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      Occupational differences in SARS-CoV-2 infection: analysis of the UK ONS COVID-19 infection survey

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          Abstract

          Background

          Concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain occupations with the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic.

          Methods

          Analysis of cohort data from the UK Office of National Statistics COVID-19 Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression were used to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions.

          Results

          Based on 3 910 311 observations (visits) from 312 304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared with non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates.

          Conclusions

          Elevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted.

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          Most cited references35

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          Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study

          Summary Background Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk. Methods We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Symptom Study smartphone application (app) from March 24 (UK) and March 29 (USA) to April 23, 2020. Participants were voluntary users of the app and at first use provided information on demographic factors (including age, sex, race or ethnic background, height and weight, and occupation) and medical history, and subsequently reported any COVID-19 symptoms. We used Cox proportional hazards modelling to estimate multivariate-adjusted hazard ratios (HRs) of our primary outcome, which was a positive COVID-19 test. The COVID Symptom Study app is registered with ClinicalTrials.gov, NCT04331509. Findings Among 2 035 395 community individuals and 99 795 front-line health-care workers, we recorded 5545 incident reports of a positive COVID-19 test over 34 435 272 person-days. Compared with the general community, front-line health-care workers were at increased risk for reporting a positive COVID-19 test (adjusted HR 11·61, 95% CI 10·93–12·33). To account for differences in testing frequency between front-line health-care workers and the general community and possible selection bias, an inverse probability-weighted model was used to adjust for the likelihood of receiving a COVID-19 test (adjusted HR 3·40, 95% CI 3·37–3·43). Secondary and post-hoc analyses suggested adequacy of PPE, clinical setting, and ethnic background were also important factors. Interpretation In the UK and the USA, risk of reporting a positive test for COVID-19 was increased among front-line health-care workers. Health-care systems should ensure adequate availability of PPE and develop additional strategies to protect health-care workers from COVID-19, particularly those from Black, Asian, and minority ethnic backgrounds. Additional follow-up of these observational findings is needed. Funding Zoe Global, Wellcome Trust, Engineering and Physical Sciences Research Council, National Institutes of Health Research, UK Research and Innovation, Alzheimer's Society, National Institutes of Health, National Institute for Occupational Safety and Health, and Massachusetts Consortium on Pathogen Readiness.
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            Collider bias undermines our understanding of COVID-19 disease risk and severity

            Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage.
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                Author and article information

                Journal
                J Epidemiol Community Health
                J Epidemiol Community Health
                jech
                jech
                Journal of Epidemiology and Community Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                0143-005X
                1470-2738
                October 2022
                11 July 2022
                11 July 2022
                : 76
                : 10
                : 841-846
                Affiliations
                [1 ] departmentCentre for Biostatistics , University of Manchester , Manchester, UK
                [2 ] departmentEpidemiology and Population Health , London School of Hygiene & Tropical Medicine , London, UK
                [3 ] Institute of Occupational Medicine , Edinburgh, UK
                [4 ] departmentMRC/CSO Social & Public Health Sciences Unit , University of Glasgow , Glasgow, UK
                [5 ] departmentCentre for Occupation and Environmental Health , The University of Manchester , Manchester, UK
                Author notes
                [Correspondence to ] Ms Sarah Rhodes, Centre for Biostatistics, University of Manchester, Manchester M13 9PL, UK; Sarah.A.Rhodes@ 123456manchester.ac.uk
                Author information
                http://orcid.org/0000-0002-5837-801X
                http://orcid.org/0000-0001-8712-736X
                http://orcid.org/0000-0001-6593-9092
                Article
                jech-2022-219101
                10.1136/jech-2022-219101
                9484374
                35817467
                968da105-c02b-4b05-a894-094e0ede2381
                © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 01 April 2022
                : 28 June 2022
                Funding
                Funded by: NRS;
                Award ID: SCAF/15/02
                Funded by: FundRef http://dx.doi.org/10.13039/501100000869, Health and Safety Executive;
                Award ID: N/A
                Funded by: FundRef http://dx.doi.org/10.13039/100012095, Scottish Government;
                Award ID: SPHSU17
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_00022/2
                Categories
                Original Research
                1506
                2474
                Custom metadata
                unlocked
                free

                Public health
                occupational health,covid-19,epidemiology
                Public health
                occupational health, covid-19, epidemiology

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