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The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia
The ongoing COVID-19 pandemic has posed a global threat to human health. In order to prevent the spread of this virus, many countries have imposed travel restrictions. This difficult situation has dramatically affected the airline industry by reducing the passenger volume, number of flights, airline...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8849875/ https://www.ncbi.nlm.nih.gov/pubmed/35194345 http://dx.doi.org/10.1016/j.jairtraman.2022.102192 |
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author | Kuo, Pei-Fen Brawiswa Putra, I Gede Setiawan, Faizal Azmi Wen, Tzai-Hung Chiu, Chui-Sheng Sulistyah, Umroh Dian |
author_facet | Kuo, Pei-Fen Brawiswa Putra, I Gede Setiawan, Faizal Azmi Wen, Tzai-Hung Chiu, Chui-Sheng Sulistyah, Umroh Dian |
author_sort | Kuo, Pei-Fen |
collection | PubMed |
description | The ongoing COVID-19 pandemic has posed a global threat to human health. In order to prevent the spread of this virus, many countries have imposed travel restrictions. This difficult situation has dramatically affected the airline industry by reducing the passenger volume, number of flights, airline flow patterns, and even has changed the entire airport network, especially in Northeast Asia (because it includes the original disease seed). However, although most scholars have used conventional statistical analysis to describe the changes in passenger volume before and during the COVID-19 outbreak, very few of them have applied statistical assessment or time series analysis, and have not even examined how the impact may be different from place to place. Therefore, the purpose of this study was to identify the impact of COVID-19 on the airline industry and affected areas (including the origin-destination flow and the airport network). First, a Clustering Large Applications (CLARA) algorithm was used to group numerous origin-destination (O-D) flow patterns based on their characteristics and to determine if these characteristics have changed the severity of the impact of each cluster during the COVID-19 outbreak. Second, two statistical tests (the paired t-test and the Wilcoxon signed-rank test) were utilized to determine if the entire airport network and the top 30 hub airports changed during COVID-19. Four centrality measurement indices (degree, closeness, eigenvector, and betweenness centrality) of the airports were used to assess the entire network and ranking of individual hub airports. The study data, provided by The Official Aviation Guide (OAG) from December 2019 to April 2020, indicated that during the COVID-19 outbreak, there was a decrease in passenger volume (60%–98.4%) as well as the number of flights (1.5%–82.6%). However, there were no such significant changes regarding the popularity ranking of most airports during the outbreak. Before this occurred (December 2019), most hub airports were in China (April 2020), and this trend remain similar during the COVID-19 outbreak. However, the values of the centrality measurement decreased significantly for most hub airports due to travel restrictions issued by the government. |
format | Online Article Text |
id | pubmed-8849875 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88498752022-02-18 The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia Kuo, Pei-Fen Brawiswa Putra, I Gede Setiawan, Faizal Azmi Wen, Tzai-Hung Chiu, Chui-Sheng Sulistyah, Umroh Dian J Air Transp Manag Article The ongoing COVID-19 pandemic has posed a global threat to human health. In order to prevent the spread of this virus, many countries have imposed travel restrictions. This difficult situation has dramatically affected the airline industry by reducing the passenger volume, number of flights, airline flow patterns, and even has changed the entire airport network, especially in Northeast Asia (because it includes the original disease seed). However, although most scholars have used conventional statistical analysis to describe the changes in passenger volume before and during the COVID-19 outbreak, very few of them have applied statistical assessment or time series analysis, and have not even examined how the impact may be different from place to place. Therefore, the purpose of this study was to identify the impact of COVID-19 on the airline industry and affected areas (including the origin-destination flow and the airport network). First, a Clustering Large Applications (CLARA) algorithm was used to group numerous origin-destination (O-D) flow patterns based on their characteristics and to determine if these characteristics have changed the severity of the impact of each cluster during the COVID-19 outbreak. Second, two statistical tests (the paired t-test and the Wilcoxon signed-rank test) were utilized to determine if the entire airport network and the top 30 hub airports changed during COVID-19. Four centrality measurement indices (degree, closeness, eigenvector, and betweenness centrality) of the airports were used to assess the entire network and ranking of individual hub airports. The study data, provided by The Official Aviation Guide (OAG) from December 2019 to April 2020, indicated that during the COVID-19 outbreak, there was a decrease in passenger volume (60%–98.4%) as well as the number of flights (1.5%–82.6%). However, there were no such significant changes regarding the popularity ranking of most airports during the outbreak. Before this occurred (December 2019), most hub airports were in China (April 2020), and this trend remain similar during the COVID-19 outbreak. However, the values of the centrality measurement decreased significantly for most hub airports due to travel restrictions issued by the government. Elsevier Ltd. 2022-05 2022-02-17 /pmc/articles/PMC8849875/ /pubmed/35194345 http://dx.doi.org/10.1016/j.jairtraman.2022.102192 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Kuo, Pei-Fen Brawiswa Putra, I Gede Setiawan, Faizal Azmi Wen, Tzai-Hung Chiu, Chui-Sheng Sulistyah, Umroh Dian The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia |
title | The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia |
title_full | The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia |
title_fullStr | The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia |
title_full_unstemmed | The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia |
title_short | The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia |
title_sort | impact of the covid-19 pandemic on o-d flow and airport networks in the origin country and in northeast asia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8849875/ https://www.ncbi.nlm.nih.gov/pubmed/35194345 http://dx.doi.org/10.1016/j.jairtraman.2022.102192 |
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