Settings for non-household transmission of SARS-CoV-2 during the second lockdown in England and Wales – analysis of the Virus Watch household community cohort study [version 1; peer review: 2 approved]

Vincent Nguyen; Clare French; Parth Patel; Alexei Yavlinksy; Colette Smith; Cyril Geismar; Sarah Beale; Anne M. Johnson; Robert W. Aldridge; Annalan M.D. Navaratnam; Wing Lam Erica Fong; Ellen Fragaszy; Thomas Byrne; Jana Kovar; Andrew Hayward; Susan Hoskins

Wellcome Open Research (Aug 2022)

Settings for non-household transmission of SARS-CoV-2 during the second lockdown in England and Wales – analysis of the Virus Watch household community cohort study [version 1; peer review: 2 approved]

Vincent Nguyen,
Clare French,
Parth Patel,
Alexei Yavlinksy,
Colette Smith,
Cyril Geismar,
Sarah Beale,
Anne M. Johnson,
Robert W. Aldridge,
Annalan M.D. Navaratnam,
Wing Lam Erica Fong,
Ellen Fragaszy,
Thomas Byrne,
Jana Kovar,
Andrew Hayward,
Susan Hoskins

Affiliations

Vincent Nguyen: Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Clare French: NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Uinversity of Bristol, Bristol, BS8 2BN, UK
Parth Patel: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Alexei Yavlinksy: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Colette Smith: Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
Cyril Geismar: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Sarah Beale: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Anne M. Johnson: ORCiD; Institute for Global Health, University College London, London, WC1N 1EH, UK
Robert W. Aldridge: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Annalan M.D. Navaratnam: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Wing Lam Erica Fong: Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Ellen Fragaszy: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Thomas Byrne: Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
Jana Kovar: ORCiD; Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
Andrew Hayward: ORCiD; Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
Susan Hoskins: ORCiD; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK

Journal volume & issue: Vol. 7

Abstract

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Background: “Lockdowns” to control serious respiratory virus pandemics were widely used during the coronavirus disease 2019 (COVID-19) pandemic. However, there is limited information to understand the settings in which most transmission occurs during lockdowns, to support refinement of similar policies for future pandemics. Methods: Among Virus Watch household cohort participants we identified those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outside the household. Using survey activity data, we undertook multivariable logistic regressions assessing the contribution of activities on non-household infection risk. We calculated adjusted population attributable fractions (APAF) to estimate which activity accounted for the greatest proportion of non-household infections during the pandemic’s second wave. Results: Among 10,858 adults, 18% of cases were likely due to household transmission. Among 10,475 participants (household-acquired cases excluded), including 874 non-household-acquired infections, infection was associated with: leaving home for work or education (AOR 1.20 (1.02 – 1.42), APAF 6.9%); public transport (more than once per week AOR 1.82 (1.49 – 2.23), public transport APAF 12.42%); and shopping (more than once per week AOR 1.69 (1.29 – 2.21), shopping APAF 34.56%). Other non-household activities were rare and not significantly associated with infection. Conclusions: During lockdown, going to work and using public or shared transport independently increased infection risk, however only a minority did these activities. Most participants visited shops, accounting for one-third of non-household transmission. Transmission in restricted hospitality and leisure settings was minimal suggesting these restrictions were effective. If future respiratory infection pandemics emerge these findings highlight the value of working from home, using forms of transport that minimise exposure to others, minimising exposure to shops and restricting non-essential activities.

Published in Wellcome Open Research

ISSN: 2398-502X (Online)
Publisher: Wellcome
Country of publisher: United Kingdom
LCC subjects: Medicine; Science
Website: https://wellcomeopenresearch.org/

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