JOURNAL ARTICLE
Public health and elections: Correlating COVID-19 vaccination rates with 2020 U.S. presidential election results.
Published In: International Journal of Modern Physics C: Computational Physics & Physical Computation, 2024, v. 35, n. 7. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Villaseñor-Ibáñez, J.; del Castillo-Mussot, M.; Hernández-Ramírez, E. 3 of 3
Abstract
We correlate county-level partial and full vaccination rates with results from the 2020 United States (U.S.) election, obtaining Pearson correlation values for each individual state, noting top and bottom values, and observing an almost absolute positive correlation between Biden support and vaccination rates, and inversely a negative correlation when considering Trump support. This trend holds for other territorial categories: regions and subdivisions. Correlation values based on county-level data for two other categories of interest are found: urbanization level and ethnic group majority by county. We find a higher degree of correlation for White majority counties, and a lower one for majority minority counties. When analyzing urbanization level we find the lowest values in highly urban counties. We posit a relationship between these two categories, based on the fact that urban counties are generally more ethnically diverse, and suburban and rural areas generally retain white majorities. Our results showcase the current process of political polarization and history leading to this phenomenon, which includes the role that health topics and issues have played in it, reinforcing the idea of politics and health being strongly linked subjects in the United States. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Modern Physics C: Computational Physics & Physical Computation. 2024/07, Vol. 35, Issue 7, p1
- Document Type:Article
- Subject Area:Political Science
- Publication Date:2024
- ISSN:0129-1831
- DOI:10.1142/S0129183124500906
- Accession Number:177991297
- Copyright Statement:Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company 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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