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Correlation between transition probability and network structure in epidemic model

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  • Cai, Chao-Ran
  • Cai, Dong-Qian

Abstract

In discrete-time dynamics, it is frequently assumed that the transition probabilities (e.g., the recovery probability) are independent of the network structure. However, there is a lack of empirical evidence to support this claim in large time intervals. This paper presents the nonlinear relations between the rates (in continuous-time dynamics) and probabilities of the susceptible–infected–susceptible model on annealed and static networks. It is shown that the transition probabilities are affected not only by the rates and the time interval, but also by the network structure. The correctness of the nonlinear relations on networks is verified based on theoretical calculation and Monte Carlo simulation.

Suggested Citation

  • Cai, Chao-Ran & Cai, Dong-Qian, 2025. "Correlation between transition probability and network structure in epidemic model," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925001559
    DOI: 10.1016/j.chaos.2025.116142
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    References listed on IDEAS

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    1. Chang, Xin & Cai, Chao-Ran, 2021. "Analytical computation of the epidemic prevalence and threshold for the discrete-time susceptible–infected–susceptible dynamics on static networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    2. Lamata-Otín, Santiago & Reyna-Lara, Adriana & Gómez-Gardeñes, Jesús, 2024. "Integrating Virtual and Physical Interactions through higher-order networks to control epidemics," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).
    3. Chang, Xin & Cai, Chao-Ran & Zhang, Ji-Qiang & Yang, Wen-Li, 2024. "The universality of physical images at relative timescales on multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
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