![]() ![]() They have dependencies on the shiny, shinythemes, plotly, ggplot2, epicontacts, tibble, dplyr, shinycssloaders, lubridate, data.table, magrittr, igraph, DT, network, GGally, sna, intergraph and htmlwidgets packages. The chainchecker applications are implemented as R shiny applications either run on a web server or using R portable. These tools have been actively used in the field as part of ongoing outbreak investigations. The results can then be visualised interactively. The aim is that inconsistencies due to mis-entered data or conflicting information can be highlighted easily and quickly. The focus is on user-defined values which are incorporated to a logic set to verify transmission links. The chainchecker online and desktop applications allow the user to visualise and verify transmission links and chronological data. However, none of the above currently verify transmission links from routinely collected data such as symptom onset date or date of death. ![]() There are number of existing tools to visualise transmission links, particularly epicontacts, an R package to examine transmission links and Go.Data, a tool to collect and visualise contact data. However, due to the large quantity of data and different data sets, as well as subsequent data entry errors, inconsistencies in potential epidemiological links are difficult to identify. Ģ020 saw the continuation of the second largest outbreak of Ebola in history.Ĭontact tracing and determination of epidemiological links are key pillars of EVD outbreak control and are an important aspect of the multi-faceted response. The software is available at which is a web-based application that links to the desktop application available for download and the github repository. chainchecker is a R shiny application which has an offline version for use with VHF (viral hemorrhagic fever) databases or linelists. Finally, there is utility for cluster analysis and the ability to highlight nosocomial transmission. ![]() This data may then be visualised as a transmission tree with inconsistent links highlighted. It has an upload function for viral hemorrhagic fever data and utility for additional entries. The application includes the calculation of exposure windows for individual cases of EVD based on user defined incubation periods and user specified symptom profiles. We present chainchecker, an online and offline shiny application which visualises, curates and verifies transmission chain data. However, due to the large quantity of data and subsequent data entry errors, inconsistencies in potential epidemiological links are difficult to identify. Determining epidemiological links between cases is a key part of outbreak control. 2020 saw the continuation of the second largest outbreak of Ebola virus disease (EVD) in history. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |