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甲流阳性率抽样精度估计与样本量控制策略
引用本文:曹志冬,曾大军,王全意,王小莉,刘加奇.甲流阳性率抽样精度估计与样本量控制策略[J].系统工程理论与实践,2015,35(10):2467-2472.
作者姓名:曹志冬  曾大军  王全意  王小莉  刘加奇
作者单位:1. 中国科学院 自动化研究所 复杂系统管理与控制国家重点实验室, 北京 100190;2. 北京市疾病预防控制中心, 北京 100013
基金项目:国家自然科学基金(91024030, 71025001, 91224008, 91324007)
摘    要:基于2009年8月3日11月14日北京市甲型H1N1病例的阳性率抽样数据,计算得到了后验精度估计.实验结果表明,在置信水平1-α=0.95的条件下,北京市甲型H1N1阳性率抽样检测的绝对误差均没有超过0.1,处于可控水平.甲流疫情早期,抽样检测的相对误差较大,37周以前的相对误差大于0.5.随着疫情发展,相对误差逐步降低,估计结果趋于可靠,42周后的相对误差小于0.2.最后,针对阳性病例样本检测的问题,提出了基于精度控制的最优样本量控制策略,探索了不同条件下边际样本量的变化规律,分析了阳性率与绝对误差组合控制下的最优样本量估计.

关 键 词:精度估计  样本量  样本量策略  控制  抽样检测  阳性率  
收稿时间:2014-12-26

Precision estimation and sample size planning to test influenza A H1N1 positive rate
CAO Zhi-dong,ZENG Da-jun,WANG Quan-yi,WANG Xiao-li,LIU Jia-qi.Precision estimation and sample size planning to test influenza A H1N1 positive rate[J].Systems Engineering —Theory & Practice,2015,35(10):2467-2472.
Authors:CAO Zhi-dong  ZENG Da-jun  WANG Quan-yi  WANG Xiao-li  LIU Jia-qi
Institution:1. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;2. Beijing Center for Disease Control and Prevention, Beijing 100013, China
Abstract:Using the data in the influenza A H1N1 positive rate of sampling from August 3, 2009 to November 14, Beijing, we estimated the precision of absolute error and relative error. During the epidemic, absolute error of the H1N1 positive rate was less than 0.1 under the confidence level of 1-α=0.95, this error was at a controllable level. The relative error of the H1N1 positive rate was large at the early phase of influenza A H1N1 transmission, > 0.5 before 37 weeks. With the development of the epidemic, the relative error decreased gradually, which means that the result tends to be a reliable estimate. The relative error was less than 0.2 after 42 weeks. Finally, this paper provided a sample size planning based on precision control for sampling test of positive cases. We argued the marginal changes in sample size with a series of conditions. Optimal sample sizes were estimated under different combinations of positive rate and absolute error.
Keywords:precision estimation  sample size  sample size planning  control  sampling test  positive rate  
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