The University of Southampton
University of Southampton Institutional Repository

A case-association cluster detection and visualisation tool with an application to Legionnaires' disease

A case-association cluster detection and visualisation tool with an application to Legionnaires' disease
A case-association cluster detection and visualisation tool with an application to Legionnaires' disease
Statistical methods used in spatio-temporal surveillance of disease are able to identify abnormal clusters of cases but typically do not provide a measure of the degree of association between one case and another. Such a measure would facilitate the assignment of cases to common groups and be useful in outbreak investigations of diseases that potentially share the same source. This paper presents a model-based approach, which on the basis of available location data, provides a measure of the strength of association between cases in space and time and which is used to designate and visualise the most likely groupings of cases. The method was developed as a prospective surveillance tool to signal potential outbreaks, but it may also be used to explore groupings of cases in outbreak investigations. We demonstrate the method by using a historical case series of Legionnaires' disease amongst residents of England and Wales.
legionnaires’ disease, cluster, case-association, detection, visualisation
0277-6715
3522-3538
Sansom, P.
70b165b8-330f-4940-a5e0-baa00c05d617
Copley, V.R.
1f1d38c3-7a9c-4358-8bc2-e2c1374b4a51
Naik, F.C.
00241f0b-7506-45be-aa95-9ddea3de1a36
Leach, S.
6bd55fb6-3cdd-4b1b-914b-06f8270b687c
Hall, I.M.
442e6a3c-4fdd-4964-aaf2-70b8e52cdd70
Sansom, P.
70b165b8-330f-4940-a5e0-baa00c05d617
Copley, V.R.
1f1d38c3-7a9c-4358-8bc2-e2c1374b4a51
Naik, F.C.
00241f0b-7506-45be-aa95-9ddea3de1a36
Leach, S.
6bd55fb6-3cdd-4b1b-914b-06f8270b687c
Hall, I.M.
442e6a3c-4fdd-4964-aaf2-70b8e52cdd70

Sansom, P., Copley, V.R., Naik, F.C., Leach, S. and Hall, I.M. (2013) A case-association cluster detection and visualisation tool with an application to Legionnaires' disease. Statistics in Medicine, 32 (20), 3522-3538. (doi:10.1002/sim.5765). (PMID:23483594)

Record type: Article

Abstract

Statistical methods used in spatio-temporal surveillance of disease are able to identify abnormal clusters of cases but typically do not provide a measure of the degree of association between one case and another. Such a measure would facilitate the assignment of cases to common groups and be useful in outbreak investigations of diseases that potentially share the same source. This paper presents a model-based approach, which on the basis of available location data, provides a measure of the strength of association between cases in space and time and which is used to designate and visualise the most likely groupings of cases. The method was developed as a prospective surveillance tool to signal potential outbreaks, but it may also be used to explore groupings of cases in outbreak investigations. We demonstrate the method by using a historical case series of Legionnaires' disease amongst residents of England and Wales.

Full text not available from this repository.

More information

e-pub ahead of print date: 11 March 2013
Published date: 10 September 2013
Keywords: legionnaires’ disease, cluster, case-association, detection, visualisation
Organisations: Primary Care & Population Sciences

Identifiers

Local EPrints ID: 351866
URI: https://eprints.soton.ac.uk/id/eprint/351866
ISSN: 0277-6715
PURE UUID: 393af244-2aae-4187-949e-b9b37d6c3995

Catalogue record

Date deposited: 25 Apr 2013 13:58
Last modified: 16 Jul 2019 21:35

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×