Objectives: The aim of the study is to characterize the incidence of SARS-CoV-2 exposure and COVID-19 infection among California workers' compensation claims in 2020 and examine risk factors for exposure.
Methods: Using a case-control approach, we combined machine learning techniques and job exposure matrices to assess associations between exposures and illness claims and clusters of claims within specific worksites over a 3-week period.
Results: Of the 117,125 COVID-19 claims, most were primarily among younger groups, of shorter tenure, and from health care occupations. Illness claims were among older groups with longer tenure. Jobs with very close physical proximity and high physical activity, along with transportation and warehousing industries, were associated with being part of a cluster of claims.
Conclusions: The findings merit further study but indicate respiratory viral transmission and support efforts to systematically incorporate work-related variables into other California data sources.
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| http://dx.doi.org/10.1097/JOM.0000000000003163 | DOI Listing |
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