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Joan T Matamalas1, Alex Arenas1, Sergio Gómez1

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This study introduces a new method for epidemic containment by deactivating crucial links in complex networks. This approach effectively controls disease spread while maintaining network functionality.

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Area of Science:

  • Epidemiology
  • Network Science
  • Mathematical Modeling

Background:

  • Epidemic containment in complex networks is critical for managing large-scale infections.
  • Current strategies often focus on node isolation, neglecting the role of links in disease transmission.
  • Understanding link contributions is essential for effective epidemic control.

Purpose of the Study:

  • To develop a model for assessing the contribution of links to epidemic spreading processes in complex networks.
  • To propose a novel epidemic containment strategy based on link deactivation.
  • To validate the proposed model and strategy using synthetic and real-world network data.

Main Methods:

  • Formulation of discrete-time governing equations to analyze link contributions.
  • Development of a link-based epidemic containment scheme.
  • Validation through simulations on synthetic and real networks.

Main Results:

  • The proposed model accurately determines epidemic incidence and critical thresholds.
  • Link deactivation proves to be an effective strategy for epidemic containment.
  • The approach provides a quantitative assessment of link importance in disease transmission.

Conclusions:

  • Epidemic containment via link deactivation is a promising strategy for controlling disease spread.
  • This method offers an effective way to manage epidemics while preserving network functionality.
  • The findings are applicable to various networks, including air transportation systems.