Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting

We evaluated the performance of X-bar chart, exponentially weighted moving average, and C3 cumulative sums aberration detection algorithms for acute diarrheal disease syndromic surveillance at naval sites in Peru during 2007–2011. The 3 algorithms’ detection sensitivity was 100%, specificity was 97%...

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Main Authors: Emily Alsentzer, Sarah-Blythe Ballard, Joan Neyra, Delphis M. Vera, Victor B. Osorio, Jose Quispe, David L. Blazes, Luis Loayza
Format: Article
Language:English
Published: Centers for Disease Control and Prevention 2020-09-01
Series:Emerging Infectious Diseases
Subjects:
Online Access:https://wwwnc.cdc.gov/eid/article/26/9/19-1315_article
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author Emily Alsentzer
Sarah-Blythe Ballard
Joan Neyra
Delphis M. Vera
Victor B. Osorio
Jose Quispe
David L. Blazes
Luis Loayza
author_facet Emily Alsentzer
Sarah-Blythe Ballard
Joan Neyra
Delphis M. Vera
Victor B. Osorio
Jose Quispe
David L. Blazes
Luis Loayza
author_sort Emily Alsentzer
collection DOAJ
description We evaluated the performance of X-bar chart, exponentially weighted moving average, and C3 cumulative sums aberration detection algorithms for acute diarrheal disease syndromic surveillance at naval sites in Peru during 2007–2011. The 3 algorithms’ detection sensitivity was 100%, specificity was 97%–99%, and positive predictive value was 27%–46%.
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1080-6059
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spelling doaj.art-a63bafe512254ea083727f89cc4e572a2022-12-21T23:42:04ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592020-09-012692196220010.3201/eid2609.191315Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited SettingEmily AlsentzerSarah-Blythe BallardJoan NeyraDelphis M. VeraVictor B. OsorioJose QuispeDavid L. BlazesLuis LoayzaWe evaluated the performance of X-bar chart, exponentially weighted moving average, and C3 cumulative sums aberration detection algorithms for acute diarrheal disease syndromic surveillance at naval sites in Peru during 2007–2011. The 3 algorithms’ detection sensitivity was 100%, specificity was 97%–99%, and positive predictive value was 27%–46%.https://wwwnc.cdc.gov/eid/article/26/9/19-1315_articleoutbreak detection algorithmssyndromic surveillanceacute diarrheal diseaseresource-limited settingenteric infections
spellingShingle Emily Alsentzer
Sarah-Blythe Ballard
Joan Neyra
Delphis M. Vera
Victor B. Osorio
Jose Quispe
David L. Blazes
Luis Loayza
Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting
Emerging Infectious Diseases
outbreak detection algorithms
syndromic surveillance
acute diarrheal disease
resource-limited setting
enteric infections
title Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting
title_full Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting
title_fullStr Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting
title_full_unstemmed Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting
title_short Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting
title_sort assessing 3 outbreak detection algorithms in an electronic syndromic surveillance system in a resource limited setting
topic outbreak detection algorithms
syndromic surveillance
acute diarrheal disease
resource-limited setting
enteric infections
url https://wwwnc.cdc.gov/eid/article/26/9/19-1315_article
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