Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting

Conventional disease surveillance mechanisms that rely on passive reporting may be too slow and insensitive to rapidly detect a large-scale infectious disease outbreak; the reporting time from a patient’s initial symptoms to specific disease diagnosis takes days to weeks. To meet this need, new surv...

Full description

Bibliographic Details
Main Authors:	Benjamin Miller, Heidi Kassenborg, William Dunsmuir, Jayne Griffith, Mansour Hadidi, James D. Nordin, Richard Danila
Format:	Article
Language:	English
Published:	Centers for Disease Control and Prevention 2004-10-01
Series:	Emerging Infectious Diseases
Subjects:	Bioterrorism Surveillance ICD-9 Syndrome Research United States
Online Access:	https://wwwnc.cdc.gov/eid/article/10/10/03-0789_article

id	doaj-26a8a1df73bf443cba4a98e50e9d2f83
record_format	Article
spelling	doaj-26a8a1df73bf443cba4a98e50e9d2f832020-11-25T02:29:17ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592004-10-0110101806181110.3201/eid1010.030789Syndromic Surveillance for Influenzalike Illness in Ambulatory Care SettingBenjamin MillerHeidi KassenborgWilliam DunsmuirJayne GriffithMansour HadidiJames D. NordinRichard DanilaConventional disease surveillance mechanisms that rely on passive reporting may be too slow and insensitive to rapidly detect a large-scale infectious disease outbreak; the reporting time from a patient’s initial symptoms to specific disease diagnosis takes days to weeks. To meet this need, new surveillance methods are being developed. Referred to as nontraditional or syndromic surveillance, these new systems typically rely on prediagnostic data to rapidly detect infectious disease outbreaks, such as those caused by bioterrorism. Using data from a large health maintenance organization, we discuss the development, implementation, and evaluation of a time-series syndromic surveillance detection algorithm for influenzalike illness in Minnesota.https://wwwnc.cdc.gov/eid/article/10/10/03-0789_articleBioterrorismSurveillanceICD-9SyndromeResearchUnited States
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Benjamin Miller Heidi Kassenborg William Dunsmuir Jayne Griffith Mansour Hadidi James D. Nordin Richard Danila
spellingShingle	Benjamin Miller Heidi Kassenborg William Dunsmuir Jayne Griffith Mansour Hadidi James D. Nordin Richard Danila Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting Emerging Infectious Diseases Bioterrorism Surveillance ICD-9 Syndrome Research United States
author_facet	Benjamin Miller Heidi Kassenborg William Dunsmuir Jayne Griffith Mansour Hadidi James D. Nordin Richard Danila
author_sort	Benjamin Miller
title	Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting
title_short	Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting
title_full	Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting
title_fullStr	Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting
title_full_unstemmed	Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting
title_sort	syndromic surveillance for influenzalike illness in ambulatory care setting
publisher	Centers for Disease Control and Prevention
series	Emerging Infectious Diseases
issn	1080-6040 1080-6059
publishDate	2004-10-01
description	Conventional disease surveillance mechanisms that rely on passive reporting may be too slow and insensitive to rapidly detect a large-scale infectious disease outbreak; the reporting time from a patient’s initial symptoms to specific disease diagnosis takes days to weeks. To meet this need, new surveillance methods are being developed. Referred to as nontraditional or syndromic surveillance, these new systems typically rely on prediagnostic data to rapidly detect infectious disease outbreaks, such as those caused by bioterrorism. Using data from a large health maintenance organization, we discuss the development, implementation, and evaluation of a time-series syndromic surveillance detection algorithm for influenzalike illness in Minnesota.
topic	Bioterrorism Surveillance ICD-9 Syndrome Research United States
url	https://wwwnc.cdc.gov/eid/article/10/10/03-0789_article
work_keys_str_mv	AT benjaminmiller syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting AT heidikassenborg syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting AT williamdunsmuir syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting AT jaynegriffith syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting AT mansourhadidi syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting AT jamesdnordin syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting AT richarddanila syndromicsurveillanceforinfluenzalikeillnessinambulatorycaresetting
_version_	1724833985422426112

Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting

Similar Items