ArticleTransportation research. Part A, Policy and practice2022
An airport level framework for examining the impact of COVID-19 on airline demand.
Article in Transportation research. Part A, Policy and practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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Who cites it
3 citing papers in PubMed.
- Article
- Airport terminal passenger forecast under the impact of COVID-19 outbreaks: A case study from China.Journal of building engineering · 2023Article
- COVID-19 pandemic and air transportation: Summary of Recent Research, Policy Consideration and Future Research Directions.Transportation research interdisciplinary perspectives · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, we examine the influence of Coronavirus disease 2019 (COVID-19) on airline demand at the disaggregate resolution of airport. The primary focus of our proposed research effort is to develop a framework that provides a blueprint for airline demand recovery as COVID-19 cases evolve over time. Airline monthly demand data is sourced from Bureau of Transportation Statistics for 380 airports for 24 months from January 2019 through December 2020. The demand data is augmented with a host of independent variables including COVID-19 related factors, demographic characteristics and built environment characteristics at the county level, airport specific factors, spatial factors, temporal factors, and adjoining county attributes. The effect of COVID-19 related factors is identified by considering global and local COVID-19 transmission, temporal indicators of pandemic start and progress, and interactions of airline demand predictors with global and local COVID-19 indicators. Finally, we present a blueprint for airline demand recovery where we consider three hypothetical scenarios of COVID-19 transmission rates - expected, pessimistic and optimistic. The results at the airport level from these scenarios are aggregated at the state or regional level by adding the demand from all airports in the corresponding state or region. These trends are presented by State and Region to illustrate potential differences across various scenarios. The results highlight a potentially slow path to airline demand recovery until COVID-19 cases subside.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.