Clancy Damian, Green Nathan
Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK.
Math Biosci. 2007 Feb;205(2):297-314. doi: 10.1016/j.mbs.2006.08.023. Epub 2006 Sep 7.
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.
我们将关注用于通过封闭人群中感染传播的连续时间随机SIR(易感者→感染者→康复者)模型的最优干预策略。在之前关于此类最优策略的工作中,通常假设模型参数值是已知的;但在现实中,参数值存在不确定性。我们将考虑参数估计变化对最优策略的影响,以及通过贝叶斯决策理论框架明确考虑参数不确定性的影响。我们考虑允许(i)隔离任意数量感染者,或(ii)对所有易感者进行免疫(全面免疫)的策略。给出了数值示例来说明我们的结果。