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

P. Sansom, V. R. Copley, Falguni Naik, Stephen Leach, Ian Hall*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)3522-3538
    Number of pages17
    JournalStatistics in Medicine
    Volume32
    Issue number20
    DOIs
    Publication statusPublished - 10 Sep 2013

    Bibliographical note

    Copyright:
    Copyright 2013 Elsevier B.V., All rights reserved.

    Keywords

    • Case-association
    • Cluster
    • Detection
    • Legionnaires' disease
    • Visualisation

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