Excess risk of SARS-CoV-2 infection among in-person nonhealthcare workers in six states, September 2020-June 2021

Extending a COVID-19 Job Exposure Matrix: The SARS-CoV-2 or COVID-19 Job Exposure Matrix Module (SCoVJEM Module) for Population-Based Studies

The risk of workplace SARS-CoV-2 transmission is increased by aerosolization or droplets and increased respiratory rates or increased viral stability in cold environments. Few methods exist for identifying occupational risks of SARS-CoV-2 transmission. We extended a SARS-CoV-2 job exposure matrix (JEM) into four dimensions, talking loudly (Loud) (very loud, loud, somewhat loud, or not), physical activity (PA) (high, medium or low), and cold (Cold) (cold or not) and hot environments (Hot) (hot or not), using data from the Occupational Information Network (O*NET) and a priori questions for each and noise measurements for 535 occupations. We classified 70%+ occupations as loud or very loud (74.6%); whereas 13.8% were high PA, 18.5% exposed to cold, and 23.7% exposed to hot temperatures. Applying to California 2019 workforce data to explore by race/ethnicity and sex, we found 21.2% worked in very loud and 12.6% in high PA occupations and 15.7% in cold and 17.8% hot environments. Latino workers were highly represented in very loud and high PA levels among farming (83.8 and 78.4%) and construction (58.7% and 50.3%). More males worked in each highest exposure level than females. This JEM provides aerosol transmission proxies for COVID-19 risk factors and merits investigation as a tool for epidemiologic studies.

Prevalence of COVID-19 and Long COVID by Industry and Occupation: Behavioral Risk Factor Surveillance System 2022

BACKGROUND

Workers in healthcare and other essential occupations had elevated risks for COVID-19 infection early in the pandemic. No survey of U.S. workers to date has comprehensively assessed the prevalence of both COVID-19 and Long COVID across industries and occupations (I&O) at a detailed level.

METHODS

Behavioral Risk Factor Surveillance System data for 2022 from 39 states, Guam, and the U.S. Virgin Islands were used to estimate prevalence of self-reported history of COVID-19 and Long COVID, as well as the prevalence of Long COVID among those reporting prior COVID-19, by broad and detailed I&O. Adjusted prevalence ratios were used to compare outcome prevalence in each I&O to prevalence among all other workers combined.

RESULTS

By broad I&O, workers in healthcare, protective services, and education had elevated prevalences of COVID-19. The prevalence of Long COVID was elevated in healthcare and protective service but not education workers. Detailed I&O with significantly elevated prevalences of COVID-19 but not Long COVID included Dairy Product Manufacturing industry workers and subsets of mining workers. Both COVID-19 and Long COVID were elevated among bartenders/drinking places and personal care and appearance workers. The prevalence of Long COVID was elevated among farmworkers who reported having had COVID-19.

CONCLUSIONS

Industries and occupations with elevated levels of COVID-19 or Long COVID in this study may warrant increased measures to prevent transmission of airborne respiratory viruses. Accommodations are a key component for supporting workers in all workplaces. This new information about the distribution of Long COVID by I&O suggests where employer understanding and implementation of tailored workplace supports and accommodations are most needed to support continued employment of affected workers.

Occupational and non-occupational factors of post-COVID-19 condition: a cross-sectional survey in the French general working population

Introduction

Although the working population carries the greatest burden of long COVID, occupational and non-occupational factors of the condition have not yet been well documented in this population. The aim of this study was to investigate these factors.

Methods

A nationwide random sampling cross-sectional survey was conducted among the adult population in mainland France after the large Omicron waves in the autumn of 2022. Post-COVID-19 condition (PCC) was defined according to the WHO. Associations of occupational and non-occupational factors with PCC were tested in a conceptual model accounting for the relationships between these factors and considering two control groups (previously infected participants without PCC and participants with no reported or diagnosed SARS-CoV-2 infection). Interactions between occupational and non-occupational factors were considered.

