Improved inference of time-varying reproduction numbers during infectious disease outbreaks
Improved inference of time-varying reproduction numbers during infectious disease outbreaks
复制标题
DOI：
10.1016/j.epidem.2019.100356
复制
发表时间：
2019-12-01
期刊：
影响因子：
3.8
通讯作者：
Cori, A.
中科院分区：
文献类型：
--
作者：
Thompson, R. N.;Stockwin, J. E.;Cori, A.
准确估计表征传染病传播的参数对于在流行期间优化控制干预至关重要。评估疫情当前威胁的一个有价值的衡量标准是与时间相关的繁殖数，即每个受感染者引起的继发病例的预期数量。这一数量可以利用流行病期间连续几次观察到的新病例数和连续间隔（传播链中出现症状的病例之间的时间）分布的数据来估计。估计繁殖数量的一些方法依赖于预先存在的序列间隔分布估计，并假设整个疫情是由当地传播驱动的。在这里，我们表明，准确推断当前的传输率，与此估计的不确定性，需要：（i）最新的观察序列的间隔，包括;（ii）本地传输所产生的情况下，从其他地方进口的区别。我们展示了如何病原体的传播性可以推断适当使用数据集从H1N1流感，埃博拉病毒疾病和中东呼吸综合征的爆发。我们提出了一个工具，用于估计在传染病爆发期间的实时繁殖数量准确，这是一个R软件包（EpiEstim 2.2）。它也可以作为一个交互式的，用户友好的在线界面（EpiEstim应用程序），允许非专业人士使用。我们的工具很容易应用于评估传播潜力，从而在未来爆发各种入侵病原体时提供控制信息。
Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) upto-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.