Bao Xiaoge, Ji Peng, Lin Wei, Perc Matjaž, Kurths Jürgen
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, People's Republic of China.
Research Institute of Intelligent Complex Systems and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, People's Republic of China.
R Soc Open Sci. 2021 Nov 10;8(11):210682. doi: 10.1098/rsos.210682. eCollection 2021 Nov.
Air travel has been one of the hardest hit industries of COVID-19, with many flight cancellations and airport closures as a consequence. By analysing structural characteristics of the Official Aviation Guide flight data, we show that this resulted in an increased average distance between airports, and in an increased number of long-range routes. Based on our study of network robustness, we uncover that this disruption is consistent with the impact of a mixture of targeted and random global attack on the worldwide air transportation network. By considering the individual functional evolution of airports, we identify anomalous airports with high centrality but low degree, which further enables us to reveal the underlying transitions among airport-specific representations in terms of both geographical and geopolitical factors. During the evolution of the air transportation network, we also observe how the network attempted to cope by shifting centralities between different airports around the world. Since these shifts are not aligned with optimal strategies for minimizing delays and disconnects, we conclude that they are consistent with politics trumping science from the viewpoint of epidemic containment and transport.
航空旅行是受新冠疫情冲击最严重的行业之一，导致许多航班取消和机场关闭。通过分析官方航空指南航班数据的结构特征，我们发现这导致了机场之间平均距离的增加以及远程航线数量的增多。基于我们对网络稳健性的研究，我们发现这种中断与针对全球航空运输网络的定向和随机全球攻击混合影响一致。通过考虑机场的个体功能演变，我们识别出具有高中心性但低度数的异常机场，这进一步使我们能够从地理和地缘政治因素方面揭示机场特定表征之间的潜在转变。在航空运输网络的演变过程中，我们还观察到网络如何试图通过在全球不同机场之间转移中心性来应对。由于这些转移与最小化延误和中断的最优策略不一致，我们得出结论，从疫情防控和运输的角度来看，它们与政治凌驾于科学之上是一致的。
