Literature DB >> 34224948

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

Edward M Hill1, Benjamin D Atkins2, Matt J Keeling2, Michael J Tildesley2, Louise Dyson2.   

Abstract

Around 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.
Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  COVID-19; Infectious disease model; Mathematical epidemiology; SARS-CoV-2; Universities

Year:  2021        PMID: 34224948     DOI: 10.1016/j.epidem.2021.100476

Source DB:  PubMed          Journal:  Epidemics        ISSN: 1878-0067            Impact factor:   4.396


  7 in total

1.  Genomic Surveillance of SARS-CoV-2 in a University Community: Insights Into Tracking Variants, Transmission, and Spread of Gamma (P.1) Variant.

Authors:  Ilinca I Ciubotariu; Jack Dorman; Nicole M Perry; Lev Gorenstein; Jobin J Kattoor; Abebe A Fola; Amy Zine; G Kenitra Hendrix; Rebecca P Wilkes; Andrew Kitchen; Giovanna Carpi
Journal:  Open Forum Infect Dis       Date:  2022-05-26       Impact factor: 4.423

2.  Screening for SARS-CoV-2 Infection in Students at the Medical University of Warsaw, Poland Between November 15 and December 10, 2021 Using a Single Lateral Flow Test, the Panbio™ COVID-19 Ag Rapid Test.

Authors:  Mariusz Gujski; Paulina Mularczyk-Tomczewska; Filip Raciborski; Piotr Samel-Kowalik; Łukasz Samoliński; Dorota Olczak-Kowalczyk; Mateusz Jankowski
Journal:  Med Sci Monit       Date:  2022-06-04

3.  SARS-CoV-2 infection in UK university students: lessons from September-December 2020 and modelling insights for future student return.

Authors:  Jessica Enright; Edward M Hill; Helena B Stage; Kirsty J Bolton; Emily J Nixon; Emma L Fairbanks; Maria L Tang; Ellen Brooks-Pollock; Louise Dyson; Chris J Budd; Rebecca B Hoyle; Lars Schewe; Julia R Gog; Michael J Tildesley
Journal:  R Soc Open Sci       Date:  2021-08-04       Impact factor: 3.653

4.  Estimating data-driven coronavirus disease 2019 mitigation strategies for safe university reopening.

Authors:  Qihui Yang; Don M Gruenbacher; Caterina M Scoglio
Journal:  J R Soc Interface       Date:  2022-03-14       Impact factor: 4.118

5.  A hybrid stochastic model and its Bayesian identification for infectious disease screening in a university campus with application to massive COVID-19 screening at the University of Liège.

Authors:  M Arnst; G Louppe; R Van Hulle; L Gillet; F Bureau; V Denoël
Journal:  Math Biosci       Date:  2022-03-16       Impact factor: 3.935

6.  Safe university: a guide for open academic institutions through the pandemic.

Authors:  Manolis Wallace; Georgios Pappas
Journal:  Clin Microbiol Infect       Date:  2022-02-03       Impact factor: 13.310

7.  Genomic epidemiology of SARS-CoV-2 in a university outbreak setting and implications for public health planning.

Authors:  Sema Nickbakhsh; Joseph Hughes; Nicolaos Christofidis; Emily Griffiths; Sharif Shaaban; Jessica Enright; Katherine Smollett; Kyriaki Nomikou; Natasha Palmalux; Lily Tong; Stephen Carmichael; Vattipally B Sreenu; Richard Orton; Emily J Goldstein; Rachael M Tomb; Kate Templeton; Rory N Gunson; Ana da Silva Filipe; Catriona Milosevic; Emma Thomson; David L Robertson; Matthew T G Holden; Christopher J R Illingworth; Alison Smith-Palmer
Journal:  Sci Rep       Date:  2022-07-19       Impact factor: 4.996

  7 in total

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