COVID-19 and US Labor Force: County-Level Insights

Anissa Champion, Daniel Ojeda, Ching Yu Huang, Daehan Kwak

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The COVID-19 pandemic has highlighted the crucial role of socio-economic factors in shaping health outcomes. Understanding the correlations between different societal attributes and how each one contributed to COVID-19 outcomes in the United States is essential. Therefore, this study utilized real-time reported COVID-19 data from a database known as SimpleMaps and integrated it with US county data to analyze the societal attribute, labor force, and its correlation with COVID-19 outcomes. This study reveals that the labor force has a correlation with COVID-19 cases and deaths. In addition to identifying correlations, the study creates visuals to help visualize the trends better. These findings and visuals can offer valuable insights for policymakers in implementing targeted strategies to mitigate the impact of COVID-19 on vulnerable populations and enhance the understanding of socio-economic factors' impact on COVID-19 outcomes.

Original languageEnglish
Title of host publicationProceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1891-1893
Number of pages3
ISBN (Electronic)9798350327595
DOIs
StatePublished - 2023
Event2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 - Las Vegas, United States
Duration: 24 Jul 202327 Jul 2023

Publication series

NameProceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023

Conference

Conference2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023
Country/TerritoryUnited States
CityLas Vegas
Period24/07/2327/07/23

Keywords

  • correlation analysis
  • Covid-19
  • labor force
  • socio-economics factors

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