Background: Work-related exposures play an important role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, yet few studies have compared SARS-CoV-2 expsoure risk across occupations and industries.
Methods: During September 2020 to May 2021, the Wisconsin Department of Health Services collected occupation and industry data as part of routine coronavirus disease 2019 (COVID-19) case investigations. Adults aged 18-64 years with confirmed or probable COVID-19 in Wisconsin were assigned standardized occupation and industry codes. Cumulative incidence rates were weighted for non-response and calculated using full-time equivalent (FTE) workforce denominators from the 2020 American Community Survey.
Results: An estimated 11.6% of workers (347 013 of 2.98 million) in Wisconsin, ages 18-64 years, had COVID-19 from September 2020 to May 2021. The highest incidence by occupation (per 100 FTE) occurred among personal care and services workers (22.1), healthcare practitioners and support staff (20.7), and protective services workers (20.7). High-risk sub-groups included nursing assistants and personal care aides (28.8), childcare workers (25.8), food and beverage service workers (25.3), personal appearance workers (24.4), and law enforcement workers (24.1). By industry, incidence was highest in healthcare (18.6); the highest risk sub-sectors were nursing care facilities (30.5) and warehousing (28.5).
Conclusions: This analysis represents one of the most complete examinations to date of COVID-19 incidence by occupation and industry. Our approach demonstrates the value of standardized occupational data collection by public health and may be a model for improved occupational surveillance elsewhere. Workers at higher risk of SARS-CoV-2 exposure may benefit from targeted workplace COVID-19 vaccination and mitigation efforts.
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http://dx.doi.org/10.1093/cid/ciac586 | DOI Listing |
BMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
View Article and Find Full Text PDFBMJ Open
December 2024
Department of Exercise and Sport Science, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Background: Sedentary behaviour (SB) is detrimental to cardiometabolic disease (CMD) risk, which can begin in young adulthood. To devise effective SB-CMD interventions in young adults, it is important to understand which context-specific SB (CS-SB) are most detrimental for CMD risk, the lifestyle behaviours that cluster with CS-SBs and the socioecological predictors of CS-SB.
Methods And Analysis: This longitudinal observational study will recruit 500 college-aged (18-24 years) individuals.
BMJ Open
December 2024
Faculty of Pharmaceutical Management and Economics, Hanoi University of Pharmacy, Hanoi, Vietnam
Objectives: To investigate the social support status and associated factors among Vietnamese methadone maintenance patients during the COVID-19 pandemic.
Design: Cross-sectional study.
Setting: Three methadone clinics.
Clin Immunol
December 2024
Univ Rennes, INSERM, EHESP, IRSET (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France. Electronic address:
Occupational exposure to crystalline silica is etiologically linked to an increased incidence of systemic sclerosis (SSc), also called Erasmus syndrome. The underlying mechanisms of silica-related SSc are still poorly understood. We demonstrated that early and repeated silica exposure contribute to the severity of SSc symptoms in the hypochloric acid (HOCl)-induced SSc mouse model.
View Article and Find Full Text PDFBackground: To analyse the epidemiological characteristics of orthopaedic trauma patients and thereby optimize healthcare resource allocation and improve treatment efficiency.
Materials And Methods: Relying on the hospital information system (HIS) database, we retrospectively analysed the epidemiological characteristics of orthopaedic trauma inpatients in our hospital between 2013 and 2022, including patient demographic information, causes of injury, location of injury and hospitalization costs.
Results: The median age of the patients was 36 (26-47) years old; the age stratification of the patients was highest in the proportion of patients aged 40-50 years old (29.
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