Results

The survey included 1131 working adults. PCC was positively associated with reported infection while providing care (prevalence ratio (PR)=2.06 (95% CI 1.08 to 3.94)), being in contact with a colleague (PR=1.61 (95% CI 1.04 to 2.48)) and increased workload (PR=2.85 (95% CI 1.12 to 7.24)), whereas it was negatively associated with reported infection while being in contact with the public or clients (PR=0.23 (95% CI 0.07 to 0.76)). Several non-occupational factors were associated with PCC: sex, household size, household financial satisfaction, number of pre-existing chronic conditions, anxiety, injury sequelae and perceived SARS-CoV-2 infection severity. No interactions were found between these factors.

Conclusions

Reducing the burden of long COVID in the working population requires public health strategies that consider a wide spectrum of factors, including work conditions in a broad sense. Specific attention should be given to the most vulnerable workers accumulating such factors.

Occupational and industry prevalence of new long-term symptoms within American Red Cross blood donors with and without history of SARS-CoV-2 infection

PURPOSE

Limited information is known about the burden of Long COVID by occupation and industry. This study compares the occurrence of self-reported new long-term symptoms lasting 4 weeks or longer among blood donors with and without prior SARS-CoV-2 infection by occupation and industry.

METHODS

The American Red Cross invited blood donors 18 years and older who donated during May 4-December 31, 2021 to participate in online surveys. New long-term symptoms lasting 4 weeks or longer were assessed by self-reported occurrence of any of 35 symptoms since March 2020. SARS-CoV-2 infection status was determined by serological testing and self-report. We describe the prevalence of new long-term symptoms by SARS-CoV-2 infection status. We calculate the difference in reported new long-term symptoms by SARS-CoV-2 infection status within occupation and industry categories.

RESULTS

Data were collected from 27,907 employed adults - 9763 were previously infected and 18,234 were never infected with SARS-CoV-2. New long-term symptoms were more prevalent among those previously infected compared to the never-infected respondents (45% vs 24%, p < 0.05). Among all respondents, new long-term symptoms by occupation ranged from 26% (installation, maintenance, and repair) to 41% (healthcare support) and by industry ranged from 26% (mining) to 55% (accommodation and food services). New long-term neurological and other symptoms were commonly reported by those previously infected with SARS-CoV-2.

DISCUSSION

New long-term symptoms are more prevalent among certain occupation and industry groups, which likely reflects differential exposure to SARS-CoV-2. These findings highlight potential need for workplace accommodations in a variety of occupational settings to address new long-term symptoms.

SARS-CoV-2 infection among Colorado adults working outside the home: Occupation, race and ethnicity and mask use

OBJECTIVES

The workplace is an important setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure and transmission. Using data from a large case-control study in Colorado during 2021 and 2022, we aimed to evaluate working outside the home and SARS-CoV-2 infection, the racial and ethnic distribution of workers in occupations associated with infection, and workplace face mask use.

METHODS

Cases were Colorado adults with a positive SARS-CoV-2 test by reverse transcription-polymerase chain reaction (RT-PCR) reported to Colorado's COVID-19 surveillance system selected from surveillance data ≤12 days after their specimen collection date. Control participants were randomly selected adult Coloradans with a RT-PCR-confirmed negative SARS-CoV-2 test result reported to the same surveillance system.

RESULTS

Working outside the home was associated with infection (odds ratio [OR] = 1.46, 95% confidence interval [CI]: 1.39-1.54). Among participants working outside the home, "Food Preparation and Serving Related" (aOR = 2.35, 95% CI: 1.80-3.06), "Transportation and Material Moving" (aOR = 2.09, 95% CI: 1.62-2.69), "Construction and Extraction" (aOR = 1.88, 95% CI: 1.36-2.59), "Protective Service" (aOR = 1.60, 95% CI: 1.15-2.24), and "Sales and Related" (aOR = 1.44, 95% CI: 1.22-1.69) were occupational categories most strongly associated with infection. American Indian/Alaskan Native, Black, and Hispanic/Latino participants were more likely than others to work in occupational categories with the highest odds of infection (p < 0.05). Cases were less likely than controls to report always wearing a mask (31.9% vs. 41.5%) and wearing a KN95/N95/KF94 mask (16.8% vs. 27.2%) at work.

CONCLUSIONS

These findings emphasize the importance of occupation and workplace mask use in the COVID-19 pandemic and its disproportionate racial/ethnic impact on workers.

