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Analyzing multiple COVID-19 outbreak impacts: A case study based on Chinese national air passenger flow
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),...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842631/ https://www.ncbi.nlm.nih.gov/pubmed/36685313 http://dx.doi.org/10.1016/j.tra.2023.103586 |
Sumario: | 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. |
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