Table of Contents
ISRN Epidemiology
Volume 2013, Article ID 345618, 5 pages
http://dx.doi.org/10.5402/2013/345618
Research Article

SEIR Epidemic Dynamics in Random Networks

Institute for Cyber Security, The University of Texas at San Antonio, San Antonio, TX 78249, USA

Received 19 December 2012; Accepted 8 January 2013

Academic Editors: A. Finckh, M. Lancellotti, and R. Zhao

Copyright © 2013 Yilun Shang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Predicting disease transmission on complex networks has attracted considerable recent attention in the epidemiology community. In this paper, we develop a low-dimensional system of nonlinear ordinary differential equations to model the susceptible-exposed-infectious-recovered (SEIR) epidemics on random network with arbitrary degree distributions. Both the final size of epidemics and the time-dependent behaviors are derived within our simple framework. The underlying network is represented by the configuration model, which appropriately accounts for the heterogeneity and finiteness of the degree observed in a variety of real contact networks. Moreover, a generalized model where the infectious state of individual can be skipped is treated in brief.