Occupational inequalities in the prevalence of COVID-19: A longitudinal observational study of England, August 2020 to January 2021

  1. Mark A. Green
  2. Malcolm G. Semple

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Abstract

The COVID-19 pandemic has reinforced, amplified and created new health inequalities. Examining how COVID-19 prevalence varies by measures of work and occupation may help to understand these inequalities. The aim of the study is to evaluate how occupational inequalities in the prevalence of COVID-19 varies across England and their possible explanatory factors. We used data for 363,651 individuals (2,178,835 observations) aged 18 years and over between 1 st May 2020 and 31 st January 2021 from the Office for National Statistics Covid Infection Survey, a representative longitudinal survey of individuals in England. We focus on two measures of work; employment status for all adults, and work sector of individuals currently working. Multi-level binomial regression models were used to estimate the likelihood of testing positive of COVID-19, adjusting for known explanatory covariates. 0.9% of participants tested positive for COVID-19 over the study period. COVID-19 prevalence was higher among adults who were students or furloughed (i.e., temporarily not working). Among adults currently working, COVID-19 prevalence was highest in adults employed in the hospitality sector, with higher prevalence for individuals employed in transport, social care, retail, health care and educational sectors. Inequalities by work were not consistent over time. We find an unequal distribution of infections relating to COVID-19 by work and employment status. While our findings demonstrate the need for greater workplace interventions to protect employees tailored to their specific work sector needs, focusing on employment alone ignores the importance of SARS-CoV-2 transmission outside of employed work (i.e., furloughed and student populations).

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  1. Version published to 10.1371/journal.pone.0283119
  2. ScreenIT

    SciScore for 10.1101/2021.06.01.21258140: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationThe CIS is a representative random sample survey of the population in England used to monitor trends in COVID-Individuals are invited take a COVID-19 test irrespective of whether they have symptoms or not, allowing an estimate of overall COVID-19 prevalence.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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:
    There are several limitations to our study. We do not account for all possible explanatory factors (e.g., deprivation, social distancing behaviours) that may explain occupational inequalities due to a lack of suitable data available for our analysis. Through focusing on work sector, rather than specific occupation or role, we may be limited how generalisable our findings are. For example, teaching and education would include both primary and secondary teachers who were expected to teach classes face-to-face and therefore have different exposures to University lecturers who could far easier adapt to work from home. The lack of specific occupation categories may therefore under-estimate the specific risks and inequalities faced across England. Finally, our analyses are association-based and do not explore potential causal pathways or mechanisms through how and why occupation influences COVID-19 risk. Future research should extend our analyses to consider the specific mechanisms that may explain, mediate or moderate risk.

    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.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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

    About SciScore

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  3. Version published to 10.1101/2021.06.01.21258140v1 on medRxiv