Estimation of differential occupational risk of COVID-19 by comparing risk factors with case data by occupational group.

ABSTRACT:

Background

The disease burden of coronavirus disease 2019 (COVID-19) is not uniform across occupations. Although healthcare workers are well-known to be at increased risk, data for other occupations are lacking. In lieu of this, models have been used to forecast occupational risk using various predictors, but no model heretofore has used data from actual case numbers. This study assesses the differential risk of COVID-19 by occupation using predictors from the Occupational Information Network (O*NET) database and correlating them with case counts published by the Washington State Department of Health to identify workers in individual occupations at highest risk of COVID-19 infection.

Methods

The O*NET database was screened for potential predictors of differential COVID-19 ri

SUBMITTER: Zhang M 

PROVIDER: S-EPMC7753309 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature