Syndromic surveillance using veterinary laboratory data: algorithm combination and customization of alerts

Fernanda C. Dórea, Beverly J. McEwen, W. Bruce McNab, Javier Sanchez, Crawford W. Revie

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Background: Syndromic surveillance research has focused on two main themes: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals. Methods: This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of laboratory submissions counts. These are: the Shewhart control charts designed to detect sudden spikes in counts; the EWMA control charts developed to detect slow increasing outbreaks; and the Holt-Winters exponential smoothing, which can explicitly account for temporal effects in the data stream monitored. A scoring system to detect and report alarms using these algorithms in a complementary way is proposed. Results: The use of multiple algorithms in parallel resulted in increased system sensitivity. Specificity was decreased in simulated data, but the number of false alarms per year when the approach was applied to real data was considered manageable (between 1 and 3 per year for each of ten syndromic groups monitored). The automated implementation of this approach, including a method for on-line filtering of potential outbreak signals is described. Conclusion: The developed system provides high sensitivity for detection of potential outbreak signals while also providing robustness and flexibility in establishing what signals constitute an alarm. This flexibility allows an analyst to customize the system for different syndromes.

LanguageEnglish
Article numbere82183
Number of pages10
JournalPLoS ONE
Volume8
Issue number12
DOIs
Publication statusPublished - 11 Dec 2013

Fingerprint

Customization
Surveillance
Disease Outbreaks
monitoring
Count
disease detection
Flexibility
Shewhart Control Chart
EWMA Chart
Exponential Smoothing
Information Storage and Retrieval
Control Charts
False Alarm
Time series
time series analysis
Data Streams
Spike
Scoring
Specificity
Early Diagnosis

Keywords

  • syndromic surveillance
  • disease detection
  • infection outbreak simulations

Cite this

Dórea, Fernanda C. ; McEwen, Beverly J. ; McNab, W. Bruce ; Sanchez, Javier ; Revie, Crawford W. / Syndromic surveillance using veterinary laboratory data : algorithm combination and customization of alerts. In: PLoS ONE. 2013 ; Vol. 8, No. 12.
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Syndromic surveillance using veterinary laboratory data : algorithm combination and customization of alerts. / Dórea, Fernanda C.; McEwen, Beverly J.; McNab, W. Bruce; Sanchez, Javier; Revie, Crawford W.

In: PLoS ONE, Vol. 8, No. 12, e82183, 11.12.2013.

Research output: Contribution to journalArticle

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