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Objective: This study aimed to evaluate the long-term, symptomatic recovery of healthcare workers from acute COVID-19 infections up to 3 years after the initial COVID-19 outbreak., Methods: A cross-sectional study was performed among employees of a community-based healthcare system in Massachusetts who had a recorded positive COVID-19 test. Survey responses were collected between September 2022 and January 2023. The survey included validated questionnaires: WHOQOL-BREF, EQ-5D-5 L, DASS-21, FCV-19S, K6+, and the Insomnia Severity Index. We compared the long-COVID (ie, symptoms lasting >28 days) and non-long-COVID groups., Results: Among the 280 respondents (15.2% response rate), those with long COVID (73.4%) reported significantly worse quality of life and greater levels of depression, anxiety, and stress metrics. However, no significant difference was found between the two groups' fear of COVID-19., Conclusions: Targeted support for healthcare workers with prolonged symptoms after COVID-19 is warranted., Competing Interests: Lan, Zalaquett, Lutchman, Iliaki, Buley, Nathan, Prieto, and Kales have no relationships/conditions/circumstances that present potential conflict of interest., (Copyright © 2024 American College of Occupational and Environmental Medicine.)

Background: Data on COVID-19 vaccine effectiveness (VE) among healthcare workers (HCWs) during periods of delta variant predominance are limited., Methods: We followed a population of urban Massachusetts HCWs (45% non-White) subject to epidemiologic surveillance. We accounted for covariates such as demographics and community background infection incidence, as well as information bias regarding COVID-19 diagnosis and vaccination status., Results: During the study period (December 16, 2020 to September 30, 2021), 4615 HCWs contributed to a total of 1,152,486 person-days at risk (excluding 309 HCWs with prior infection) and had a COVID-19 incidence rate of 5.2/10,000 (114 infections out of 219,842 person-days) for unvaccinated person-days and 0.6/10,000 (49 infections out of 830,084 person-days) for fully vaccinated person-days, resulting in an adjusted VE of 82.3% (95% CI 75.1-87.4%). For the secondary analysis limited to the period of delta variant predominance in Massachusetts (i.e., July 1 to September 30, 2021), we observed an adjusted VE of 76.5% (95% CI 40.9-90.6%). Independently, we found no re-infection among those with prior COVID-19, contributing to 74,557 re-infection-free person-days, adding to the evidence base for the robustness of naturally acquired immunity., Conclusions: We found a VE of 76.5% against the delta variant. Our work also provides further evidence of naturally acquired immunity., (© 2022. The Author(s).)

Objective: To better understand coronavirus disease 2019 (COVID-19) transmission among healthcare workers (HCWs), we investigated occupational and nonoccupational risk factors associated with cumulative COVID-19 incidence among a Massachusetts HCW cohort., Design, Setting, and Participants: The retrospective cohort study included adult HCWs in a single healthcare system from March 9 to June 3, 2020., Methods: The SARS-CoV-2 nasopharyngeal RT-PCR results and demographics of the study participants were deidentified and extracted from an established occupational health, COVID-19 database at the healthcare system. HCWs from each particular job grouping had been categorized into frontline or nonfrontline workers. Incidence rate ratios (IRRs) and odds ratios (ORs) were used to compare subgroups after excluding HCWs involved in early infection clusters before universal masking began. A sensitivity analysis was performed comparing jobs with the greatest potential occupational risks with others., Results: Of 5,177 HCWs, 152 (2.94%) were diagnosed with COVID-19. Affected HCWs resided in areas with higher community attack rates (median, 1,755.2 vs 1,412.4 cases per 100,000; P < .001; multivariate-adjusted IRR, 1.89; 95% CI, 1.03-3.44 comparing fifth to first quintile of community rates). After multivariate adjustment, African-American and Hispanic HCWs had higher incidence of COVID-19 than non-Hispanic white HCWs (IRR, 2.78; 95% CI, 1.78-4.33; and IRR, 2.41, 95% CI, 1.42-4.07, respectively). After adjusting for race and residential rates, frontline HCWs had a higher IRR (1.73, 95% CI, 1.16-2.54) than nonfrontline HCWs overall, but not within specific job categories nor when comparing the highest risk jobs to others., Conclusions: After universal masking was instituted, the strongest risk factors associated with HCW COVID-19 infection were residential community infection rate and race.

SARS-CoV-2 antibody seroprevalence among health-care workers (HCW) can assess past exposure and possible immunity, which varies across different regions, populations and times. We investigated the seroprevalence among HCW in Massachusetts (a region suffering high COVID-19 mortality) at the end of first wave of the SARS-CoV-2 pandemic. All HCW at Cambridge Health Alliance were invited to participate in this cross-sectional survey in June 2020. Those who volunteered, consented and provided a blood sample were included. Dried blood specimens from finger-prick sampling collected either at home by each HCW or onsite by the study team were analyzed for anti-SARS-CoV-2 IgM and IgG to the virus' receptor binding domain, using an enzyme-linked immunosorbent assay. IgM and IgG antibody abundance were categorized based on the number of standard deviations above the cross-reacting levels found in existing, pre-pandemic blood samples previously obtained by the Ragon Institute and analyzed by the Broad Institute (Cambridge, MA). Seroprevalence estimates were made based on 'positive' IgM or IgG using 'low' (>6 SD), 'medium' (>4.5 SD), and 'high' prevalence cutoffs (>3 SD).A total of 433 out of 5,204 eligible HCWs consented and provided samples. Participating HCWs had a lower cumulative incidence (from the start of the pandemic up to the bloodspot collections) of SARS-CoV-2 RT-PCR positivity (1.85%) compared to non-participants (3.29%). The low, medium, and high seroprevalence estimates were 8.1%, 11.3%, and 14.5%, respectively. The weighted estimates based on past PCR positivity were 13.9%, 19.4%, and 24.9%, respectively, for the entire healthcare system population after accounting for participation bias.

Background: Healthcare workers (HCWs) and other essential workers are at risk of occupational infection during the COVID-19 pandemic. Several infection control strategies have been implemented. Evidence shows that universal masking can mitigate COVID-19 infection, though existing research is limited by secular trend bias., Aims: To investigate the effect of hospital universal masking on COVID-19 incidence among HCWs compared to the general population., Methods: We compared the 7-day average incidence rates between a Massachusetts (USA) healthcare system and Massachusetts residents statewide. The study period was from 17 March (the date of first incident case in the healthcare system) to 6 May (the date Massachusetts implemented public masking). The healthcare system implemented universal masking on 26 March, we allotted a 5-day lag for effect onset and peak COVID-19 incidence in Massachusetts was 20 April. Thus, we categorized 17-31 March as the pre-intervention phase, 1-20 April the intervention phase and 21 April to 6 May the epidemic decline phase. Temporal incidence trends (i.e. 7-day average slopes) were compared using standardized coefficients from linear regression models., Results: The standardized coefficients were similar between the healthcare system and the state in both the pre-intervention and epidemic decline phases. During the intervention phase, the healthcare system's epidemic slope became negative (standardized β: -0.68, 95% CI: -1.06 to -0.31), while Massachusetts' slope remained positive (standardized β: 0.99, 95% CI: 0.94 to 1.05)., Conclusions: Universal masking was associated with a decreasing COVID-19 incidence trend among HCWs, while the infection rate continued to rise in the surrounding community., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)