Symbolic transfer entropy reveals the age structure of pandemic influenza transmission from high-volume influenza-like illness data
Symbolic transfer entropy reveals the age structure of pandemic influenza transmission from high-volume influenza-like illness data
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DOI：
10.1098/rsif.2019.0628
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发表时间：
2020-03-25
影响因子：
3.9
通讯作者：
Gog, Julia R.
中科院分区：
文献类型：
--
作者：
Kissler, Stephen M.;Viboud, Cecile;Gog, Julia R.
推断年龄组在流行病传播中的相对作用的现有方法通常只能适用于少数年龄组，和/或需要对所研究的疾病具有高度特异性的数据。这里，符号传递熵（STE）是一种用于识别随机过程之间信息不对称传递的度量，它被提出作为揭示流行病中年龄组之间不对称传播模式的一种方法。STE提供了一个可能主导传播的年龄组的排名，而不是重建明确的年龄组间传播矩阵。通过模拟，我们确定STE可以识别出哪个年龄组在传播中占主导地位，即使年龄组之间的报告率存在差异，即使数据嘈杂。然后，对2009年秋季美国884个城市12个年龄组流感样疾病的时间序列进行两两STE计算。从5岁到19岁的STE升高表明，在2009年美国秋季流感大流行期间，学龄儿童可能是最重要的感染传播者。与成人相比，儿童寻求医生的比例更高，这一结果可能会部分混淆，但报告率的差异不太可能解释STE观察到的差异。
Existing methods to infer the relative roles of age groups in epidemic transmission can normally only accommodate a few age classes, and/or require data that are highly specific for the disease being studied. Here, symbolic transfer entropy (STE), a measure developed to identify asymmetric transfer of information between stochastic processes, is presented as a way to reveal asymmetric transmission patterns between age groups in an epidemic. STE provides a ranking of which age groups may dominate transmission, rather than a reconstruction of the explicit between-age-group transmission matrix. Using simulations, we establish that STE can identify which age groups dominate transmission even when there are differences in reporting rates between age groups and even if the data are noisy. Then, the pairwise STE is calculated between time series of influenza-like illness for 12 age groups in 884 US cities during the autumn of 2009. Elevated STE from 5 to 19 year-olds indicates that school-aged children were likely the most important transmitters of infection during the autumn wave of the 2009 pandemic in the USA. The results may be partially confounded by higher rates of physician-seeking behaviour in children compared to adults, but it is unlikely that differences in reporting rates can explain the observed differences in STE.