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A COVID-19 Risk Assessment for the US Labor Force
The consequences of COVID-19 infection varies substantially based on individual social risk factors and predisposing health conditions. Understanding this variability may be critical for targeting COVID-19 control measures, resources and policies, including efforts to return people back to the workp...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217089/ https://www.ncbi.nlm.nih.gov/pubmed/32511435 http://dx.doi.org/10.1101/2020.04.13.20063776 |
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author | Maher, Samantha Hill, Alexandra E Britton, Peter Fenichel, Eli P. Daszak, Peter Zambrana-Torrelio, Carlos Bayham, Jude |
author_facet | Maher, Samantha Hill, Alexandra E Britton, Peter Fenichel, Eli P. Daszak, Peter Zambrana-Torrelio, Carlos Bayham, Jude |
author_sort | Maher, Samantha |
collection | PubMed |
description | The consequences of COVID-19 infection varies substantially based on individual social risk factors and predisposing health conditions. Understanding this variability may be critical for targeting COVID-19 control measures, resources and policies, including efforts to return people back to the workplace. We compiled individual level data from the National Health Information Survey and Quarterly Census of Earnings and Wages to estimate the number of at-risk workers for each US county and industry, accounting for both social and health risks. Nearly 80% of all workers have at least one health risk and 11% are over 60 with an additional health risk. We document important variation in the at-risk population across states, counties, and industries that could provide a strategic underpinning to a staged return to work. |
format | Online Article Text |
id | pubmed-7217089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-72170892020-06-07 A COVID-19 Risk Assessment for the US Labor Force Maher, Samantha Hill, Alexandra E Britton, Peter Fenichel, Eli P. Daszak, Peter Zambrana-Torrelio, Carlos Bayham, Jude medRxiv Article The consequences of COVID-19 infection varies substantially based on individual social risk factors and predisposing health conditions. Understanding this variability may be critical for targeting COVID-19 control measures, resources and policies, including efforts to return people back to the workplace. We compiled individual level data from the National Health Information Survey and Quarterly Census of Earnings and Wages to estimate the number of at-risk workers for each US county and industry, accounting for both social and health risks. Nearly 80% of all workers have at least one health risk and 11% are over 60 with an additional health risk. We document important variation in the at-risk population across states, counties, and industries that could provide a strategic underpinning to a staged return to work. Cold Spring Harbor Laboratory 2020-04-17 /pmc/articles/PMC7217089/ /pubmed/32511435 http://dx.doi.org/10.1101/2020.04.13.20063776 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/It is made available under a CC-BY-NC-ND 4.0 International license (http://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Article Maher, Samantha Hill, Alexandra E Britton, Peter Fenichel, Eli P. Daszak, Peter Zambrana-Torrelio, Carlos Bayham, Jude A COVID-19 Risk Assessment for the US Labor Force |
title | A COVID-19 Risk Assessment for the US Labor Force |
title_full | A COVID-19 Risk Assessment for the US Labor Force |
title_fullStr | A COVID-19 Risk Assessment for the US Labor Force |
title_full_unstemmed | A COVID-19 Risk Assessment for the US Labor Force |
title_short | A COVID-19 Risk Assessment for the US Labor Force |
title_sort | covid-19 risk assessment for the us labor force |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217089/ https://www.ncbi.nlm.nih.gov/pubmed/32511435 http://dx.doi.org/10.1101/2020.04.13.20063776 |
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