Discrete-time Markov chain approach to contact-based disease spreading in complex networks

By Sergio Gómez, Alex Arenas, Javier Borge-Holthoefer, Sandro Meloni, Yamir Moreno. 2009

495 citations recorded by the source corpus.

Many epidemic processes in networks spread by stochastic contacts among their connected vertices. There are two limiting cases widely analyzed in the physics literature, the so-called contact process (CP) where the contagion is expanded at a certain rate from an infected vertex to one neighbor at a time, and the reactive process (RP) in which an infected individual effectively contacts all its neighbors to expand the epidemics. However, a more realistic scenario is obtained from the interpolation between these two cases, considering a certain number of stochastic contacts per unit time. Here we propose a discrete-time formulation of the problem of contact-based epidemic spreading. We resolve a family of models, parameterized by the number of stochastic contact trials per unit time, that range from the CP to the RP. In contrast to the common heterogeneous mean-field approach, we focus on the probability of infection of individual nodes. Using this formulation, we can construct the whole phase diagram of the different infection models and determine their critical properties.

Subfields: Modeling and Simulation, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/163b4570595e2fbd9d1e82abbf740df37ae2f0b0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Modeling and Simulation

Zhen Wang

In Statistical and Nonlinear Physics

Citations in the corpus

The structure and dynamics of multilayer networks (2014, background): “[255] for SIS, and that represents an intermediate step between the accurate microscopic equations [235] and the HMF approximation.”