Optimal intervention for an epidemic model under parameter uncertainty

Damian Clancy, Nathan Green

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Abstract

We will be concerned with optimal intervention policies for a continuous-time stochastic SIR (susceptible → infective → removed) model for the spread of infection through a closed population. In previous work on such optimal policies, it is common to assume that model parameter values are known; in reality, uncertainty over parameter values exists. We shall consider the effect upon the optimal policy of changes in parameter estimates, and of explicitly taking into account parameter uncertainty via a Bayesian decision-theoretic framework. We consider policies allowing for (i) the isolation of any number of infectives, or (ii) the immunisation of all susceptibles (total immunisation). Numerical examples are given to illustrate our results. © 2006 Elsevier Inc. All rights reserved.
Original languageEnglish
Pages (from-to)297-314
Number of pages17
JournalMathematical Biosciences
Volume205
Issue number2
DOIs
Publication statusPublished - Feb 2007

Keywords

  • Bayesian decision theory
  • Dynamic programming
  • General stochastic epidemic
  • Immunisation policies

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