Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses

Author:

Pearce NeilORCID,Rhodes SarahORCID,Stocking Katie,Pembrey LucyORCID,van Veldhoven KarinORCID,Brickley Elizabeth B.,Robertson Steve,Davoren Donna,Nafilyan Vahe,Windsor-Shellard Ben,Fletcher Tony,van Tongeren Martie

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.

Funder

Wellcome Trust

Colt Foundation

United Kingdom Government

Publisher

F1000 Research Ltd

Subject

General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)

Reference46 articles.

1. Comparisons between countries are essential for the control of COVID-19.;N Pearce;Int J Epidemiol.,2020

2. Accurate statistics on Covid-19 are essential for policy guidance and decisions.;N Pearce;Am J Public Health.,2020

3. Covid-19 and health at work;R Agius;Occup Med (Lond).,2020

4. The Covid-19 (Coronavirus) pandemic: consequence for occupational health.;L Burdorf;Scand J Work Environ Health.,2020

5. The COVID-19 pandemic: major risks to healthcare and other workers on the front line.;M Sim;Occup Environ Med.,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3