Directionally Sensitive Multivariate Statistical Process Control Methods with Application to Syndromic Surveillance

dc.contributor.authorFricker, Ronald D. Jr.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2016-12-28T01:19:53Zen
dc.date.available2016-12-28T01:19:53Zen
dc.date.issued2007en
dc.description.abstractCurrent syndromic surveillance systems run multiple simultaneous univariate procedures, each focused on detecting an outbreak in a single data stream. Multivariate procedures have the potential to better detect some types of outbreaks, but most of the existing methods are directionally invariant and are thus less relevant to the problem of syndromic surveillance. This article develops two directionally sensitive multivariate procedures and compares the performance of these procedures both with the original directionally invariant procedures and with the application of multiple univariate procedures using both simulated and real syndromic surveillance data. The performance comparison is conducted using metrics and terminology from the statistical process control (SPC) literature with the intention of helping to bridge the SPC and syndromic surveillance literatures. This article also introduces a new metric, the average overlapping run length (AORL), developed to compare the performance of various procedures on limited actual syndromic surveillance data. Among the procedures compared, in the simulations the directionally sensitive multivariate cumulative sum (MCUSUM) procedure was preferred, whereas in the real data the multiple univariate CUSUMs and the MCUSUM performed similarly. This article concludes with a brief discussion of the choice of performance metrics used herein versus the metrics more commonly used in the syndromic surveillance literature (sensitivity, specificity, and timeliness), as well as some recommendations for future research.en
dc.description.notesBecause the authors were US Government employees at the time of publication, the publisher does not hold the copyright.en
dc.description.versionPublished versionen
dc.identifier.issue1en
dc.identifier.urihttp://hdl.handle.net/10919/73852en
dc.identifier.volume3en
dc.language.isoenen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleDirectionally Sensitive Multivariate Statistical Process Control Methods with Application to Syndromic Surveillanceen
dc.title.serialAdvances in Disease Surveillanceen
dc.typeArticle - Refereeden
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/Statisticsen

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