title: Epidemics on networks with large initial conditions or changing structure.
abstract: In this paper we extend previous work deriving dynamic equations governing infectious disease spread on networks. The previous work has implicitly assumed that the disease is initialized by an infinitesimally small proportion of the population. Our modifications allow us to account for an arbitrarily large initial proportion infected. This helps resolve an apparent paradox in earlier work whereby the number of susceptible individuals could increase if too many individuals were initially infected. It also helps explain an apparent small deviation that has been observed between simulation and theory. An advantage of this modification is that it allows us to account for changes in the structure or behavior of the population during the epidemic.
authors.affiliation: School of Mathematical Sciences, School of Biological Sciences, and Monash Academy for Cross & Interdisciplinary Mathematics, Monash University, Melbourne, Victoria, Australia.
authors.forename: Joel C
authors.initials: JC
authors.lastname: Miller
mesh_terms: D000465:Algorithms; D003141:Communicable Diseases / Q000453:epidemiology; D058872:Epidemics; D006801:Humans; D008962:Models, Theoretical; D015203:Reproducibility of Results