Comparison between CAN and EAN on October 1^st to 31^st before and during the COVID-19 pandemic.

Comparison between CAN and EAN on October 1st to 31st before and during the COVID-19 pandemic.</p

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(RAR)</p

Evolution of air traffic and COVID-19 confirmed cases in Europe and China.

Evolution of air traffic and COVID-19 confirmed cases in Europe and China.</p

Resilience assessment framework for airport network.

Resilience assessment framework for airport network.</p

Comparison of resilience metrics in China and Europe during COVID-19 epidemic.

Comparison of resilience metrics in China and Europe during COVID-19 epidemic.</p

Efficiency comparison between Chinese and European airport networks based on different attack strategies.

Efficiency comparison between Chinese and European airport networks based on different attack strategies.</p

Resilience index of airports during COVID-19 pandemic.

Orange and green bar represent the resilience metrics of the first seven months of 2020 and entire year of 2020, respectively.</p

Comparison of network efficiency based on different recovery strategies.

(a)–(d) show the recovery process of the CAN and EAN based on degree and node strength recovery strategies; the red box and blue box in (e) and (f) represent variation in air traffic of airports in China and Europe in 2019 and 2020, respectively.</p

Network metrics.

Network metrics.</p

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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.</div