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Is construction work associated with increased community transmission of coronavirus disease 2019 (COVID-19) and disproportionate morbidity among construction workers in US cities?
This decision analytical model of COVID-19 found that resuming construction work during shelter-in-place orders was associated with increased hospitalization risks in the construction workforce and increase transmission in the surrounding community. Based on COVID-19 hospitalization data through August 20, 2020, construction workers had a nearly 5-fold increased risk of hospitalization in central Texas compared with other occupational categories.
The findings of this study suggest that enacting workplace safety policies and providing paid sick leave could protect essential workers in high-contact industries and prevent further widening of disparities in COVID-19 morbidity and mortality.
Policy makers have relaxed restrictions for certain nonessential industries, including construction, jeopardizing the effectiveness of social distancing measures and putting already at-risk populations at greater risk of coronavirus disease 2019 (COVID-19) infection. In Texas, Latinx populations are overly represented among construction workers, and thus have elevated rates of exposure that are compounded by prevalent high-risk comorbidities and lack of access to health care.
To assess the association between construction work during the COVID-19 pandemic and hospitalization rates for construction workers and the surrounding community.
Design, Setting, and Participants
This decision analytical model used a mathematical model of COVID-19 transmission, stratified by age and risk group, with construction workers modeled explicitly. The model was based on residents of the Austin–Round Rock metropolitan statistical area, with a population of 2.17 million. Based on 500 stochastic simulations for each of 15 scenarios that varied the size of the construction workforce and level of worksite transmission risk, the association between continued construction work and hospitalizations was estimated and then compared with anonymized line-list hospitalization data from central Texas through August 20, 2020.
Social distancing interventions, size of construction workforce, and level of disease transmission at construction worksites.
Main Outcomes and Measures
For each scenario, the total number of COVID-19 hospitalizations and the relative risk of hospitalization among construction workers was projected and then compared with relative risks estimated from reported hospitalization data.
Allowing unrestricted construction work was associated with an increase of COVID-19 hospitalization rates through mid-August 2020 from 0.38 per 1000 residents to 1.5 per 1000 residents and from 0.22 per 1000 construction workers to 9.3 per 1000 construction workers. This increased risk was estimated to be offset by safety measures (such as thorough cleaning of equipment between uses, wearing of protective equipment, limits on the number of workers at a worksite, and increased health surveillance) that were associated with a 50% decrease in transmission. The observed relative risk of hospitalization among construction workers compared with other occupational categories among adults aged 18 to 64 years was 4.9 (95% CI, 3.8-6.2).
Conclusions and Relevance
The findings of this study suggest that unrestricted work in high-contact industries, such as construction, is associated with a higher level of community transmission, increased risks to at-risk workers, and larger health disparities among members of racial and ethnic minority groups.
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Accepted for Publication: September 24, 2020.
Published: October 29, 2020. doi:10.1001/jamanetworkopen.2020.26373
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Pasco RF et al. JAMA Network Open.
Corresponding Author: Lauren Ancel Meyers, PhD, Department of Integrative Biology, The University of Texas at Austin, One University Station C0990, Austin, TX 78712 (email@example.com).
Author Contributions: Mr Pasco had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Pasco, Johnston, Pignone, Meyers.
Acquisition, analysis, or interpretation of data: Pasco, Fox, Pignone, Meyers.
Drafting of the manuscript: Pasco, Meyers.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Pasco, Fox, Meyers.
Obtained funding: Meyers.
Administrative, technical, or material support: Johnston, Meyers.
Supervision: Fox, Meyers.
Conflict of Interest Disclosures: None reported.
Funding/Support: This study was supported, in part, by contract 75D-301-19-C-05930 from the US Centers for Disease Control and Prevention and grant R01AI151176 from the National Institutes of Health.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: The authors thank Zhanwei Du, PhD, Michaela Petty, Xutong Wang, MS (The University of Texas at Austin), and other members of the University of Texas at Austin COVID-19 Modeling Consortium for assisting in the development of the transmission model. None of these individuals were compensated beyond their regular salaries.
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