PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho Kawaguchi, Saitama 332-0012, Japan.
Math Biosci Eng. 2011 Jan;8(1):49-64. doi: 10.3934/mbe.2011.8.49.
The influenza A (H1N1) pandemic 2009 posed an epidemiological challenge in ascertaining all cases. Although the counting of all influenza cases in real time is often not feasible, empirical observations always involve diagnostic test procedures. This offers an opportunity to jointly quantify transmission dynamics and diagnostic accuracy. We have developed a joint estimation procedure that exploits parsimonious models to describe the epidemic dynamics and that parameterizes the number of test positives and test negatives as a function of time. Our analyses of simulated data and data from the empirical observation of interpandemic influenza A (H1N1) from 2007-08 in Japan indicate that the proposed approach permits a more precise quantification of the transmission dynamics compared to methods that rely on test positive cases alone. The analysis of entry screening data for the H1N1 pandemic 2009 at Tokyo-Narita airport helped us quantify the very limited specificity of influenza-like illness in detecting actual influenza cases in the passengers. The joint quantification does not require us to condition diagnostic accuracy on any pre-defined study population. Our study suggests that by consistently reporting both test positive and test negative cases, the usefulness of extractable information from routine surveillance record of infectious diseases would be maximized.
2009 年甲型 H1N1 流感大流行在确定所有病例方面带来了流行病学挑战。尽管实时统计所有流感病例通常是不可行的，但经验观察总是涉及诊断测试程序。这为联合量化传播动力学和诊断准确性提供了机会。我们开发了一种联合估计程序，该程序利用简约模型来描述流行动力学，并将阳性和阴性测试的数量参数化作为时间的函数。我们对模拟数据和 2007-08 年日本间发性甲型 H1N1 流感的经验观察数据的分析表明，与仅依赖阳性测试病例的方法相比，所提出的方法可以更精确地量化传播动力学。对东京成田机场 2009 年 H1N1 大流行入境筛查数据的分析帮助我们量化了流感样疾病在检测乘客实际流感病例方面的特异性非常有限。联合量化不需要我们将诊断准确性条件限定在任何预先定义的研究人群上。我们的研究表明，通过始终报告阳性和阴性测试病例，可以最大限度地利用传染病常规监测记录中可提取的信息。
