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A novel resilience analysis methodology for airport networks system from the perspective of different epidemic prevention and control policy responses.
Guo, Jiuxia; Yang, Zongxin; Zhong, Qingwei; Sun, Xiaoqian; Wang, Yinhai.
  • Guo J; College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, Sichuan, China.
  • Yang Z; College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, Sichuan, China.
  • Zhong Q; College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, Sichuan, China.
  • Sun X; National Key Laboratory of CNS/ATM, School of Electronic and Information Engineering, Beihang University, Beijing, China.
  • Wang Y; Department of Civil and Environmental, University of Washington, Seattle, WA, United States of America.
PLoS One ; 18(2): e0281950, 2023.
Article in English | MEDLINE | ID: covidwho-2261571
ABSTRACT
As the COVID-19 pandemic fades, the aviation industry is entering a fast recovery period. To analyze airport networks' post-pandemic resilience during the recovery process, this paper proposes a Comprehensive Resilience Assessment (CRA) model approach using the airport networks of China, Europe, and the U.S.A as case studies. The impact of COVID-19 on the networks is analyzed after populating the models of these networks with real air traffic data. The results suggest that the pandemic has caused damage to all three networks, although the damages to the network structures of Europe and the U.S.A are more severe than the damage in China. The analysis suggests that China, as the airport network with less network performance change, has a more stable level of resilience. The analysis also shows that the different levels of stringency policy in prevention and control measures during the epidemic directly affected the recovery rate of the network. This paper provides new insights into the impact of the pandemic on airport network resilience.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Aviation / COVID-19 Type of study: Observational study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0281950

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Aviation / COVID-19 Type of study: Observational study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0281950