Social Vulnerabilities Among Hired Migrant and Seasonal Farmworkers During COVID-19: The Need for Employment-Based Indicators

OBJECTIVES

This study aimed to explore farmworkers' experiences of social vulnerability during the peak period of the COVID-19 pandemic.

METHODS

Telephone surveys of 63 migrant and seasonal farmworkers across three major agricultural areas in Florida were conducted. The survey, designed and disseminated with critical support from a statewide farmworker membership and advocacy organization, included items related to social and occupational precarity and a suite of demographic conditions, including specific employment-based indicators and categories. Data were analyzed with SPSS using a series of statistical significance tests including Pearson's Chi-Square, Fisher's Exact, T-tests, and Mann-Whitney U. An open-ended question regarding employment precarity was also analyzed for frequencies of responses pertaining to a set of descriptive categories.

RESULTS

Survey findings demonstrated a high degree of social vulnerability among the farmworker sample, with notable variation in the type and severity of vulnerability and risk exposure across employment-based indicators and occupational categories. For example, a cross-industry comparison between vegetable field workers and greenhouse nursery workers revealed a disparity in COVID-exposure risk through commuting characteristics, as 43% of vegetable field workers used shared, employer-provided transport, while 68% of nursery workers used personal vehicles.

CONCLUSION

While previous research has broadly established the extreme precarity of migrant and seasonal farmworkers during the peak COVID-19 period, the variability of experience, exposure to risk, and social vulnerability between farmworkers representing distinct employment-based indicators and occupational categories demonstrated in this study contributes to widening awareness of the importance of assessing farmworker experiences at a more granular level. In addition to delineating social vulnerability across key demographic categories, cross-industry comparisons between farmworkers revealed significant discrepancies in risk and vulnerability to COVID-19. Future research that further explores this variability may reveal opportunities to improve disaster-relief planning and mitigate social vulnerability in future disaster scenarios. The importance of surveying the vulnerability of worker populations, aside from geographic communities, is highlighted.

Occupation and COVID-19: Lessons From the Pandemic

Recognition that an individual's job could affect the likelihood of contracting coronavirus disease 2019 created challenges for investigators who sought to understand and prevent the transmission of severe acute respiratory syndrome coronavirus 2. Considerable research resources were devoted to separating the effects of occupational from nonoccupational risk factors. This commentary highlights results from studies that adjusted for multiple nonoccupational risk factors while estimating the effects of occupations and occupational risk factors. Methods used in these studies will prove useful in future infectious disease epidemics and pandemics and may potentially enrich studies of other occupational infectious and noninfectious respiratory diseases.

COVID-19 mortality among Massachusetts workers and the association with telework ability, 2020

BACKGROUND

Working outside the home put some workers at risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure and might partly explain elevated coronavirus disease 2019 (COVID-19) mortality rates in the first months of the pandemic in certain groups of Massachusetts workers. To further investigate this premise, we examined COVID-19 mortality among Massachusetts workers, with a specific focus on telework ability based on occupation.

METHODS

COVID-19-associated deaths between January 1 and December 31, 2020 among Massachusetts residents aged 18-64 years were analyzed. Deaths were categorized into occupation-based quadrants (Q) of telework ability. Age-adjusted rates were calculated by key demographics, industry, occupation, and telework quadrant using American Community Survey workforce estimates as denominators. Rate ratios (RRs) and 95% confidence intervals comparing rates for quadrants with workers unlikely able to telework (Q2, Q3, Q4) to that among those likely able to telework (Q1) were calculated.

RESULTS

The overall age-adjusted COVID-19-associated mortality rate was 26.4 deaths per 100,000 workers. Workers who were male, Black non-Hispanic, Hispanic, born outside the US, and with lower than a high school education level experienced the highest rates among their respective demographic groups. The rate varied by industry, occupation and telework quadrant. RRs comparing Q2, Q3, and Q4 to Q1 were 0.99 (95% confidence interval [CI]: 0.8-1.2), 3.2 (95% CI: 2.6-3.8) and 2.5 (95% CI: 2.0-3.0), respectively.

CONCLUSION

Findings suggest a positive association between working on-site and COVID-19-associated mortality. Work-related factors likely contributed to COVID-19 among Massachusetts workers and should be considered in future studies of COVID-19 and similar diseases.