVID-19 (Disease) -- Prevention -- Great Britain -- Mathematical models , COVID-19 (Disease) -- Transmission -- Great Britain -- Mathematical models
Journal or Publication Title: Epidemics
Publisher: Elsevier BV
ISSN: 1755-4365
Official Date: September 2021
Dates:
DateEvent
September 2021Published
29 June 2021Available
15 June 2021Accepted
Volume: 36
Article Number: 100476
DOI: 10.1016/j.epidem.2021.100476
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/S022244/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
MR/V009761/1[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/V038613/1UK Research and Innovationhttp://dx.doi.org/10.13039/100014013

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