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Optimizing spreading dynamics in interconnected networks.

Liming Pan1, Wei Wang1, Shimin Cai1

  • 1Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu611731, China.

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This study introduces an optimal strategy for adding multiple edges between networks to enhance disease spreading dynamics. The proposed method maximizes prevalence and minimizes outbreak thresholds, outperforming random or high-degree connections.

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Area of Science:

  • Complex Networks
  • Epidemiology
  • Statistical Physics

Background:

  • Optimizing spreading dynamics in interconnected networks is crucial.
  • Previous research primarily focused on single edge additions, leaving multi-edge strategies unexplored.
  • Understanding optimal interlayer structures is key for network-based interventions.

Purpose of the Study:

  • To develop a theoretical strategy for maximizing stationary spreading prevalence in interconnected networks.
  • To investigate the optimal placement of multiple edges between two isolated networks.
  • To simultaneously minimize the outbreak threshold and maximize prevalence.

Main Methods:

  • Utilized the susceptible-infected-susceptible (SIS) model.
  • Employed a discrete-time Markov chain approach for theoretical analysis.
  • Performed numerical simulations on synthetic and real-world network datasets.

Main Results:

  • Derived an approximate optimal strategy for adding multiple interconnecting edges.
  • The strategy effectively maximizes spreading prevalence near the critical point.
  • Demonstrated superior performance compared to random or high-degree node connections.

Conclusions:

  • The proposed strategy provides an effective method for optimizing spreading dynamics in interconnected systems.
  • This approach offers a dual benefit of increasing prevalence while lowering the outbreak threshold.
  • The findings are applicable to designing robust network interventions.