Did Modeling Overestimate the Transmission Potential of Pandemic (H1N1-2009)? Sample Size Estimation for Post-Epidemic Seroepidemiological Studies
Did Modeling Overestimate the Transmission Potential of Pandemic (H1N1-2009)? Sample Size Estimation for Post-Epidemic Seroepidemiological Studies
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DOI：
10.1371/journal.pone.0017908
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发表时间：
2011-03-24
期刊：
影响因子：
3.7
通讯作者：
Castillo-Chavez, Carlos
中科院分区：
文献类型：
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作者：
Nishiura, Hiroshi;Chowell, Gerardo;Castillo-Chavez, Carlos
背景资料：在H1N1-2009流行波之前和之后的血清流行病学研究对于估计人群发病率是有用的，有可能在建模研究中验证生殖数R的早期估计。方法学/主要发现：由于最终的流行规模，在流行病期间感染的人口比例，是不是一个二项抽样过程的结果，因为感染事件不是相互独立的，我们建议使用的渐近分布的最终大小来计算近似95%的置信区间所观察到的最终大小。这使得可以将观察到的最终大小与基于建模研究的预测进行比较（R = 1.15、1.40和1.90），这也产生了用于确定未来血清流行病学研究的样本量的简单公式。我们检查了11个已发表的H1N1-2009血清流行病学研究，这些研究是在观察了一些国家的发病高峰后进行的。在6项研究中观察到的血清阳性比例似乎小于根据R = 1.40预测的比例; 6项研究中有4项在报告的峰值发病率后不到1个月内采集血清。将观察到的最终尺寸与R = 1.15和1.90进行比较表明，所有11项研究似乎都没有显着偏离R = 1.15的预测，但如果使用R = 1.90，则9项研究的最终尺寸表明高估。结论：已发表的血清流行病学研究的样本量太小，无法评估模型预测的有效性，除非使用R = 1.90。我们建议在确定流行后血清流行病学研究的样本量，计算观察到的最终大小的95%置信区间，并进行相关的假设检验，而不是使用依赖于二项比例的方法，使用所提出的方法。
Background: Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies.Methodology/Principal Findings: Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used.Conclusions: Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion.