Change in unemployment by social vulnerability among United States counties with rapid increases in COVID-19 incidence-July 1-October 31, 2020
During the COVID-19 pandemic, the unemployment rate in the United States peaked at 14.8% in April 2020. We examined patterns in unemployment following this peak in counties with rapid increases in COVID-19 incidence. We used CDC aggregate county data to identify counties with rapid increases in COVI...
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| creator | Tang, Shichao Horter, Libby Bosh, Karin Kassem, Ahmed M Kahn, Emily B Ricaldi, Jessica N Pao, Leah Zilversmit Kang, Gloria J Singleton, Christa-Marie Liu, Tiebin Thomas, Isabel Rao, Carol Y |
| description | During the COVID-19 pandemic, the unemployment rate in the United States peaked at 14.8% in April 2020. We examined patterns in unemployment following this peak in counties with rapid increases in COVID-19 incidence.
We used CDC aggregate county data to identify counties with rapid increases in COVID-19 incidence (rapid riser counties) during July 1-October 31, 2020. We used a linear regression model with fixed effect to calculate the change of unemployment rate difference in these counties, stratified by the county's social vulnerability (an indicator compiled by CDC) in the two months before the rapid riser index month compared to the index month plus one month after the index month.
Among the 585 (19% of U.S. counties) rapid riser counties identified, the unemployment rate gap between the most and least socially vulnerable counties widened by 0.40 percentage point (p |
| doi_str_mv | 10.1371/journal.pone.0265888 |
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We used CDC aggregate county data to identify counties with rapid increases in COVID-19 incidence (rapid riser counties) during July 1-October 31, 2020. We used a linear regression model with fixed effect to calculate the change of unemployment rate difference in these counties, stratified by the county's social vulnerability (an indicator compiled by CDC) in the two months before the rapid riser index month compared to the index month plus one month after the index month.
Among the 585 (19% of U.S. counties) rapid riser counties identified, the unemployment rate gap between the most and least socially vulnerable counties widened by 0.40 percentage point (p<0.01) after experiencing a rapid rise in COVID-19 incidence. Driving the gap were counties with lower socioeconomic status, with a higher percentage of people in racial and ethnic minority groups, and with limited English proficiency.
The widened unemployment gap after COVID-19 incidence rapid rise between the most and least socially vulnerable counties suggests that it may take longer for socially and economically disadvantaged communities to recover. Loss of income and benefits due to unemployment could hinder behaviors that prevent spread of COVID-19 (e.g., seeking healthcare) and could impede response efforts including testing and vaccination. Addressing the social needs within these vulnerable communities could help support public health response measures.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0265888</identifier><identifier>PMID: 35442951</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>COVID-19 ; COVID-19 - epidemiology ; Disease control ; Earth Sciences ; Economic aspects ; Economic conditions ; Engineering and Technology ; Ethnicity ; Health care ; Humans ; Incidence ; Medicine and Health Sciences ; Minority & ethnic groups ; Minority Groups ; Pandemics ; People and Places ; Public health ; Regression models ; Social interactions ; Social Sciences ; Social Vulnerability ; Socioeconomics ; Statistics ; Unemployment ; United States - epidemiology ; Vaccination</subject><ispartof>PloS one, 2022-04, Vol.17 (4), p.e0265888-e0265888</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-4901333c3c9ccc573f952c96807d18dbfafdb3e80eb68a9482ba94d26ac8aa633</citedby><cites>FETCH-LOGICAL-c692t-4901333c3c9ccc573f952c96807d18dbfafdb3e80eb68a9482ba94d26ac8aa633</cites><orcidid>0000-0001-5392-3106 ; 0000-0003-2503-1690 ; 0000-0003-0330-0554 ; 0000-0003-4053-7841</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020703/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020703/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35442951$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Nelson, Candace C.</contributor><creatorcontrib>Tang, Shichao</creatorcontrib><creatorcontrib>Horter, Libby</creatorcontrib><creatorcontrib>Bosh, Karin</creatorcontrib><creatorcontrib>Kassem, Ahmed M</creatorcontrib><creatorcontrib>Kahn, Emily B</creatorcontrib><creatorcontrib>Ricaldi, Jessica N</creatorcontrib><creatorcontrib>Pao, Leah Zilversmit</creatorcontrib><creatorcontrib>Kang, Gloria J</creatorcontrib><creatorcontrib>Singleton, Christa-Marie</creatorcontrib><creatorcontrib>Liu, Tiebin</creatorcontrib><creatorcontrib>Thomas, Isabel</creatorcontrib><creatorcontrib>Rao, Carol Y</creatorcontrib><title>Change in unemployment by social vulnerability among United States counties with rapid increases in COVID-19 incidence-July 1-October 31, 2020</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>During the COVID-19 pandemic, the unemployment rate in the United States peaked at 14.8% in April 2020. We examined patterns in unemployment following this peak in counties with rapid increases in COVID-19 incidence.
We used CDC aggregate county data to identify counties with rapid increases in COVID-19 incidence (rapid riser counties) during July 1-October 31, 2020. We used a linear regression model with fixed effect to calculate the change of unemployment rate difference in these counties, stratified by the county's social vulnerability (an indicator compiled by CDC) in the two months before the rapid riser index month compared to the index month plus one month after the index month.
Among the 585 (19% of U.S. counties) rapid riser counties identified, the unemployment rate gap between the most and least socially vulnerable counties widened by 0.40 percentage point (p<0.01) after experiencing a rapid rise in COVID-19 incidence. Driving the gap were counties with lower socioeconomic status, with a higher percentage of people in racial and ethnic minority groups, and with limited English proficiency.
The widened unemployment gap after COVID-19 incidence rapid rise between the most and least socially vulnerable counties suggests that it may take longer for socially and economically disadvantaged communities to recover. Loss of income and benefits due to unemployment could hinder behaviors that prevent spread of COVID-19 (e.g., seeking healthcare) and could impede response efforts including testing and vaccination. 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tang, Shichao</au><au>Horter, Libby</au><au>Bosh, Karin</au><au>Kassem, Ahmed M</au><au>Kahn, Emily B</au><au>Ricaldi, Jessica N</au><au>Pao, Leah Zilversmit</au><au>Kang, Gloria J</au><au>Singleton, Christa-Marie</au><au>Liu, Tiebin</au><au>Thomas, Isabel</au><au>Rao, Carol Y</au><au>Nelson, Candace C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Change in unemployment by social vulnerability among United States counties with rapid increases in COVID-19 incidence-July 1-October 31, 2020</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2022-04-20</date><risdate>2022</risdate><volume>17</volume><issue>4</issue><spage>e0265888</spage><epage>e0265888</epage><pages>e0265888-e0265888</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>During the COVID-19 pandemic, the unemployment rate in the United States peaked at 14.8% in April 2020. We examined patterns in unemployment following this peak in counties with rapid increases in COVID-19 incidence.
We used CDC aggregate county data to identify counties with rapid increases in COVID-19 incidence (rapid riser counties) during July 1-October 31, 2020. We used a linear regression model with fixed effect to calculate the change of unemployment rate difference in these counties, stratified by the county's social vulnerability (an indicator compiled by CDC) in the two months before the rapid riser index month compared to the index month plus one month after the index month.
Among the 585 (19% of U.S. counties) rapid riser counties identified, the unemployment rate gap between the most and least socially vulnerable counties widened by 0.40 percentage point (p<0.01) after experiencing a rapid rise in COVID-19 incidence. Driving the gap were counties with lower socioeconomic status, with a higher percentage of people in racial and ethnic minority groups, and with limited English proficiency.
The widened unemployment gap after COVID-19 incidence rapid rise between the most and least socially vulnerable counties suggests that it may take longer for socially and economically disadvantaged communities to recover. Loss of income and benefits due to unemployment could hinder behaviors that prevent spread of COVID-19 (e.g., seeking healthcare) and could impede response efforts including testing and vaccination. Addressing the social needs within these vulnerable communities could help support public health response measures.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>35442951</pmid><doi>10.1371/journal.pone.0265888</doi><tpages>e0265888</tpages><orcidid>https://orcid.org/0000-0001-5392-3106</orcidid><orcidid>https://orcid.org/0000-0003-2503-1690</orcidid><orcidid>https://orcid.org/0000-0003-0330-0554</orcidid><orcidid>https://orcid.org/0000-0003-4053-7841</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | PloS one, 2022-04, Vol.17 (4), p.e0265888-e0265888 |
| issn | 1932-6203 1932-6203 |
| language | eng |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS) Journals Open Access; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | COVID-19 COVID-19 - epidemiology Disease control Earth Sciences Economic aspects Economic conditions Engineering and Technology Ethnicity Health care Humans Incidence Medicine and Health Sciences Minority & ethnic groups Minority Groups Pandemics People and Places Public health Regression models Social interactions Social Sciences Social Vulnerability Socioeconomics Statistics Unemployment United States - epidemiology Vaccination |
| title | Change in unemployment by social vulnerability among United States counties with rapid increases in COVID-19 incidence-July 1-October 31, 2020 |
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