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Delayed cutaneous reactions developed in 12 patients days after initial injection-related symptoms resolved. The reactions, some as severe as grade 3, resolved in a few days with local therapy, and all 12 patients received the second vaccination; 6 had no recurrence of the local reaction, 3 had similar reactions to the initial injection reaction, and 3 had milder reactions.

To investigate the effectiveness of a daily attestation system used by employees of a multi-institutional academic medical center, which comprised of symptom-screening, self-referrals to the Occupational Health Services team, and/or a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) test. We conducted a retrospective cohort study of all employee attestations and SARS-CoV-2 tests performed between March and June 2020. A large multi-institutional academic medical center, including both inpatient and ambulatory settings. All employees who worked at the study site. Data were combined from the attestation system (COVIDPass), the employee database, and the electronic health records and were analyzed using descriptive statistics including χ2, Wilcoxon, and Kruskal-Wallis tests. We investigated whether an association existed between symptomatic attestations by the employees and the employee testing positive for SARS-CoV-2. After data linkage and cleaning, there were 2,117,298 attestations submitted by 65,422 employees between March and June 2020. Most attestations were asymptomatic (99.9%). The most commonly reported symptoms were sore throat (n = 910), runny nose (n = 637), and cough (n = 570). Among the 2,026 employees who ever attested that they were symptomatic, 905 employees were tested within 14 days of a symptomatic attestation, and 114 (13%) of these tests were positive. The most common symptoms associated with a positive SARS-CoV-2 test were anosmia (23% vs 4%) and fever (46% vs 19%). Daily symptom attestations among healthcare workers identified a handful of employees with COVID-19. Although the number of positive tests was low, attestations may help keep unwell employees off campus to prevent transmissions.

Objective:To describe the incidence of systemic overlap and typical coronavirus disease 2019 (COVID-19) symptoms in healthcare personnel (HCP) following COVID-19 vaccination and association of reported symptoms with diagnosis of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in the context of public health recommendations regarding work exclusion.Design:This prospective cohort study was conducted between December 16, 2020, and March 14, 2021, with HCP who had received at least 1 dose of either the Pfizer-BioNTech or Moderna COVID-19 vaccine.Setting:Large healthcare system in New England.Interventions:HCP were prompted to complete a symptom survey for 3 days after each vaccination. Reported symptoms generated automated guidance regarding symptom management, SARS-CoV-2 testing requirements, and work restrictions. Overlap symptoms (ie, fever, fatigue, myalgias, arthralgias, or headache) were categorized as either lower or higher severity. Typical COVID-19 symptoms included sore throat, cough, nasal congestion or rhinorrhea, shortness of breath, ageusia and anosmia.Results:Among 64,187 HCP, a postvaccination electronic survey had response rates of 83% after dose 1 and 77% after dose 2. Report of ≥3 lower-severity overlap symptoms, ≥1 higher-severity overlap symptoms, or at least 1 typical COVID-19 symptom after dose 1 was associated with increased likelihood of testing positive. HCP with prior COVID-19 infection were significantly more likely to report severe overlap symptoms after dose 1.Conclusions:Reported overlap symptoms were common; however, only report of ≥3 low-severity overlap symptoms, at least 1 higher-severity overlap symptom, or any typical COVID-19 symptom were associated with infection. Work-related restrictions for overlap symptoms should be reconsidered.

Standard adverse event (AE) monitoring only records whether events occur after the intervention, and not whether these events vary over time. To test whether there were statistically distinct time-varying trajectories of AE (e.g., \"side effects\") after an intervention and identify characteristics of individuals associated with these patterns. Group-based trajectory models applied to an observational study of individuals who received one or two doses of a mRNA COVID-19 vaccine (i.e., the intervention). 50,484 healthcare personnel who received their vaccinations within the Mass General Brigham (MGB) healthcare system. Vaccination. Allergic and non-allergic AE for 1-3 days after each of two COVID-19 vaccinations. Trajectories models identified distinct groups with different trajectories after intervention: two groups after the first vaccination and five groups after the second vaccination. These groups differed by demographics, age, prior prescription for epinephrine auto-injectors, prior COVID-19 history, time-of-day of vaccination, and vaccine manufacturer. Several different time-based trajectories after the intervention (e.g., first two COVID-19 vaccinations) were noted; individuals in these groups varied by demographic and clinical criteria. These time-based methods may be able to identify groups at higher risk of future adverse reactions, provide a basis for future studies of the physiology underlying these risk differentials, and improve counseling surrounding interventions associated with AEs. We suggest that trajectory-based methods be added to post-intervention surveillance.

