An automated distance matrix tool to facilitate investigation in legionnaires' disease clusters
PHE ePoster Library. Shantikumar S. Apr 9, 2019; 257502
Saran Shantikumar
Saran Shantikumar
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Rate & Comment (0)

Abstract Background:
In legionnaires' disease outbreaks, the investigator is often faced with a number of community-acquired cases with no apparent link between them and a multiplicity of potential Legionella aerosol sources that need to be assessed and prioritised for investigation. We have developed a format for the rapid visual assessment of the match between potential sources and case histories and a tool to automate the time-consuming task of populating the output. The ToolThe postcodes of cases' residence, work places and places visited over the 10 days before illness onset are collected as part of enhanced surveillance, and the postcodes of local cooling towers or other putative sources of environmental aerosols collected. The as-the-crow-flies distances between all pairs of postcodes are then calculated using a custom-designed distance matrix tool (developed in R). The resulting distance matrix is visualised using a heat map, with darker colours representing shorter distances, enabling rapid visualisation of commonly visited sites or proximity to potential sources.ApplicationThis distance matrix tool is of value in allowing a rapid visual assessment of the relationship between potential sources and case histories, allowing the identification and prioritisation of sources for investigation. An example will be presented. The tool has been used successfully by our Outbreak Control Teams and as part of their risk assessment in legionnaires' disease clusters, and can be used for other purposes where the creation of a distance matrix is required.In order to improve accessibility, for example to non-R users, the tool has been adapted to be accessed and utilised via a web interface (using RStudio), which can be hosted by PHE's Shiny Server. Funding SS is funded by an NIHR Clinical Lectureship
    This eLearning portal is powered by:
    This eLearning portal is powered by MULTIEPORTAL
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.


Save Settings