Abstract
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%.
Highlights
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
We assessed the performance of 3 acute diarrheal disease (ADD) aberration detection algorithms in this resource-limited setting: X-bar chart, exponentially weighted moving average (EWMA), and Early Aberration Reporting System (EARS) C3 cumulative sums (CUSUM) models [5,6,7,8,9]
87% occurred in persons >5 years of age, 9% in children 1–4 years of age, and 4% in children
Summary
X-bar, EWMA, and C3 CUSUM aberration detection algorithms identified all ADD outbreaks during 2009–2011, and approximately one third to one half of algorithm outbreak signals corresponded to true outbreaks. These findings suggest that these algorithms can usefully inform outbreak asset deployment, in resource-limited settings. CUSUM frequently produced false-positives in the weeks after large outbreaks (e.g., after the 76-case outbreak at Policlínico Naval Ancón) (Table). Nonbloody acute diarrheal disease case count and incidence, 2007–2011, and true outbreak detection data and algorithm performance, 2009–2011, for the 45 naval surveillance sites in Peru, analyzed by using X-bar chart, exponentially weighted moving average, and Early Aberration Reporting System C3 cumulative sums models*
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.