Joint estimation of the basic reproduction number and generation time parameters for infectious disease outbreaks
Joint estimation of the basic reproduction number and generation time parameters for infectious disease outbreaks
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DOI：
10.1093/biostatistics/kxq058
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发表时间：
2011-04-01
期刊：
影响因子：
2.1
通讯作者：
Clarke, Paul S.
中科院分区：
文献类型：
--
作者：
Griffin, Jamie T.;Garske, Tini;Clarke, Paul S.
基本繁殖数是决定传染病是否持续存在的关键参数。随着时间的推移，其对应的有效繁殖数在实时评估干预措施是否已使疫情得到控制方面具有价值。在本文中，我们用理论论证和模拟来理解基于全连续时间流行病模型的再现数估计与最近发展的另外两种估计之间的关系。所有这些方法都使用了“流行曲线”数据，并要求对产生时间分布进行假设。两个最简单的估计不需要关于通常难以获得的种群规模的信息。最简单的估计需要进一步的假设，而这些假设在实际环境中很少有效，并且与其他估计相比会产生严重的偏差。此外，我们还表明，在不完全爆发的早期阶段，一般来说，世代时间分布和繁殖数的参数是不确定的。根据这些结果，我们建议，在可能的情况下，应根据一个定义良好的流行病模型来估计基本和有效的繁殖数；此外，如果外部信息是可用的，那么它应该被纳入贝叶斯分析。
The basic reproduction number is a key parameter determining whether an infectious disease will persist. Its counterpart over time, the effective reproduction number, is of value in assessing in real time whether interventions have brought an outbreak under control. In this paper, we use theoretical arguments and simulation to understand the relationship between estimation of the reproduction number based on a full continuous time epidemic model and 2 other recently developed estimators. All these methods make use of "epidemic curve" data and require assumptions about the generation time distribution. The 2 simplest estimators do not require information about the-often difficult to obtain-population size. The simplest estimator is shown to require further assumptions that are rarely valid in practical settings and to produce severely biased estimates compared to the others. Furthermore, we show that in general the parameters of the generation time distribution and the reproduction number are non-identified in the early stages of an incomplete outbreak. On the basis of these results, we recommend that, wherever possible, estimation of the basic and effective reproduction numbers should be based on a well-defined epidemic model; moreover, if external information is available then it should be incorporated in a Bayesian analysis.