@article {1060,
title = {Linking population-level models with growing networks: a class of epidemic models},
journal = {Phys Rev E Stat Nonlin Soft Matter Phys},
volume = {72},
number = {4 Pt 2},
year = {2005},
pages = {046110},
abstract = {We introduce a class of growing network models that are directly applicable to epidemiology. We show how to construct a growing network model (individual-level model) that generates the same epidemic-level outcomes as a population-level ordinary differential equation (ODE) model. For concreteness, we analyze the susceptible-infected (SI) ODE model of disease invasion. First, we give an illustrative example of a growing network whose population-level variables are compatible with those of this ODE model. Second, we demonstrate that a growing network model can be found that is equivalent to the Crump-Mode-Jagers (CMJ) continuous-time branching process of the SI ODE model of disease invasion. We discuss the computational advantages that our growing network model has over the CMJ branching process.},
keywords = {Fundamentals of Theoretical Epidemiology},
url = {http://www.semel.ucla.edu/sites/all/files/biomedicalmodeling/pdf/article_pre_networks_2005.pdf},
author = {Breban, R. and Vardavas, R. and S Blower}
}