Extinction times of epidemic outbreaks in networks

Abstract

In the Susceptible-Infectious-Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold.

References in corpus (2)

• Networks and the Epidemiology of Infectious Disease
• Law of large numbers for the SIR epidemic on a random graph with given degrees

Cited by in corpus (10)

• Temporal network structures controlling disease spreading
• Epidemic extinction and control in heterogeneous networks
• Interplay between the local information based behavioral responses and the epidemic spreading in complex networks
• Information content of contact-pattern representations and predictability of epidemic outbreaks
• Heterogeneous network epidemics: real-time growth, variance and extinction of infection
• Time evolution of predictability of epidemics on networks
• Predicting epidemic evolution on contact networks from partial observations
• Large-deviations of the SIR model around the epidemic threshold
• Expected Extinction Times of Epidemics with State-Dependent Infectiousness
• How network properties and epidemic parameters influence stochastic SIR dynamics on scale-free random networks