Impacts of Physical-Layer Information on Epidemic Spreading in Cyber-Physical Networked Systems
Year: 2025
Type: article
Abstract: Since Granell et al. proposed a multiplex network for information and epidemic propagation, researchers have explored how information propagation affects epidemic dynamics. However, the role of individuals acquiring information through physical interactions has received relatively less attention. In this work, we introduce a novel source of information: physical-layer information, and derive the epidemic outbreak threshold using the Microscopic Markov Chain Approach (MMCA). Our simulation results indicate that the outbreak threshold derived from the MMCA is consistent with the Monte Carlo (MC) simulation results, thereby confirming the accuracy of the theoretical model. Furthermore, we find that the physical-layer information effectively increases the population’s awareness density and the infection threshold$\beta _{c}$, while reducing the population’s infection density, thereby suppressing the spreading of the epidemic. Another interesting finding is that when the density of 2-simplex information is relatively high, the 2-simplex plays a role similar to pairwise interaction, significantly enhancing the population’s awareness density and effectively preventing large-scale epidemic outbreaks. In addition, our model works equally well for cyber-physical systems with similar interaction mechanisms, while we simulate and validate it in a real grid system.
Authors: Xianglai Yuan, Yichao Yao, Han Wu, Minyu Feng
Institutions: Southwest University, University of Southampton
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Awards: G6170836279, G6857572036
OpenAlex ID: W4408564010