Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses [version 1; peer review: 1 approved, 2 approved with reservations]: Available data and framework for analyses

Neil Pearce, Sarah Rhodes, Katie Stocking, Lucy Pembrey, Karin van Veldhoven, Elizabeth B. Brickley, Steve Robertson, Donna Davoren, Vahe Nafilyan, Ben Windsor-Shellard, Tony Fletcher, Martie van Tongeren, Helen Kreissl

Research output: Contribution to journalArticle

Abstract

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Original languageEnglish
Article number102
Pages (from-to)102
JournalWellcome open research
Volume6
DOIs
Publication statusPublished - 10 May 2021

Keywords

  • COVID-19
  • Epidemiology
  • Occupation

Research Beacons, Institutes and Platforms

  • Manchester Environmental Research Institute

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