amei: An R Package for the Adaptive Management of Epidemiological Interventions

• Main Authors: Daniel Merl, Leah R. Johnson, Robert B. Gramacy, Marc Mangel
• Format: Article
• Language: English
• Published: Foundation for Open Access Statistics 2010-10-01
• Series: Journal of Statistical Software
• Subjects: SIR model; Bayesian inference; optimal decisions; Markov chain Monte Carlo
• Online Access: http://www.jstatsoft.org/v36/i06/paper

The <b>amei</b> package for <b>R</b> is a tool that provides a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic. Uncertainty regarding the underlying disease parameters is propagated through to the decision process via Bayesian posterior inference. The strategies produced through this framework are adaptive: vaccination schedules are iteratively adjusted to reflect the anticipated trajectory of the epidemic given the current population state and updated parameter estimates. This document briefly covers the background and methodology underpinning the implementation provided by the package and contains extensive examples showing the functions and methods in action.