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    Impacts of bridging nodes on the epidemic activation mechanisms

    José Carlos M. Silva1,*, Diogo H. Silva2,*,†, Wesley Cota1, Francisco A. Rodrigues2, and Silvio C. Ferreira1,3,‡,§

    • 1Departamento de Física, Universidade Federal de Viçosa, Viçosa, Minas Gerais 36570-900, Brazil
    • 2Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, São Paulo 13566-590, Brazil
    • 3National Institute of Science and Technology for Complex Systems, Rio de Janeiro 22290-180, Brazil

    • *These authors contributed equally to this work.
    • †Present address: Instituto Federal Fluminense, Campus Quissamã, Piteiras-Quissamã, Rio de Janeiro 28735-970, Brazil.
    • ‡Contact author: silviojr@ufv.br
    • §On leave at Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, São Paulo 13566-590, Brazil.

    Phys. Rev. E 113, 044308 – Published 17 April, 2026

    DOI: https://doi.org/10.1103/rlr4-w2kt

    Abstract

    Bridging nodes, which connect critical components of a network, play an important role in maintaining structural integrity and facilitating communication within the network, representing indirect yet relevant connections. Epidemic triggering mechanisms in networks often involve long-range mutual activation of hubs, mediated by paths composed of low-degree nodes. While low-degree nodes are abundant in networks, their role in bridging central nodes in epidemic activation mechanisms has not been thoroughly analyzed. Starting with a backbone network with a power-law degree distribution, we investigate the role of adding degree-2 bridging nodes that are preferentially attached to hubs. Our findings reveal that bridging nodes can mediate an indirect feedback interaction between hubs that modifies the epidemic localization and activation mechanisms of the epidemic processes with recurrent infections. In particular, the collective activation observed in the presence of waning immunity, which produces a finite epidemic threshold in power-law networks with degree exponent γ>3, is altered to a localized activation with a vanishing threshold. Our numerical results are analytically supported by the nonbacktracking matrix properties that emerge in the recurrent dynamical message-passing theory.

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