Department of Infectious Disease Epidemiology, Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, UK.
Biostatistics. 2011 Apr;12(2):303-12. doi: 10.1093/biostatistics/kxq058. Epub 2010 Sep 21.
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.
基本再生数是决定传染病是否持续存在的关键参数。其对应的有效再生数在实时评估干预措施是否已控制疫情方面具有重要价值。在本文中,我们使用理论论证和模拟来理解基于完整连续时间传染病模型的再生数估计与其他 2 种最近开发的估计方法之间的关系。所有这些方法都利用了“传染病曲线”数据,并需要关于分布的生成时间的假设。2 种最简单的估计器不需要通常难以获得的人口规模的信息。最简单的估计器被证明需要进一步的假设,这些假设在实际情况下很少成立,并且与其他估计器相比产生严重偏差的估计值。此外,我们表明,在不完全爆发的早期阶段,通常情况下,生成时间分布和再生数的参数是不可识别的。基于这些结果,我们建议在可能的情况下,基本和有效再生数的估计应基于明确定义的传染病模型;此外,如果有外部信息可用,则应将其纳入贝叶斯分析。