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Hill EM, Atkins BD, Keeling MJ, Tildesley MJ, Dyson L. Modelling SARS-CoV-2 transmission in a UK university setting. Epidemics 2021; 36:100476. [PMID: 34224948 PMCID: PMC7611483 DOI: 10.1016/j.epidem.2021.100476] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 03/15/2021] [Accepted: 06/15/2021] [Indexed: 01/12/2023] Open
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.
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Affiliation(s)
- Edward M Hill
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7 AL, United Kingdom; Joint UNIversities Pandemic and Epidemiological Research(1), United Kingdom.
| | - Benjamin D Atkins
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7 AL, United Kingdom; Joint UNIversities Pandemic and Epidemiological Research(1), United Kingdom
| | - Matt J Keeling
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7 AL, United Kingdom; Joint UNIversities Pandemic and Epidemiological Research(1), United Kingdom
| | - Michael J Tildesley
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7 AL, United Kingdom; Joint UNIversities Pandemic and Epidemiological Research(1), United Kingdom
| | - Louise Dyson
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7 AL, United Kingdom; Joint UNIversities Pandemic and Epidemiological Research(1), United Kingdom
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Hill EM, Atkins BD, Keeling MJ, Dyson L, Tildesley MJ. A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2. PLoS Comput Biol 2021; 17:e1009058. [PMID: 34133427 PMCID: PMC8208574 DOI: 10.1371/journal.pcbi.1009058] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 05/10/2021] [Indexed: 01/03/2023] Open
Abstract
As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated. We use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create 'COVID-secure' workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics. The progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels. In the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.
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Affiliation(s)
- Edward M. Hill
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/
| | - Benjamin D. Atkins
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/
| | - Matt J. Keeling
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/
| | - Louise Dyson
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/
| | - Michael J. Tildesley
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/
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Smith CM, Shallcross LJ, Dutey-Magni P, Conolly A, Fuller C, Hill S, Jhass A, Marcheselli F, Michie S, Mindell JS, Ridd MJ, Tsakos G, Hayward AC, Fragaszy EB. Incidence, healthcare-seeking behaviours, antibiotic use and natural history of common infection syndromes in England: results from the Bug Watch community cohort study. BMC Infect Dis 2021; 21:105. [PMID: 33482752 PMCID: PMC7820521 DOI: 10.1186/s12879-021-05811-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 01/15/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Better information on the typical course and management of acute common infections in the community could inform antibiotic stewardship campaigns. We aimed to investigate the incidence, management, and natural history of a range of infection syndromes (respiratory, gastrointestinal, mouth/dental, skin/soft tissue, urinary tract, and eye). METHODS Bug Watch was an online prospective community cohort study of the general population in England (2018-2019) with weekly symptom reporting for 6 months. We combined symptom reports into infection syndromes, calculated incidence rates, described the proportion leading to healthcare-seeking behaviours and antibiotic use, and estimated duration and severity. RESULTS The cohort comprised 873 individuals with 23,111 person-weeks follow-up. The mean age was 54 years and 528 (60%) were female. We identified 1422 infection syndromes, comprising 40,590 symptom reports. The incidence of respiratory tract infection syndromes was two per person year; for all other categories it was less than one. 194/1422 (14%) syndromes led to GP (or dentist) consultation and 136/1422 (10%) to antibiotic use. Symptoms usually resolved within a week and the third day was the most severe. CONCLUSIONS Most people reported managing their symptoms without medical consultation. Interventions encouraging safe self-management across a range of acute infection syndromes could decrease pressure on primary healthcare services and support targets for reducing antibiotic prescribing.
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Affiliation(s)
- Catherine M Smith
- Institute of Health informatics, UCL, 222 Euston Road, London, NW1 2DA, UK.
| | - Laura J Shallcross
- Institute of Health informatics, UCL, 222 Euston Road, London, NW1 2DA, UK
| | - Peter Dutey-Magni
- Institute of Health informatics, UCL, 222 Euston Road, London, NW1 2DA, UK
| | - Anne Conolly
- NatCen Social Research, 35 Northampton Square, London, EC1V 0AX, UK
| | - Christopher Fuller
- Institute of Health informatics, UCL, 222 Euston Road, London, NW1 2DA, UK
| | - Suzanne Hill
- NatCen Social Research, 35 Northampton Square, London, EC1V 0AX, UK
| | - Arnoupe Jhass
- Institute of Health informatics, UCL, 222 Euston Road, London, NW1 2DA, UK
- Research Department of Primary Care and Population Health, UCL, Rowland Hill Street, London, NW3 2PF, UK
| | | | - Susan Michie
- Centre for Behaviour Change, UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Jennifer S Mindell
- Research Department of Epidemiology and Public Health, UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Matthew J Ridd
- Health Science Institute, University of Bristol, 39 Whatley Road, Bristol, BS8 2PS, UK
| | - Georgios Tsakos
- Research Department of Epidemiology and Public Health, UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Ellen B Fragaszy
- Institute of Health informatics, UCL, 222 Euston Road, London, NW1 2DA, UK
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
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