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
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
10 September 2013
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), .
(doi:10.1002/sim.5765).
(PMID:23483594)
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.
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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: http://eprints.soton.ac.uk/id/eprint/351866
ISSN: 0277-6715
PURE UUID: 393af244-2aae-4187-949e-b9b37d6c3995
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Date deposited: 25 Apr 2013 13:58
Last modified: 14 Mar 2024 13:44
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Contributors
Author:
P. Sansom
Author:
V.R. Copley
Author:
F.C. Naik
Author:
S. Leach
Author:
I.M. Hall
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