On Computer-Intensive Simulation and Estimation Methods for Rare Event Analysis in Epidemic Models

TL;DR

This paper explores advanced simulation techniques like interacting branching particle methods to estimate rare event probabilities in epidemic models, where traditional methods fail, providing new tools for public health crisis analysis.

Contribution

It introduces the application of recent computer simulation methods to estimate and generate rare epidemic events, addressing limitations of crude Monte-Carlo procedures.

Findings

Effective estimation of rare epidemic event probabilities.

Successful generation of epidemic model paths for rare events.

Application to multiple epidemic models demonstrating practicality.

Abstract

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 are also considered and discussed thoroughly.