EPIDEMIC SPREADING IN A COMPLEX NETWORK-Reference-Cited by-同舟云学术

EPIDEMIC SPREADING IN A COMPLEX NETWORK

Published:2007-09 Issue:09 Volume:18 Page:1453-1458
ISSN:0129-1831
Container-title:International Journal of Modern Physics C
language:en
Short-container-title:Int. J. Mod. Phys. C

Author:

HE MINGFENG¹,WANG BIN²,XIAO XINHUA³,SUN LEI⁴

Affiliation:

1. Department of Applied Mathematics and College of Advanced Science and Technology, Dalian University of Technology, Dalian, 116024, China

2. School of Enviromental and Biological Science and Technology and Institute of University Students' Innovation, Dalian University of Technology, Dalian, 116024, China

3. School of Electronic and Information Engineering and Institute of University Students' Innovation, Dalian University of Technology, Dalian, 116024, China

4. School of Chemical Engineering and Institute of University Students' Innovation, Dalian University of Technology, Dalian, 116024, China

Abstract

In this paper, a complex network is constructed as comprising "clusters" which can be interpreted as a group of people with regular contacts. In each "cluster" individuals contact fully. A given individual contact individuals in other "clusters" by links. Then we study the dynamical behavior of the epidemiological model in this complex network, and discuss the influence of the intra-cluster infection probability, the extra-cluster infection probability, and infection time before being detected on epidemic dynamics. The results show that extra-cluster infection reduction, early detection and swift isolation are good infection control practices.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0129183107011522

Reference19 articles.

1. A contribution to the mathematical theory of epidemics

2. Statistical mechanics of complex networks

3. Evolution of networks

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