Seminar in PSA 107

ABSTRACT

Title:  Infection dynamics on complex networks.     

By:    Zonghua Liu, ASU Department of Mathematics & Statistics

Abstract: 

Recently we have considered the entire spectrum of architectures of general networks, ranging from being heterogeneous (scale-free) to homogeneous (random), and investigated the infection dynamics by using a three-state epidemiological model that does not involve the mechanism of self-recovery. This model is relevant to realistic situations such as the propagation of a flu virus or information over a social network. Our physical analysis and computations indicate that, (1) regardless of
the network architecture, there exists a substantial fraction of nodes that can never be infected, and (2) heterogeneous networks are relatively more robust against spreads of infection as compared with homogeneous networks. We have also addressed the problem of immunization for preventing wide spread of infection, with the result that targeted immunization is effective for heterogeneous networks.

Reference:

Z. Liu, Y.-C. Lai, and N. Ye, ``Propagation and immunization of infection on general networks with both homogenous and heterogeneous components,'' Physical Review E 67, 031911 (2003). [This work has been selected by the Virtual Journal of Biological Physics Research for the April 1, 2003 issue (http://www.vjbio.org).]