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Volume 13, Number 2—February 2007

Research

Code-based Syndromic Surveillance for Influenzalike Illness by International Classification of Diseases, Ninth Revision

Nicola Marsden-Haug*1, Virginia B. Foster*, Philip L. Gould†, Eugene Elbert*2, Hailiang Wang*, and Julie A. Pavlin*3Comments to Author 
Author affiliations: *Walter Reed Army Institute of Research, Silver Spring, Maryland, USA; †Air Force Institute for Operational Health, Brooks City Base, Texas, USA;

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Figure 3

Newly created groups of International Classification of Diseases, Ninth Revision (ICD-9), codes for influenzalike illness (ILI) based on correlation to positive cultures and signal-to-noise ratios were run with anomaly detection algorithms. Two groups, large and small, were created with ICD-9 codes that had an average use of >50× per day in the large group with the remainder in the small group. Daily counts of the codes in the Large and Small syndromic groups were plotted from October 2000 to

Figure 3. Newly created groups of International Classification of Diseases, Ninth Revision (ICD-9), codes for influenzalike illness (ILI) based on correlation to positive cultures and signal-to-noise ratios were run with anomaly detection algorithms. Two groups, large and small, were created with ICD-9 codes that had an average use of >50× per day in the large group with the remainder in the small group. Daily counts of the codes in the Large and Small syndromic groups were plotted from October 2000 to December 2004. An algorithm based on a mixed time series model that combines regression and exponentially weighted moving average (EWMA) is used to detect potential outbreaks and takes into account weekends and holidays. Yellow alerts occur when the daily value exceeds that expected with a 95% confidence interval, and red alerts occur when the amount exceeds the expected with a 99% confidence interval. A) Large syndrome group. B) Small syndrome group.

Main Article

1Current affiliation: Tacoma–Pierce County Health Department, Tacoma, Washington, USA

2Current affiliation: US Census Bureau, Suitland, Maryland, USA

3Current affiliation: Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA

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