Profiling of a network behind an infectious disease outbreak

Abstract
I describe a method to estimate a social network topology and diffusion parameters from the time sequence data of an infectious disease outbreak. The method is applicable to a stochastic diffusion process in a meta-population and SIR (Susceptible, Infectious, and Recovered) model over a social network. The method is based on the maximal likelihood estimation from the data on the number of the infectious persons. I demonstrate the performance of the method of profiling with the WHO (World Health Organization) report on SARS (Severe Acute Respiratory Syndrome) pandemic in 2003.
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