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Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts.

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Title: Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts.
Authors: Haley, Beth M.1 (AUTHOR), Patil, Prasad2 (AUTHOR), Levy, Jonathan I.1 (AUTHOR), Spangler, Keith R.1 (AUTHOR), Tieskens, Koen F.1 (AUTHOR), Carnes, Fei1 (AUTHOR), Peng, Xiaojing2 (AUTHOR), Klevens, R. Monina3 (AUTHOR), Troppy, T. Scott3 (AUTHOR), Fabian, M. Patricia1 (AUTHOR), Lane, Kevin J.1 (AUTHOR), Leibler, Jessica H.1 (AUTHOR) jleibler@bu.edu
Source: Journal of Community Health. Feb2024, Vol. 49 Issue 1, p91-99. 9p.
Subject Terms: *COVID-19 pandemic, COVID-19, Confidence intervals, Occupational exposure, Risk assessment, Construction industry, Descriptive statistics, Research funding, Sociodemographic factors, Transportation
Geographic Terms: Massachusetts
Abstract: Occupational exposure to SARS-CoV-2 varies by profession, but "essential workers" are often considered in aggregate in COVID-19 models. This aggregation complicates efforts to understand risks to specific types of workers or industries and target interventions, specifically towards non-healthcare workers. We used census tract-resolution American Community Survey data to develop novel essential worker categories among the occupations designated as COVID-19 Essential Services in Massachusetts. Census tract-resolution COVID-19 cases and deaths were provided by the Massachusetts Department of Public Health. We evaluated the association between essential worker categories and cases and deaths over two phases of the pandemic from March 2020 to February 2021 using adjusted mixed-effects negative binomial regression, controlling for other sociodemographic risk factors. We observed elevated COVID-19 case incidence in census tracts in the highest tertile of workers in construction/transportation/buildings maintenance (Phase 1: IRR 1.32 [95% CI 1.22, 1.42]; Phase 2: IRR: 1.19 [1.13, 1.25]), production (Phase 1: IRR: 1.23 [1.15, 1.33]; Phase 2: 1.18 [1.12, 1.24]), and public-facing sales and services occupations (Phase 1: IRR: 1.14 [1.07, 1.21]; Phase 2: IRR: 1.10 [1.06, 1.15]). We found reduced case incidence associated with greater percentage of essential workers able to work from home (Phase 1: IRR: 0.85 [0.78, 0.94]; Phase 2: IRR: 0.83 [0.77, 0.88]). Similar trends exist in the associations between essential worker categories and deaths, though attenuated. Estimating industry-specific risk for essential workers is important in targeting interventions for COVID-19 and other diseases and our categories provide a reproducible and straightforward way to support such efforts. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Community Health is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts.
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  Data: <searchLink fieldCode="AR" term="%22Haley%2C+Beth+M%2E%22">Haley, Beth M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Patil%2C+Prasad%22">Patil, Prasad</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Levy%2C+Jonathan+I%2E%22">Levy, Jonathan I.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Spangler%2C+Keith+R%2E%22">Spangler, Keith R.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tieskens%2C+Koen+F%2E%22">Tieskens, Koen F.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Carnes%2C+Fei%22">Carnes, Fei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peng%2C+Xiaojing%22">Peng, Xiaojing</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Klevens%2C+R%2E+Monina%22">Klevens, R. Monina</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Troppy%2C+T%2E+Scott%22">Troppy, T. Scott</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fabian%2C+M%2E+Patricia%22">Fabian, M. Patricia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lane%2C+Kevin+J%2E%22">Lane, Kevin J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Leibler%2C+Jessica+H%2E%22">Leibler, Jessica H.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jleibler@bu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Community+Health%22">Journal of Community Health</searchLink>. Feb2024, Vol. 49 Issue 1, p91-99. 9p.
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  Data: *<searchLink fieldCode="DE" term="%22COVID-19+pandemic%22">COVID-19 pandemic</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+exposure%22">Occupational exposure</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+industry%22">Construction industry</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Sociodemographic+factors%22">Sociodemographic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Transportation%22">Transportation</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Massachusetts%22">Massachusetts</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Occupational exposure to SARS-CoV-2 varies by profession, but "essential workers" are often considered in aggregate in COVID-19 models. This aggregation complicates efforts to understand risks to specific types of workers or industries and target interventions, specifically towards non-healthcare workers. We used census tract-resolution American Community Survey data to develop novel essential worker categories among the occupations designated as COVID-19 Essential Services in Massachusetts. Census tract-resolution COVID-19 cases and deaths were provided by the Massachusetts Department of Public Health. We evaluated the association between essential worker categories and cases and deaths over two phases of the pandemic from March 2020 to February 2021 using adjusted mixed-effects negative binomial regression, controlling for other sociodemographic risk factors. We observed elevated COVID-19 case incidence in census tracts in the highest tertile of workers in construction/transportation/buildings maintenance (Phase 1: IRR 1.32 [95% CI 1.22, 1.42]; Phase 2: IRR: 1.19 [1.13, 1.25]), production (Phase 1: IRR: 1.23 [1.15, 1.33]; Phase 2: 1.18 [1.12, 1.24]), and public-facing sales and services occupations (Phase 1: IRR: 1.14 [1.07, 1.21]; Phase 2: IRR: 1.10 [1.06, 1.15]). We found reduced case incidence associated with greater percentage of essential workers able to work from home (Phase 1: IRR: 0.85 [0.78, 0.94]; Phase 2: IRR: 0.83 [0.77, 0.88]). Similar trends exist in the associations between essential worker categories and deaths, though attenuated. Estimating industry-specific risk for essential workers is important in targeting interventions for COVID-19 and other diseases and our categories provide a reproducible and straightforward way to support such efforts. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Community Health is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10900-023-01249-x
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        Text: English
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      – SubjectFull: COVID-19 pandemic
        Type: general
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      – SubjectFull: Confidence intervals
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      – SubjectFull: Occupational exposure
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      – SubjectFull: Construction industry
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      – SubjectFull: Transportation
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      – SubjectFull: Massachusetts
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