Importance Allergic history in individuals with confirmed anaphylaxis to a messenger RNA (mRNA) COVID-19 vaccine is common. However, the risk factors for allergy symptoms after receiving the vaccine are unknown. Objective To assess the association between self-reported history of high-risk allergy and self-reported allergic reactions after mRNA COVID-19 vaccination of health care employees. Design, Setting, and Participants This cohort study obtained demographic, medical, and vaccine administration data of employees of Mass General Brigham from the institutional electronic health record. Employees who received at least 1 dose of an mRNA COVID-19 vaccine between December 14, 2020, and February 1, 2021, and who completed at least 1 postvaccination symptom survey in the 3 days after vaccination were included. Exposures Self-reported history of high-risk allergy, defined as a previous severe allergic reaction to a vaccine, an injectable medication, or other allergen. Main Outcomes and Measures The primary outcome was 1 or more self-reported allergic reactions in the first 3 days after dose 1 or dose 2 of an mRNA COVID-19 vaccine. Multivariable log binomial regression was used to assess the association between allergic reactions and high-risk allergy status. Results A total of 52 998 health care employees (mean [SD] age, 42 [14] years; 38 167 women [72.0%]) were included in the cohort, of whom 51 706 (97.6%) received 2 doses of an mRNA COVID-19 vaccine and 474 (0.9%) reported a history of high-risk allergy. Individuals with vs without a history of high-risk allergy reported more allergic reactions after receiving dose 1 or 2 of the vaccine (11.6% [n = 55] vs 4.7% [n = 2461]). In the adjusted model, a history of high-risk allergy was associated with an increased risk of allergic reactions (adjusted relative risk [aRR], 2.46; 95% CI, 1.92-3.16), with risk being highest for hives (aRR, 3.81; 95% CI, 2.33-6.22) and angioedema (aRR, 4.36; 95% CI, 2.52-7.54). Conclusions and Relevance This cohort study found that self-reported history of high-risk allergy was associated with an increased risk of self-reported allergic reactions within 3 days of mRNA COVID-19 vaccination. However, reported allergy symptoms did not impede the completion of the 2-dose vaccine protocol among a cohort of eligible health care employees, supporting the overall safety of mRNA COVID-19 vaccine.

Side effects of COVID-19 or other vaccinations may affect an individual’s safety, ability to work or care for self or others, and/or willingness to be vaccinated. Identifying modifiable factors that influence these side effects may increase the number of people vaccinated. In this observational study, data were from individuals who received an mRNA COVID-19 vaccine between December 2020 and April 2021 and responded to at least one post-vaccination symptoms survey that was sent daily for three days after each vaccination. We excluded those with a COVID-19 diagnosis or positive SARS-CoV2 test within one week after their vaccination because of the overlap of symptoms. We used machine learning techniques to analyze the data after the first vaccination. Data from 50,484 individuals (73% female, 18 to 95 years old) were included in the primary analysis. Demographics, history of an epinephrine autoinjector prescription, allergy history category (e.g., food, vaccine, medication, insect sting, seasonal), prior COVID-19 diagnosis or positive test, and vaccine manufacturer were identified as factors associated with allergic and non-allergic side effects; vaccination time 6:00–10:59 was associated with more non-allergic side effects. Randomized controlled trials should be conducted to quantify the relative effect of modifiable factors, such as time of vaccination.

Objectives Underreporting of occupational injuries is well documented, but underreporting patterns may vary by worker characteristics, obscuring disparities. We tested for racial and ethnic differences in injury reporting patterns by comparing injuries reported via research survey and administrative injury database in the same group of healthcare workers in the US. Methods We used data from a cohort of 1568 hospital patient-care workers who were asked via survey whether they had been injured at work during the year prior (self-reported injury; N=244). Using the hospital's injury database, we determined whether the same workers had reported injuries to the hospital's occupational health service during that year (administratively reported injury; N=126). We compared data sources to test for racial and ethnic differences in injury reporting practices. Results In logistic regression models adjusted for demographic and occupational characteristics, black workers' odds of injury as measured by self-report data were 1.91 [95% confidence interval (95% CI) 1.04–3.49] compared with white workers. The same black workers' odds of injury as measured by administrative data were 1.22 (95% CI 0.54–2.77) compared with white workers. Conclusions The undercount of occupational injuries in administrative versus self-report data may be greater among black compared to white workers, leading to underestimates of racial disparities in workplace injury.

