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

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...

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Bibliographic Details
Published inEurophysics letters Vol. 89; no. 3; pp. 38009 - 38014
Main Authors Gómez, S, Arenas, A, Borge-Holthoefer, J, Meloni, S, Moreno, Y
Format Journal Article
LanguageEnglish
Published IOP Publishing 01.02.2010
EDP Sciences
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Summary: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.
Bibliography:ark:/67375/80W-2KBG19KH-6
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publisher-ID:epl12464
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0295-5075
1286-4854
DOI:10.1209/0295-5075/89/38009