Effect of coupling structure on traffic-driven epidemic spreading in interconnected networks

Jie Chen, Xuegang Tan, Jinde Cao and Ming Li

Physica A: Statistical Mechanics and its Applications, 2022, vol. 607, issue C

Abstract: Interconnected networks, as the good abstraction of many real complex systems, have recently attracted a lot of attentions. In this paper, we propose a traffic-driven epidemic model in interconnected networks to show the effects of interplay induced by the coupled structure. Through simulations on interconnected scale-free networks, we find that in the free flow state, the disassortative coupling can effectively suppress the spreading of epidemics by introducing a more uniform distribution of traffic load, especially for high coupling strength. This result has also been confirmed by our mean-field solution. When the system is congested, the results show that the epidemic threshold is subject to the critical point of the traffic process, which depends on the coupling mode, traffic routing and allocation mechanism of node capacity. We also check our model under different routing protocols, the results show that our findings are robust, indicating that the coupling structure is the determining factor of the dynamics on interconnected networks.

Keywords: Interconnected networks; Epidemic spreading; Traffic dynamics; Coupling structure; Routing strategy (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007737

DOI: 10.1016/j.physa.2022.128215

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