Modeling Airport Congestion Contagion by SIS Epidemic Spreading on Airline Networks

  • Klemens Köstler
  • Rommy Gobardhan
  • Alberto Ceria
  • Huijuan WangEmail author
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 881)


We model airport congestion contagion as an SIS spreading process on an airport transportation network to explain airport vulnerability. The vulnerability of each airport is derived from the US Airport Network data as its congestion probability. We construct three types of airline networks to capture diverse features such as the frequency and duration of flights. The weight of each link augments its infection rate in SIS spreading process. The nodal infection probability in the meta-stable state is used as estimate the vulnerability of the corresponding airport. We illustrate that our model could reasonably capture the distribution of nodal vulnerability and rank airports in vulnerability evidently better than the random ranking, but not significantly better than using nodal network properties. Such congestion contagion model not only allows the identification of vulnerable airports but also opens the possibility to reduce global congestion via congestion reduction in few airports.


Airline transportation network Epidemic spreading Network vulnerability 



This work is supported by Netherlands Organisation for Scientific Research NWO (TOP Grant no. 612.001.802).


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Klemens Köstler
    • 1
  • Rommy Gobardhan
    • 2
  • Alberto Ceria
    • 2
  • Huijuan Wang
    • 2
    Email author
  1. 1.Faculty of Aerospace EngineeringDelft University of TechnologyDelftThe Netherlands
  2. 2.Faculty of Electrical Engineering, Mathematics and Computer ScienceDelft University of TechnologyDelftThe Netherlands

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