Non-Markovian epidemic spreading on temporal networks
arXiv:2303.04740 · doi:10.1016/j.chaos.2023.113664
Abstract
Many empirical studies have revealed that the occurrences of contacts associated with human activities are non-Markovian temporal processes with a heavy tailed inter-event time distribution. Besides, there has been increasing empirical evidence that the infection and recovery rates are time-dependent. However, we lack a comprehensive framework to analyze and understand non-Markovian contact and spreading processes on temporal networks. In this paper, we propose a general formalism to study non-Markovian dynamics on non-Markovian temporal networks. We find that, under certain conditions, non-Markovian dynamics on temporal networks are equivalent to Markovian dynamics on static networks. Interestingly, this result is independent of the underlying network topology.
References in corpus (8)
- Activity driven modeling of time varying networks
- A generalized model of social and biological contagion
- Equivalence between non-Markovian and Markovian dynamics in epidemic spreading processes
- Percolation in self-similar networks
- Non-Markovian SIR epidemic spreading model
- Modeling temporal networks using random itineraries
- Burstiness in activity-driven networks and the epidemic threshold
- Unifying continuous, discrete, and hybrid susceptible-infected-recovered processes on networks