Imperial College London, London, United Kingdom.
University of Cambridge, Cambridge, United Kingdom.
PLoS One. 2021 Feb 19;16(2):e0247002. doi: 10.1371/journal.pone.0247002. eCollection 2021.
2020 saw the continuation of the second largest outbreak of Ebola virus disease (EVD) in history. Determining epidemiological links between cases is a key part of outbreak control. However, due to the large quantity of data and subsequent data entry errors, inconsistencies in potential epidemiological links are difficult to identify. We present chainchecker, an online and offline shiny application which visualises, curates and verifies transmission chain data. The application includes the calculation of exposure windows for individual cases of EVD based on user defined incubation periods and user specified symptom profiles. It has an upload function for viral hemorrhagic fever data and utility for additional entries. This data may then be visualised as a transmission tree with inconsistent links highlighted. Finally, there is utility for cluster analysis and the ability to highlight nosocomial transmission. chainchecker is a R shiny application which has an offline version for use with VHF (viral hemorrhagic fever) databases or linelists. The software is available at https://shiny.dide.imperial.ac.uk/chainchecker which is a web-based application that links to the desktop application available for download and the github repository, https://github.com/imperialebola2018/chainchecker.
2020 年见证了历史上第二大埃博拉病毒病（EVD）疫情的持续。确定病例之间的流行病学联系是疫情控制的关键部分。然而，由于数据量庞大以及随后的数据录入错误，潜在的流行病学联系中的不一致性难以识别。我们提出了 chainchecker，这是一个在线和离线 shiny 应用程序，用于可视化、管理和验证传播链数据。该应用程序包括根据用户定义的潜伏期和用户指定的症状特征计算单个 EVD 病例的暴露窗口。它具有用于上传病毒出血热数据的功能和用于其他条目的实用程序。然后，可以将这些数据可视化为带有突出显示不一致链接的传播树。最后，具有聚类分析的实用程序和突出医院感染传播的能力。chainchecker 是一个 R shiny 应用程序，具有离线版本，可用于病毒出血热（VHF）数据库或行列表。该软件可在 https://shiny.dide.imperial.ac.uk/chainchecker 上获得，这是一个基于网络的应用程序，可链接到可下载的桌面应用程序和 GitHub 存储库，网址为 https://github.com/imperialebola2018/chainchecker。
