Multiple Estimates of Transmissibility for the 2009 Influenza Pandemic Based on Influenza-like-Illness Data from Small US Military Populations
Multiple Estimates of Transmissibility for the 2009 Influenza Pandemic Based on Influenza-like-Illness Data from Small US Military Populations
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DOI：
10.1371/journal.pcbi.1003064
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发表时间：
2013-05-01
影响因子：
4.3
通讯作者：
Riley, Steven
中科院分区：
文献类型：
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作者：
Riley, Pete;Ben-Nun, Michal;Riley, Steven
快速表征新型人类流感毒株出现时的传播能力的幅度和变异性是一项重要的公共卫生优先事项。然而，由于数据来源和方法不一致，对 2009 年大流行期间基本再生数的早期估计进行比较具有挑战性。在这里，我们定义并分析了 2009 年至 2010 年 50 个最大的空间上不同的美国军事设施（按邮政编码 MPZ 定义的军事人口）的流感样疾病 (ILI) 病例数据。我们使用非军事来源的公开数据表明，许多此类军事禁区的流感样病例发病模式与其周围平民人口的模式密切相关。在描述了广泛的发病模式（例如单峰、双峰）后，我们定义了一个类似 SIR 的简约模型，其中具有跨三个时期的内在传播率的两个可能值。我们将该模型的参数与来自所有 50 个 MPZ 的数据进行拟合，发现它们的聚类效果相当好，中值（平均）值为 1.39 (1.57)，标准差为 0.41。在我们的研究期间，传播率的增加时间趋势（dR(0)/dt 类似于 0.017week(-1)，p 值：0.013）对于去除高传播率异常值和去除较小的 20 个 MPZ 来说是稳健的。我们的结果证明了来自多个人群的快速可用且一致的数据的效用。
Rapidly characterizing the amplitude and variability in transmissibility of novel human influenza strains as they emerge is a key public health priority. However, comparison of early estimates of the basic reproduction number during the 2009 pandemic were challenging because of inconsistent data sources and methods. Here, we define and analyze influenza-like-illness (ILI) case data from 2009-2010 for the 50 largest spatially distinct US military installations (military population defined by zip code, MPZ). We used publicly available data from non-military sources to show that patterns of ILI incidence in many of these MPZs closely followed the pattern of their enclosing civilian population. After characterizing the broad patterns of incidence (e. g. single-peak, double-peak), we defined a parsimonious SIR-like model with two possible values for intrinsic transmissibility across three epochs. We fitted the parameters of this model to data from all 50 MPZs, finding them to be reasonably well clustered with a median (mean) value of 1.39 (1.57) and standard deviation of 0.41. An increasing temporal trend in transmissibility (dR(0)/dt similar to 0.017week(-1), p-value: 0.013) during the period of our study was robust to the removal of high transmissibility outliers and to the removal of the smaller 20 MPZs. Our results demonstrate the utility of rapidly available - and consistent-data from multiple populations.