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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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WRAP-modelling-SARS-CoV-2-transmission-UK-university-setting-2021.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (2126Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.epidem.2021.100476
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 | ||||||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine | ||||||||||||
| Divisions: | Faculty of Science > Life Sciences (2010- ) Faculty of Science > Mathematics |
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| 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: |
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| 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: |
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