Equivalence and its invalidation between non-Markovian and Markovian spreading dynamics on complex networks.

ABSTRACT: Epidemic spreading processes in the real world depend on human behaviors and, consequently, are typically non-Markovian in that the key events underlying the spreading dynamics cannot be described as a Poisson random process and the corresponding event time is not exponentially distributed. In contrast to Markovian type of spreading dynamics for which mathematical theories have been well developed, we lack a comprehensive framework to analyze and fully understand non-Markovian spreading processes. Here we develop a mean-field theory to address this challenge, and demonstrate that the theory enables accurate prediction of both the transient phase and the steady states of non-Markovian susceptible-infected-susceptible spreading dynamics on synthetic and empirical networks. We further find th

SUBMITTER: Feng M 

PROVIDER: S-EPMC6707263 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature