Modeling Contagion Dynamics Based on Individual Contact Patterns Using Bond Percolation Theory

In recent years, various infectious diseases have erupted frequently worldwide, which has had a huge impact on people's health and social development. Therefore, it is necessary to study the transmission mechanism and control strategies of infectious diseases. In this paper, we propose a new epidemic transmission mode by using bond percolation in quantum physics. We character the real-life individual contact patterns as different transmission path trees and calculate binomial distribution function
$P^{*}(p,\ n)$
based on bond percolation. We fuse bond percolation into the SEIRD model and study percolation patterns how to influence outbreak threshold of epidemics. By analyzing key factors in the transmission process such as blocking probability, number of transmission paths, and configuration patterns, it shows that complex number of transmission paths will lead to larger scale of infection and virus transmission effectively suppressed by blocking probability. Then, experiments were conducted on BA scale-free networks to study the temporal relationships between different nodes and the impact of network structure on virus propagation. The experimental results demonstrate the correctness and effectiveness of the proposed model. The model effectively describes the epidemic spreading process under different contact modes and the interactions between different nodes in networks, which provides theoretical basis and practical value for controlling epidemics.