The Cost of an Epidemic over a Complex Network: A Random Matrix Approach
In this paper we quantify the total economic impact of an epidemic over a complex network using tools from random matrix theory. Incorporating the direct and indirect costs of infection, we calculate the disease cost in the large graph limit for an SIS (Susceptible - Infected - Susceptible) infection process. We also give an upper bound on this cost for arbitrary finite graphs and illustrate both calculated costs using extensive simulations on random and real-world networks. We extend these calculations by considering the total social cost of an epidemic, accounting for both the immunization and disease costs for various immunization strategies and determining the optimal immunization. Our work focuses on the transient behavior of the epidemic, in contrast to previous research, which typically focuses on determining the steady-state system equilibrium.
A preliminary version of this work was presented at GameNets, 2011. The authors would like to thank Professor K. Mani Chandy and Prof. Leeat Yariv for useful comments and suggestions. This work was supported in part by the National Science Foundation under grants NSF CNS-0846025, CCF-0729203, CNS-0932428 and CCF-1018927, by the Office of Naval Research under the MURI grant N00014-08-1-0747, and by Caltech's Lee Center for Advanced Networking.
||3.0 MB||Preview Download|