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Examining the impact of socioeconomic variables on COVID-19 death rates at the state level
This study uses a step-wise regression model to identify the socioeconomic variables most significant in explaining COVID-19 death rates on a state-level basis. The regression tests cover the 1/1/2020 to 12/1/2020 period as well as the first and second halves of 2020. This study also uses the Oxford...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980794/ http://dx.doi.org/10.1007/s10818-021-09309-9 |
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author | Doti, James L. |
author_facet | Doti, James L. |
author_sort | Doti, James L. |
collection | PubMed |
description | This study uses a step-wise regression model to identify the socioeconomic variables most significant in explaining COVID-19 death rates on a state-level basis. The regression tests cover the 1/1/2020 to 12/1/2020 period as well as the first and second halves of 2020. This study also uses the Oxford stringency index to measure more precisely the efficacy of governmental mandates at the state level. The results in this study rigorously showed that while the density variables were the most significant explanatory variables during the first half of the year, their significance fell during the second half. Use of the Oxford stringency index revealed that more stringent mandates led to significant reductions in COVID-19 death rates, especially during the second half of the year. The study’s findings also reveal that a higher poverty rate in a state is significantly associated with higher COVID-19 death rates during all three periods tested. |
format | Online Article Text |
id | pubmed-7980794 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-79807942021-03-23 Examining the impact of socioeconomic variables on COVID-19 death rates at the state level Doti, James L. J Bioecon Article This study uses a step-wise regression model to identify the socioeconomic variables most significant in explaining COVID-19 death rates on a state-level basis. The regression tests cover the 1/1/2020 to 12/1/2020 period as well as the first and second halves of 2020. This study also uses the Oxford stringency index to measure more precisely the efficacy of governmental mandates at the state level. The results in this study rigorously showed that while the density variables were the most significant explanatory variables during the first half of the year, their significance fell during the second half. Use of the Oxford stringency index revealed that more stringent mandates led to significant reductions in COVID-19 death rates, especially during the second half of the year. The study’s findings also reveal that a higher poverty rate in a state is significantly associated with higher COVID-19 death rates during all three periods tested. Springer US 2021-03-20 2021 /pmc/articles/PMC7980794/ http://dx.doi.org/10.1007/s10818-021-09309-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Doti, James L. Examining the impact of socioeconomic variables on COVID-19 death rates at the state level |
title | Examining the impact of socioeconomic variables on COVID-19 death rates at the state level |
title_full | Examining the impact of socioeconomic variables on COVID-19 death rates at the state level |
title_fullStr | Examining the impact of socioeconomic variables on COVID-19 death rates at the state level |
title_full_unstemmed | Examining the impact of socioeconomic variables on COVID-19 death rates at the state level |
title_short | Examining the impact of socioeconomic variables on COVID-19 death rates at the state level |
title_sort | examining the impact of socioeconomic variables on covid-19 death rates at the state level |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980794/ http://dx.doi.org/10.1007/s10818-021-09309-9 |
work_keys_str_mv | AT dotijamesl examiningtheimpactofsocioeconomicvariablesoncovid19deathratesatthestatelevel |