Abstract
Researchers have been faced with the challenge of understanding the dynamics surrounding the spread of an epidemic in complex networks, a key topic in network science. Epidemic models have been applied in different propagation processes such as information transmission, epidemiological research, and computer virus propagation. One of such epidemic models is the contact process.
The contact process (also known as the susceptible-infected-susceptible (SIS) process) is a mathematical model with application in mathematical biology, epidemiology, computational sciences, physics, and social sciences used in describing the spread of an infectious disease through a population. In this model, individuals represent nodes in a network, and each individual can be in one of two states: infected or susceptible. The dynamics of the process are characterized by the fact that infected individuals can transmit the infection to susceptible neighbours and that infected individuals can recover.
By analyzing the behaviour of the contact process on random graph structures, this study addresses the central question of the metastable distribution of the infected fraction of the population (represented by the random graph structures). This knowledge is crucial for predicting the potential long-term impact of epidemics and developing effective control strategies.
