A stochastic SIS epidemic model with heterogeneous contacts



Downloads per month over past year

Economou, A. and Gómez-Corral, Antonio and López-García, M. (2015) A stochastic SIS epidemic model with heterogeneous contacts. Physica A: Statistical Mechanics and its Applications, 421 . pp. 78-97. ISSN 0378-4371

[thumbnail of GCorral202elsevier.pdf] PDF
Restringido a Repository staff only


Official URL: http://www.sciencedirect.com/science/article/pii/S0378437114008929


A stochastic model for the spread of an SIS epidemic among a population consisting of N individuals, each having heterogeneous infectiousness and/or susceptibility, is considered and its behavior is analyzed under the practically relevant situation when N is small. The model is formulated as a finite time-homogeneous continuous-time Markov chain X. Based on an appropriate labeling of states, we first construct its infinitesimal rate matrix by using an iterative argument, and we then present an algorithmic procedure for computing steady-state measures, such as the number of infected individuals, the length of an outbreak, the maximum number of infectives, and the number of infections suffered by a marked individual during an outbreak. The time till the epidemic extinction is characterized as a phase-type random variable when there is no external source of infection, and its Laplace-Stieltjes transform and moments are derived in terms of a forward elimination backward substitution solution. The inverse iteration method is applied to the quasi-stationary distribution of X, which provides a good approximation of the process X at a certain time, conditional on non-extinction, after a suitable waiting time. The basic reproduction number R-0 is defined here as a random variable, rather than an expected value.

Item Type:Article
Uncontrolled Keywords:Basic reproduction number; Markov chain model; Maximum number of infected individuals; Number of infections; Quasi-stationary regime; Stochastic SIS epidemic
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:29483
Deposited On:13 Apr 2015 11:30
Last Modified:30 Nov 2020 15:11

Origin of downloads

Repository Staff Only: item control page