Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales

Abstract

Background Workers across different occupations vary in their risk of SARS-CoV-2 infection, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase. Methods Data from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR). Results Increased risk was seen in nurses (aRR = 1.44, 1.25–1.65; AF = 30%, 20–39%), doctors (aRR = 1.33, 1.08–1.65; AF = 25%, 7–39%), carers (1.45, 1.19–1.76; AF = 31%, 16–43%), primary school teachers (aRR = 1.67, 1.42- 1.96; AF = 40%, 30–49%), secondary school teachers (aRR = 1.48, 1.26–1.72; AF = 32%, 21–42%), and teaching support occupations (aRR = 1.42, 1.23–1.64; AF = 29%, 18–39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020—May 2021) and attenuated later (June—October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves. Conclusions Occupational differences in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.

Clinical characteristics of COVID-19 patients treated in emergency COVID-19 hospitals in Vietnam: Experience from Phutho province, Vietnam

“…In this study, the median age of the study population was 30.0 years (interquartile range [IQR]: 14-41.2). Notably, the unvaccinated cohort were mainly under 18 years old, while the vaccinated groups were over 19 years old, which resulted in a significantly higher median age compared to the unvaccinated cohort (36 [IQR: [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46]] and 36.5 [IQR: 30-47.4] vs. 13.0 [IQR: 9-26], p<0.001). The results were similar to other reported studies which showed that most COVID-19 infections occurred in the 19-30-year age groups [7,8].…”

“…Other studies showed that healthcare staff had higher potential for getting the disease than the others because of exposure to infection in the hospital environment 28 , 29 . Further investigations should be conducted to explore the specific factors contributing to the increased risk among these occupational groups 30 .…”

“…The median age of the patients was 30.0 (IQR 14-41.2). The vaccinated cohort was significantly older than the unvaccinated cohort (median [IQR 25-75%]: 36 [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46] and 36.5 [30-47.4] vs 13.0 [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], p<0.001), with comorbidities significantly more frequent in the vaccinated groups: hypertension, diabetes mellitus, COPD, taking corticosteroids, smoking and alcohol were all significant at p<0.05. Clinical presentations were significantly presented in the unvaccinated group with 548 cases versus 419 (1 st dose) and 330 cases (2 nd dose), respectively.…”

COVID-19 in City Council Civil Servants, 1 March 2020–31 January 2023: Risk of Infection, Reinfection, Vaccine Effectiveness and the Impact of Heterologous Triple Vaccination

“…COVID-19 infections and mortality reportedly varied over time and by occupation during the pandemic [ 4 , 5 , 6 , 12 , 13 , 14 , 15 , 16 , 17 ], being influenced by a number of factors, including vaccine uptake, indoor versus outdoor work environment, poor ventilation, exposure to contaminated surfaces, number of people in the worksite, social distancing, efficiency of contract tracing and observation of non-pharmaceutical risk reduction measures [ 5 , 6 , 18 , 19 ].…”

Long-term outcomes of SARS-CoV-2 variants and other respiratory infections: evidence from the Virus Watch prospective cohort in England

“…Occupation was classified into the following categories triangulating occupation, exposure risk, and employment status: higher exposure risk occupation, lower exposure risk occupation, retired, not in employment, and unknown/other status. Further details of occupational categories are provided in the , and details of the occupational coding process are provided in related Virus Watch analyses [ 35 ].…”