COVID-19 prevalence by 5-year age band and sex (unadjusted).

COVID-19 prevalence by 5-year age band and sex (unadjusted).</p

Predicted probability of testing positive for COVID-19 by work sector, sex and month.

Note: Estimates for geographical location, age, ethnicity, household size, work location and whether an individual had travelled abroad.</p

Predicted probability of testing positive for COVID-19 by work status, sex and month.

Note: Estimates are adjusted for geographical location, age, ethnicity, household size and whether an individual had travelled abroad.</p

COVID-19 prevalence by work sector and sex (unadjusted).

Note: estimate for females employed in the armed forces excluded due to counts <10 to preserve ONS data disclosure standards.</p

Percentage of tests that were positive for COVID-19 by week of year and sex (unadjusted).

(Note: figures in first two weeks of August were redacted due to disclosive numbers (i.e., <10 positive tests. Point is estimated percentage, with error bars the 95% confidence intervals).</p

Model summary for analysing COVID-19 risk by socio-demographic features including occupational group for adults who work.

Model summary for analysing COVID-19 risk by socio-demographic features including occupational group for adults who work.</p

Appendix.

The COVID-19 pandemic has reinforced, amplified and created new health inequalities. Examining how COVID-19 prevalence varies by measures of work and occupation may help to understand these inequalities. The aim of the study is to evaluate how occupational inequalities in the prevalence of COVID-19 varies across England and their possible explanatory factors. We used data for 363,651 individuals (2,178,835 observations) aged 18 years and over between 1st May 2020 and 31st January 2021 from the Office for National Statistics Covid Infection Survey, a representative longitudinal survey of individuals in England. We focus on two measures of work; employment status for all adults, and work sector of individuals currently working. Multi-level binomial regression models were used to estimate the likelihood of testing positive of COVID-19, adjusting for known explanatory covariates. 0.9% of participants tested positive for COVID-19 over the study period. COVID-19 prevalence was higher among adults who were students or furloughed (i.e., temporarily not working). Among adults currently working, COVID-19 prevalence was highest in adults employed in the hospitality sector, with higher prevalence for individuals employed in transport, social care, retail, health care and educational sectors. Inequalities by work were not consistent over time. We find an unequal distribution of infections relating to COVID-19 by work and employment status. While our findings demonstrate the need for greater workplace interventions to protect employees tailored to their specific work sector needs, focusing on employment alone ignores the importance of SARS-CoV-2 transmission outside of employed work (i.e., furloughed and student populations).</div

COVID-19 prevalence by work status and sex (unadjusted).

COVID-19 prevalence by work status and sex (unadjusted).</p

COVID-19 prevalence by ethnic group and sex (unadjusted).

COVID-19 prevalence by ethnic group and sex (unadjusted).</p

Model summary for analysing COVID-19 risk by socio-demographic features including occupational status.

Model summary for analysing COVID-19 risk by socio-demographic features including occupational status.</p