Evidence map›Paper›PMID 34141900›Full record

ArticleWellcome open research2021

Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: 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 and 2 more

Abstract read
In one paragraph

Article in Wellcome open research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Ambient Air Pollution and COVID-19 in California.Research report (Health Effects Institute) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Air Pollution as a Risk for Death from Infectious Respiratory Disease.American journal of respiratory and critical care medicine · 2022
    Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Neil PearceFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.ORCID https://orcid.org/0000-0002-9938-7852
Sarah RhodesUniversity of Manchester, Manchester, M13 9PL, UK.ORCID https://orcid.org/0000-0002-5837-801X
Katie StockingUniversity of Manchester, Manchester, M13 9PL, UK.
Lucy PembreyFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.ORCID https://orcid.org/0000-0002-0455-7469
Karin van VeldhovenFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.ORCID https://orcid.org/0000-0001-5298-6148
Elizabeth B BrickleyFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Steve RobertsonFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Donna DavorenFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Vahe NafilyanFaculty of Public Health Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Ben Windsor-ShellardOffice of National Statistics (ONS), London, SWIV 2QQ, UK.
Tony FletcherFaculty of Public Health Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Martie van TongerenUniversity of Manchester, Manchester, M13 9PL, UK.

Funding

Wellcome Trust 205377
6 · The paper itself

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.

Indexed as

COVID-19epidemiologyoccupation

Identifiers

PMID34141900
PMCPMC8188261.2

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.