Recovery rate affects the effective epidemic threshold with synchronous updating

Abstract

Accurate identification of effective epidemic threshold is essential for understanding epidemic dynamics on complex networks. The existing studies on the effective epidemic threshold of the susceptible-infected-removed (SIR) model generally assume that all infected nodes immediately recover after the infection process, which more or less does not conform to the realistic situation of disease. In this paper, we systematically study the effect of arbitrary recovery rate on the SIR spreading dynamics on complex networks. We derive the theoretical effective epidemic threshold and final outbreak size based on the edge-based compartmental theory. To validate the proposed theoretical predictions, extensive numerical experiments are implemented by using asynchronous and synchronous updating methods. When asynchronous updating method is used in simulations, recovery rate does not affect the final state of spreading dynamics. But with synchronous updating, we find that the effective epidemic threshold decreases with recovery rate, and final outbreak size increases with recovery rate. A good agreement between the theoretical predictions and numerical results are observed on both synthetic and real-world networks. Our results extend the existing theoretical studies, and help us to understand the phase transition with arbitrary recovery rate.

arXiv comment7 pages, 4 figures

References in corpus (23)

• Statistical mechanics of complex networks
• Epidemic processes in complex networks
• The spread of epidemic disease on networks
• Mixing patterns in networks
• Critical phenomena in complex networks
• Epidemic dynamics and endemic states in complex networks
• Adaptive Coevolutionary Networks: A Review
• Epidemic outbreaks in complex heterogeneous networks
• Velocity and hierarchical spread of epidemic outbreaks in scale-free networks
• Thresholds for epidemic spreading in networks
• Discrete-time Markov chain approach to contact-based disease spreading in complex networks
• Evolutionary Games and Computer Simulations
• A message passing approach for general epidemic models
• Cut-offs and finite size effects in scale-free networks
• Epidemic spreading on complex networks with general degree and weight distributions
• Edge-Based Compartmental Modeling for Infectious Disease Spread Part III: Disease and Population Structure
• Non-perturbative heterogeneous mean-field approach to epidemic spreading in complex networks
• The dynamics of critical Kauffman networks under asynchronous stochastic update
• A message-passing approach for recurrent-state epidemic models on networks
• Boosting cooperation by involving extortion in spatial Prisoner's dilemma
• Dynamic message-passing equations for models with unidirectional dynamics
• Epidemic variability in complex networks
• Temporal percolation of the susceptible network in an epidemic spreading

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