Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales

  1. Sarah Beale
  2. Susan Hoskins
  3. Thomas Byrne
  4. Wing Lam Erica Fong
  5. Ellen Fragaszy
  6. Cyril Geismar
  7. Jana Kovar
  8. Annalan M D Navaratnam
  9. Vincent Nguyen
  10. Parth Patel
  11. Alexei Yavlinsky
  12. Anne M Johnson
  13. Martie Van Tongeren
  14. Robert W Aldridge
  15. Andrew Hayward

Reviewed by

Read the full article

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Background

Workers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase.

Methods

Data from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR).

Findings

Increased risk was seen in nurses (aRR=1.44, 1.25-1.65; AF=30%, 20-39%), doctors (aRR=1.33, 1.08-1.65; AF=25%, 7-39%), carers (1.45, 1.19-1.76; AF=31%, 16-43%), primary school teachers (aRR=1.67, 1.42-1.96; AF=40%, 30-49%), secondary school teachers (aRR=1.48, 1.26-1.72; AF=32%, 21-42%), and teaching support occupations (aRR=1.42, 1.23-1.64; AF=29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves.

Interpretation

Occupational differentials in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.12.14.21267460: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: Ethics Approval: Virus Watch was approved by the Hampstead NHS Health Research Authority Ethics Committee: 20/HRA/2320, and conformed to the ethical standards set out in the Declaration of Helsinki.
    Consent: All participants provided informed consent for all aspects of the study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisWe also performed a sensitivity analysis limited to participants who had undergone serological testing (n=7372) to address potential differential access and testing behaviour for virological/antigen testing across occupations; it was only possible to perform this analysis on broad occupational groups across the full study period, and not for specific occupations or by wave due to limited statistical power.

    Table 2: Resources

    Antibodies
    SentencesResources
    , anti-nucleocapsid antibody serological test, or anti-spike antibody serological test in absence of vaccination).
    anti-nucleocapsid
    suggested: None
    anti-spike
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and Limitations: Strengths of this study include the large and diverse cohort that enabled investigation of infection risk from multiple study-derived and linked sources including both symptomatic testing and serology over multiple pandemic phases. Detailed information around participants’ demographic characteristics and activities over time allowed adjustment for a comprehensive series of potential confounders, including non-work-related public activities, informed by a directed acyclic graph. However, the study has several important limitations. The Virus Watch cohort is demographically diverse but not representative of the UK population, with underrepresentation of some occupational categories limiting the ability to investigate differential risk across all occupational categories. Potential confounders, such as deprivation, are challenging to measure and residual confounding cannot be excluded. Non-work public activities were inferred from self-reported activities across a given survey week, and may not have been an accurate reflection of participants’ activity patterns across the entire relevant time period. Furthermore, social and leisure activities may have included work for some occupational groups (e.g. leisure and personal service occupations) but could not be disaggregated; however, the limited effect of adjustment in these models indicates that this was unlikely to be a major source of bias. Occupation was measured in broad categories, and only some spec...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.12.14.21267460 on medRxiv