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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 that the existence of equivalence between non-Markovian and Markovian spreading depends on a specific edge activation mechanism. In particular, when temporal correlations are absent on active edges, the equivalence can be expected; otherwise, an exact equivalence no longer holds.

SUBMITTER: Feng M 

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

REPOSITORIES: biostudies-literature

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

Feng Mi M   Cai Shi-Min SM   Tang Ming M   Lai Ying-Cheng YC  

Nature communications 20190823 1


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 processe  ...[more]

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