Estimating in real time the efficacy of measures to control emerging communicable diseases
Estimating in real time the efficacy of measures to control emerging communicable diseases
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DOI：
10.1093/aje/kwj274
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发表时间：
2006-09-15
影响因子：
5
通讯作者：
Valleron, Alain-Jacques
中科院分区：
文献类型：
--
作者：
Cauchemez, Simon;Boelle, Pierre-Yves;Valleron, Alain-Jacques
控制新出现的传染病需要迅速采取检疫等措施。对这些措施效果的评估也必须迅速进行。在本文中，作者提出了一个实时监测控制措施有效性的框架。对疫情期间繁殖数R（单个感染者产生的平均病例数）的贝叶斯估计使他们能够迅速判断疫情是否得到控制（R < 1）。只需要计数和症状发作时间，以及来自一部分病例的追踪信息。马尔可夫链蒙特卡罗和蒙特卡罗抽样被用来推断R的时间模式，直到最后一次观测。在严重急性呼吸系统综合征样暴发的模拟研究中，研究了该方法的操作特性。在这一特殊情况下，至少70%的疫情在2周后可以检测到缺乏有效性的控制措施（r> = 1.1），得出错误结论的概率低于5%。当控制措施有效（R = 0.5）时，2周后68%的疫情和3周后92%的疫情可证明这种情况，得出错误结论的概率小于5%。
Controlling an emerging communicable disease requires prompt adoption of measures such as quarantine. Assessment of the efficacy of these measures must be rapid as well. In this paper, the authors present a framework to monitor the efficacy of control measures in real time. Bayesian estimation of the reproduction number R (mean number of cases generated by a single infectious person) during an outbreak allows them to judge rapidly whether the epidemic is under control (R < 1). Only counts and time of onset of symptoms, plus tracing information from a subset of cases, are required. Markov chain Monte Carlo and Monte Carlo sampling are used to infer the temporal pattern of R up to the last observation. The operating characteristics of the method are investigated in a simulation study of severe acute respiratory syndrome-like outbreaks. In this particular setting, control measures lacking efficacy (R >= 1.1) could be detected after 2 weeks in at least 70% of the epidemics, with less than a 5% probability of a wrong conclusion. When control measures are efficacious (R = 0.5), this situation may be evidenced in 68% of the epidemics after 2 weeks and 92% of the epidemics after 3 weeks, with less than a 5% probability of a wrong conclusion.