This article focuses, in the context of epidemic models, on rare events that may possibly correspond to crisis situations from the perspective of public health. In general, no close analytic form for their occurrence probabilities is available, and crude Monte Carlo procedures fail. We show how recent intensive computer simulation techniques, such as interacting branching particle methods, can be used for estimation purposes, as well as for generating model paths that correspond to realizations of such events. Applications of these simulation-based methods to several epidemic models fitted from real datasets are also considered and discussed thoroughly.
Keywords: Monte Carlo simulation; genetic models; importance sampling; interacting branching particle system; multilevel splitting; rare-event analysis; stochastic epidemic model.
Copyright © 2015 John Wiley & Sons, Ltd.