Correlation between transition probability and network structure in epidemic model

Abstract

In discrete-time dynamics, it is frequently assumed that the transition probabilities (e.g., the recovery probability) are independent of the network structure. However, there is a lack of empirical evidence to support this claim in large time intervals. This paper presents the nonlinear relations between the rates (in continuous-time dynamics) and probabilities of the susceptible-infected-susceptible model on annealed and static networks. It is shown that the transition probabilities are affected not only by the rates and the time interval, but also by the network structure. The correctness of the nonlinear relations on networks is verified based on theoretical calculation and Monte Carlo simulation.

References in corpus (20)

• Epidemic spreading in scale-free networks
• Epidemic processes in complex networks
• Dynamical interplay between awareness and epidemic spreading in multiplex networks
• Generation of uncorrelated random scale-free networks
• Discrete-time Markov chain approach to contact-based disease spreading in complex networks
• High-accuracy approximation of binary-state dynamics on networks
• Fundamentals of spreading processes in single and multilayer complex networks
• Pair quenched mean-field theory for the susceptible-infected-susceptible model on complex networks
• Effective approach to epidemic containment using link equations in complex networks
• Non-perturbative heterogeneous mean-field approach to epidemic spreading in complex networks
• The limitations of discrete-time approaches to continuous-time contagion dynamics
• Solving the Dynamic Correlation Problem of the Susceptible-Infected-Susceptible Model on Networks
• Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks
• Chaos and unpredictability in evolutionary dynamics in discrete time
• High prevalence regimes in the pair quenched mean-field theory for the susceptible-infected-susceptible model on networks
• Non-Markovian epidemic spreading on temporal networks
• Continuous- and discrete-time Glauber dynamics. First- and second-order phase transitions in mean-field Potts models
• The nature of epidemic criticality in temporal networks
• Multistage onset of epidemics in heterogeneous networks
• The universality of physical images at relative timescales on multiplex networks