Dynamics of SIR Model on Random Networks

Abstract

we focus on studying the dynamics of infectious disease spreading SIR model on random networks. We investigate how various parameters of the network influence the behavior of spreading and analyze the occurrence of phase transitions within this networkframework. Our analysis reveals the critical role of network connectivity in shaping the dynamics of disease transmission and highlights the presence of mean-field phase transitions.
Additionally, we employ both analytical techniques and simulation methods to extract critical thresholds for the model and compare them for validation. By delving into the intricate dynamics of disease spreading on random networks, this work offers valuable
insights into the mechanisms driving epidemic propagation and provides a theoretical foundation for studying disease control strategies and public health interventions.