Modeling of the COVID-19 impact on air passenger traffic in the US, European countries, and China

Wai Ming To, Peter K.C. Lee

Research output: Contribution to journalArticlepeer-review

Abstract

The COVID-19 pandemic has changed many aspects of people's lives including travel since early 2020. Specifically, it has adversely affected people traveling by air and has hit the air transport industry significantly. But, how big is the COVID-19 impact? In order to answer such a question, we collected air passenger traffic data from the US, European countries, and China which accounted for over 75% of the world's total air passenger traffic. Air passenger traffic data in these three regions during the period January 2010 to December 2019 were modeled using seasonal autoregressive integrated moving average (ARIMA) models. Seasonal ARIMA models were used to predict air passenger traffic from January 2011 to December 2019 (just before the spread of COVID-19) and the accuracy of the models was evaluated. The models were then used to predict air passenger traffic from January 2020 to December 2022 for the case without COVID-19. The COVID-19 impacts on air passenger traffic were estimated by calculating the differences in predicted and actual air passenger numbers in monthly basis. Results showed that air passenger traffic was significantly recovered in the US and European countries but it encountered significant falls in 2021 and 2022 in China due to spikes in COVID-19 variant cases in many provinces and the implementation of zero-tolerance COVID-19 policy. Implications of the study are given.

Original languageEnglish
Article number102556
JournalJournal of Air Transport Management
Volume115
DOIs
Publication statusPublished - Mar 2024

Keywords

  • ARIMA models
  • Air passenger traffic
  • COVID-19
  • Regional analysis

Fingerprint

Dive into the research topics of 'Modeling of the COVID-19 impact on air passenger traffic in the US, European countries, and China'. Together they form a unique fingerprint.

Cite this