Epidemics in networks: A master equation approach
arXiv:1604.01049 · doi:10.1088/1751-8113/49/6/065001
Abstract
A problem closely related to epidemiology, where a subgraph of 'infected' links is defined inside a larger network, is investigated. This subgraph is generated from the underlying network by a random variable, which decides whether a link is able to propagate a disease/information. The relaxation timescale of this random variable is examined in both annealed and quenched limits, and the effectiveness of propagation of disease/information is analyzed. The dynamics of the model is governed by a master equation and two types of underlying network are considered: one is scale-free and the other has exponential degree distribution. We have shown that the relaxation timescale of the contagion variable has a major influence on the topology of the subgraph of infected links, which determines the efficiency of spreading of disease/information over the network.
References in corpus (15)
- Emergence of scaling in random networks
- Error and attack tolerance of complex networks
- Epidemic spreading in scale-free networks
- The large-scale organization of metabolic networks
- Network robustness and fragility: Percolation on random graphs
- Resilience of the Internet to random breakdowns
- Critical phenomena in complex networks
- Evolution of the social network of scientific collaborations
- Epidemic dynamics and endemic states in complex networks
- Breakdown of the Internet under intentional attack
- Absence of epidemic threshold in scale-free networks with connectivity correlations
- Ferromagnetic Phase Transition in Barabasi-Albert Networks
- Mean field solution of the Ising model on a Barabasi-Albert network
- Voter Model with Time dependent Flip-rates
- Diluted antiferromagnet in a ferromagnetic enviroment