MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
BMC Bioinformatics. 2018 Oct 22;19(Suppl 11):363. doi: 10.1186/s12859-018-2330-z.
Reconstructing individual transmission events in an infectious disease outbreak can provide valuable information and help inform infection control policy. Recent years have seen considerable progress in the development of methodologies for reconstructing transmission chains using both epidemiological and genetic data. However, only a few of these methods have been implemented in software packages, and with little consideration for customisability and interoperability. Users are therefore limited to a small number of alternatives, incompatible tools with fixed functionality, or forced to develop their own algorithms at considerable personal effort.
Here we present outbreaker2, a flexible framework for outbreak reconstruction. This R package re-implements and extends the original model introduced with outbreaker, but most importantly also provides a modular platform allowing users to specify custom models within an optimised inferential framework. As a proof of concept, we implement the within-host evolutionary model introduced with TransPhylo, which is very distinct from the original genetic model in outbreaker, and demonstrate how even complex model results can be successfully included with minimal effort.
outbreaker2 provides a valuable starting point for future outbreak reconstruction tools, and represents a unifying platform that promotes customisability and interoperability. Implemented in the R software, outbreaker2 joins a growing body of tools for outbreak analysis.
在传染病暴发中重建个体传播事件可以提供有价值的信息，并有助于制定感染控制政策。近年来，利用流行病学和遗传数据重建传播链的方法取得了相当大的进展。然而，这些方法中只有少数几个已经在软件包中实现，并且很少考虑可定制性和互操作性。因此，用户只能选择少数几种替代方法，或者使用功能固定的不兼容工具，或者被迫付出相当大的个人努力来开发自己的算法。
我们在这里提出了 outbreaker2，这是一个用于暴发重建的灵活框架。这个 R 包重新实现和扩展了最初在 outbreaker 中引入的模型，但最重要的是，它还提供了一个模块化平台，允许用户在优化的推理框架内指定自定义模型。作为一个概念验证，我们实现了 TransPhylo 中引入的宿主内进化模型，它与 outbreaker 中的原始遗传模型非常不同，并展示了即使是复杂的模型结果也可以通过最小的努力成功地包含在内。
outbreaker2 为未来的暴发重建工具提供了一个有价值的起点，代表了一个促进可定制性和互操作性的统一平台。outbreaker2 以 R 软件实现，加入了越来越多的暴发分析工具。
