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Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19
This research aims to understand temporal, regional, demographic, and policy factors that influenced travel reduction within the contiguous United States during the early period of the COVID-19 pandemic. Particularly, this research combines U.S. Census data, infection rates, and state-level mandates...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149349/ https://www.ncbi.nlm.nih.gov/pubmed/37153187 http://dx.doi.org/10.1177/03611981211009541 |
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author | Fisher, Mitchell LaMondia, Jeffrey J. |
author_facet | Fisher, Mitchell LaMondia, Jeffrey J. |
author_sort | Fisher, Mitchell |
collection | PubMed |
description | This research aims to understand temporal, regional, demographic, and policy factors that influenced travel reduction within the contiguous United States during the early period of the COVID-19 pandemic. Particularly, this research combines U.S. Census data, infection rates, and state-level mandates to determine their effects on daily, county-level vehicle miles traveled (VMT) estimations from March 1, 2020 to April 21, 2020. Specifically, this work generates metrics of VMT per capita, daily change in VMT, and VMT immediate reaction rates for every county in the U.S.A. and develops regression models to determine how these factors influence VMT rates over time. Results show that state-mandated orders were deployed in a pattern relative to their expected economic impact. Model results showed infection rates may have had a greater influence on forcing state policy adoption, ensuring reduced VMT, rather than the number of cases directly influencing individual travel to a significant degree. Additionally, counties with higher populations or labeled as urban counties saw a greater reduction in VMT across all three models compared with lower population and rural counties. Planners and policy makers in the future can utilize the results of this research to make better informed responses as well as to know the expected results of their actions. |
format | Online Article Text |
id | pubmed-10149349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-101493492023-05-03 Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 Fisher, Mitchell LaMondia, Jeffrey J. Transp Res Rec COVID-19 and Transportation This research aims to understand temporal, regional, demographic, and policy factors that influenced travel reduction within the contiguous United States during the early period of the COVID-19 pandemic. Particularly, this research combines U.S. Census data, infection rates, and state-level mandates to determine their effects on daily, county-level vehicle miles traveled (VMT) estimations from March 1, 2020 to April 21, 2020. Specifically, this work generates metrics of VMT per capita, daily change in VMT, and VMT immediate reaction rates for every county in the U.S.A. and develops regression models to determine how these factors influence VMT rates over time. Results show that state-mandated orders were deployed in a pattern relative to their expected economic impact. Model results showed infection rates may have had a greater influence on forcing state policy adoption, ensuring reduced VMT, rather than the number of cases directly influencing individual travel to a significant degree. Additionally, counties with higher populations or labeled as urban counties saw a greater reduction in VMT across all three models compared with lower population and rural counties. Planners and policy makers in the future can utilize the results of this research to make better informed responses as well as to know the expected results of their actions. SAGE Publications 2021-07-22 2023-04 /pmc/articles/PMC10149349/ /pubmed/37153187 http://dx.doi.org/10.1177/03611981211009541 Text en © National Academy of Sciences: Transportation Research Board 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | COVID-19 and Transportation Fisher, Mitchell LaMondia, Jeffrey J. Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 |
title | Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 |
title_full | Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 |
title_fullStr | Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 |
title_full_unstemmed | Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 |
title_short | Understanding the Temporal, Regional, Demographic, and Policy Factors Influencing Counties’ Daily Traffic Volume Reductions in Response to COVID-19 |
title_sort | understanding the temporal, regional, demographic, and policy factors influencing counties’ daily traffic volume reductions in response to covid-19 |
topic | COVID-19 and Transportation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149349/ https://www.ncbi.nlm.nih.gov/pubmed/37153187 http://dx.doi.org/10.1177/03611981211009541 |
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