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.
Chaos (Woodbury, N.Y.)
|November 3, 2019
Summary
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.
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.
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