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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 |
Sumario: | 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. |
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