Highlight We propose a novel COVID-19 multiple outbreak analysis method (NCMOA). This method divides the impact of multiple outbreaks on time and degree separately. The differentiated air traffic recovery patterns are analyzed in the case study. The impacts on epi-center and the nation have different critical influence factors. The implication on policy formulation of airline and government is proposed.
Abstract The spread of COVID-19 results in a significant drop in traffic levels worldwide. Quantifying the impact of multiple COVID-19 outbreaks on traffic systems is critical to developing differentiated policies in the future. This paper proposes a novel COVID-19 multiple outbreak analysis method (NCMOA), dividing the impact scope and degree under multiple COVID-19 disturbances, and using the recovery rate and accumulated loss to quantify the impacts on air passenger flow. A case study based on Chinese national air traffic flow is executed, and the recovery patterns and the differentiated disturbances are analyzed. Results show that air passenger flow recovers with a similar pattern after the first outbreak, and subsequent outbreaks cause local effects and cannot affect the overall recovery pattern. Further, the heterogeneous influence factors and trends on the epi-centers (EC) and the nation are analyzed. In addition, the methods and results of this paper quantify the impact of COVID-19 on air passenger flow at a more detailed level under multiple disturbances. They could provide a basis for differentiated policy formulation of airlines and government in the future.
Analyzing multiple COVID-19 outbreak impacts: A case study based on Chinese national air passenger flow
2023-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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