Modeling the Socio-Economic Impacts of Covid-19 Using an Improved Traditional Travel Demand Model
Bibliographic Data
| ID | 19569784 |
|---|---|
| Authors | Mehrnaz Doustmohammadi (University of Alabama in Huntsville, corresponding author), Phillip Ligrani, Phillip M Ligrani (0000-0002-0313-9580, University of Alabama in Huntsville), Michael Anderson (0000-0002-4079-1965, University of Alabama in Huntsville) |
| Year | 2020 |
| Volume | 08 |
| Issue | 04 |
| Pages | 688-704 |
| Publication date | 2020-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Current Urban Studies (JOURNAL) |
| Journal identifiers | ISSN: 2328-4900 • E-ISSN: 2328-4919 |
| Publisher | Scientific Research Publishing, Inc. (PUBLISHER) |
| DOI | 10.4236/cus.2020.84037 |
| OpenAlex | W3115588901 |
| Language | EN |
| References cited | 8 |
The emergence of the COVID-19 virus and subsequent pandemic has caused unprecedented disruption across many aspects of life across the globe. The implications have necessitated a re-evaluation of travel demand models to include the effects that mass isolation and quarantines have on roadway networks. The present paper is focused on data and methodologies to change travel demand models to account for differences encountered during the COVID-19 pandemic. Increased telecommunicating, coupled with store closures and restrictions, within the majority of business categories, has drastically changed traffic patterns. The results indicate that travel has decreased significantly, as businesses have altered their operating practices, requiring employees to work from home due to the restrictions implemented by the government. The present methodology considers a variety of potential alterations to travel patterns resulting from the presence of COVID-19. Because different amounts of reduced employment and increased telecommuting are considered, the present methodology and associated analysis show that different strategies proposed or implemented by the government can be modeled. The results provided in this paper, and the associated model, thus provide a means to account for the new traffic modelling reality resulting from the presence of COVID-19. Such travel modeling is important in regard to forecasts of future travel demand, associated transportation planning, allocation of present and future transportation resources, resulting economic benefits and challenges, and the well-being of our society, as an operationally efficient transportation network, and the associated quality of life, are maintained
Aviation · Business · Economics · Environmental economics · Telecommuting · Transport engineering · Travel behavior · Computer Science · COVID-19 epidemiological studies · COVID-19 impact on air quality · COVID-19 Pandemic Impacts · Engineering
| Highly cited | No |
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