Objective: To examine the relationships among low back pain (LBP), inadequate physical activity, and sleep deficiency among patient care workers, and of these outcomes to work context. Methods: A cross-sectional survey of patient care workers (N = 1572, response rate = 79%). Results: A total of 53% reported LBP, 46%, inadequate physical activity, and 59%, sleep deficiency. Inadequate physical activity and sleep deficiency were associated (P = 0.02), but LBP was not significantly related to either. Increased risk of LBP was significantly related to job demands, harassment at work, decreased supervisor support, and job title. Inadequate physical activity was significantly associated with low decision latitude. Sleep deficiency was significantly related to low supervisor support, harassment at work, low ergonomie practices, peopleoriented culture, and job title. Conclusions: These findings point to shared pathways in the work environment that jointly influence multiple health and well-being outcomes.

Throughout the COVID-19 pandemic, multiple policies and guidelines were issued and updated for health care personnel (HCP) for COVID-19 testing and returning to work after reporting symptoms, exposures, or infection. The high frequency of changes and complexity of the policies made it difficult for HCP to understand when they needed testing and were eligible to return to work (RTW), which increased calls to Occupational Health Services (OHS), creating a need for other tools to guide HCP. Chatbots have been used as novel tools to facilitate immediate responses to patients' and employees' queries about COVID-19, assess symptoms, and guide individuals to appropriate care resources. This study aims to describe the development of an RTW chatbot and report its impact on demand for OHS support services during the first Omicron variant surge. This study was conducted at Mass General Brigham, an integrated health care system with over 80,000 employees. The RTW chatbot was developed using an agile design methodology. We mapped the RTW policy into a unified flow diagram that included all required questions and recommendations, then built and tested the chatbot using the Microsoft Azure Healthbot Framework. Using chatbot data and OHS call data from December 10, 2021, to February 17, 2022, we compared OHS resource use before and after the deployment of the RTW chatbot, including the number of calls to the OHS hotline, wait times, call length, and time OHS hotline staff spent on the phone. We also assessed Centers for Disease Control and Prevention data for COVID-19 case trends during the study period. In the 5 weeks post deployment, 5575 users used the RTW chatbot with a mean interaction time of 1 minute and 17 seconds. The highest engagement was on January 25, 2022, with 368 users, which was 2 weeks after the peak of the first Omicron surge in Massachusetts. Among users who completed all the chatbot questions, 461 (71.6%) met the RTW criteria. During the 10 weeks, the median (IQR) number of daily calls that OHS received before and after deployment of the chatbot were 633 (251-934) and 115 (62-167), respectively (U=163; P<.001). The median time from dialing the OHS phone number to hanging up decreased from 28 minutes and 22 seconds (IQR 25:14-31:05) to 6 minutes and 25 seconds (IQR 5:32-7:08) after chatbot deployment (U=169; P<.001). Over the 10 weeks, the median time OHS hotline staff spent on the phone declined from 3 hours and 11 minutes (IQR 2:32-4:15) per day to 47 (IQR 42-54) minutes (U=193; P<.001), saving approximately 16.8 hours per OHS staff member per week. Using the agile methodology, a chatbot can be rapidly designed and deployed for employees to efficiently receive guidance regarding RTW that complies with the complex and shifting RTW policies, which may reduce use of OHS resources.

OBJECTIVE:To test the feasibility of a multicomponent pilot intervention to improve worker safety and wellness in two Boston hospitals. METHODS:A 3-month intervention was conducted on seven hospital units. Pre- (374 workers) and postsurveys (303 workers) assessed changes in safety/ergonomic behaviors and practices, and social support. Wellness outcomes included self-reported pain/aching in specific body areas (musculoskeletal disorders or MSDs) and physical activity (PA). RESULTS:Pain was reported frequently (81%), and PA averaged 4 hours per week. There was a postintervention increase in safe patient handling (P < 0.0001), safety practices (P = 0.0004), ergonomics (P = 0.009), and supervisor support (P = 0.01), but no changes in MSDs or PA. CONCLUSIONS:Safe patient handling, ergonomics, and safety practices are good targets for worker safety and wellness interventions; longer intervention periods may reduce the risk of MSDs.