Evidence map›Paper›PMID 36372668›Full record

ArticleVaccine2022

Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study.

Sarah Beale, Rachel Burns, Isobel Braithwaite, Thomas Byrne, Wing Lam Erica Fong, Ellen Fragaszy, Cyril Geismar, Susan Hoskins, Jana Kovar, Annalan M D Navaratnam and 7 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
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, 16 citations in OpenAlex.

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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

17 authors at 3 institutions in 1 country.

Sarah BealeCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK. Electronic address: sarah.beale.19@ucl.ac.uk.
Rachel BurnsCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Isobel BraithwaiteCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Thomas ByrneCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Wing Lam Erica FongCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Ellen FragaszyCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
Cyril GeismarCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
Susan HoskinsInstitute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
Jana KovarInstitute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
Annalan M D NavaratnamCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
Vincent NguyenCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
Parth PatelCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Alexei YavlinskyCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Martie Van TongerenCentre for Occupational and Environmental Health, University of Manchester, Manchester M13 9PL, UK.
Robert W AldridgeCentre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK.
Andrew HaywardInstitute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
Virus Watch Collaborative
University College London · GBHealth Data Research UK · GBUniversity of Manchester · GB

Funding

Medical Research Council MC_PC 19,070Medical Research Council MC_PC_19070Medical Research Council MR/N013867/1Medical Research Council MR/V028375/1Wellcome Trust 206602
6 · The paper itself

Abstract

backgroundOccupational disparities in COVID-19 vaccine uptake can impact the effectiveness of vaccination programmes and introduce particular risk for vulnerable workers and those with high workplace exposure. This study aimed to investigate COVID-19 vaccine uptake by occupation, including for vulnerable groups and by occupational exposure status.

methodsWe used data from employed or self-employed adults who provided occupational information as part of the Virus Watch prospective cohort study (n = 19,595) and linked this to study-obtained information about vulnerability-relevant characteristics (age, medical conditions, obesity status) and work-related COVID-19 exposure based on the Job Exposure Matrix. Participant vaccination status for the first, second, and third dose of any COVID-19 vaccine was obtained based on linkage to national records and study records. We calculated proportions and Sison-Glaz multinomial 95% confidence intervals for vaccine uptake by occupation overall, by vulnerability-relevant characteristics, and by job exposure.

findingsVaccination uptake across occupations ranged from 89-96% for the first dose, 87-94% for the second dose, and 75-86% for the third dose, with transport, trade, service and sales workers persistently demonstrating the lowest uptake. Vulnerable workers tended to demonstrate fewer between-occupational differences in uptake than non-vulnerable workers, although clinically vulnerable transport workers (76%-89% across doses) had lower uptake than several other occupational groups (maximum across doses 86%-96%). Workers with low SARS-CoV-2 exposure risk had higher vaccine uptake (86%-96% across doses) than those with elevated or high risk (81-94% across doses).

interpretationDifferential vaccination uptake by occupation, particularly amongst vulnerable and highly-exposed workers, is likely to worsen occupational and related socioeconomic inequalities in infection outcomes. Further investigation into occupational and non-occupational factors influencing differential uptake is required to inform relevant interventions for future COVID-19 booster rollouts and similar vaccination programmes.

Indexed as

COVID-19COVID-19 VaccinesAdultHumansProspective StudiesSARS-CoV-2VaccinationCOVID-19 VaccinesCOVID-19OccupationSARS-CoV-2Vaccination uptake

Identifiers

PMID36372668
PMCPMC9637514
OpenAlexW4308329653

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.