Skip to main content
Log in

Examining the Effects of Confirmed COVID-19 Cases and State Government Policies on Passenger Air Traffic Recovery by Proposing an OD Spatial Temporal Model

  • Published:
Networks and Spatial Economics Aims and scope Submit manuscript

Abstract

As the world is reopening from the unprecedented global pandemic, investigating how the intensity of transmission and responsive policies affect passenger air traffic demand is valuable for the aviation industry recovery and post-pandemic economic development. This paper investigates the effects of confirmed COVID-19 cases and state government policies at 28 hub airports in the United States from March 2020 to September 2021 by proposing an origin-destination (OD) spatial temporal econometric model. The investigation finds that (1) confirmed COVID-19 cases and state government policies had the highest effects on air traffic in the same month as these events occurred and the effects were diminishing in the following months; (2) The policy of internal movement restrictions in a given state generated a higher impact for trips arriving at this state, while confirmed COVID-19 cases and the testing policy generated a higher impact for trips departing from this state; (3) Reopening offices, lifting movement restrictions, maintaining flexibility in accessing COVID-19 tests, and using facial covering onboard are effective policies for aviation industry recovery. This paper aims to be a timely study on air travel demand when the domestic traffic has almost achieved the pre-pandemic level, offering insights into recovery of the aviation industry and preparation for future uncertainties. In addition, the proposed OD spatial temporal model which captures OD spatial dependences and temporal correlations simultaneously can equip spatial economists with an innovative and powerful tool.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data Availability

The datasets and programming code generated during and analyzed during the current study are available from the corresponding author on reasonable request.

References

Download references

Acknowledgements

This paper is supported by National Natural Science Foundation of China (No. 72101255) and the Ministry of Education in China Project of Humanities and Social Science (No. 21YJC790157).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dapeng Zhang.

Ethics declarations

Conflict of Interest

There are no conflicts of interest to this work.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, D. Examining the Effects of Confirmed COVID-19 Cases and State Government Policies on Passenger Air Traffic Recovery by Proposing an OD Spatial Temporal Model. Netw Spat Econ (2024). https://doi.org/10.1007/s11067-024-09619-1

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11067-024-09619-1

Keywords

Navigation