Reducing false alarms in syndromic surveillance
Article first published online: 22 MAR 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 14, pages 1665–1677, 30 June 2011
How to Cite
Peter, W., Najmi, A. H. and Burkom, H. S. (2011), Reducing false alarms in syndromic surveillance. Statist. Med., 30: 1665–1677. doi: 10.1002/sim.4204
- Issue published online: 2 JUN 2011
- Article first published online: 22 MAR 2011
- Manuscript Accepted: 9 DEC 2010
- Manuscript Received: 14 OCT 2008
- syndromic counts;
- information theory;
- public health
Algorithms for identifying public health threats or disease outbreaks are vulnerable to false alarms arising from sudden shifts in health-care utilization or data participation. This paper describes a method of reducing false alerts in automated public health surveillance algorithms, and in particular, automated syndromic surveillance algorithms, that rely on health-care utilization data. The technique is based on monitoring syndromic counts with reference to a suitable background, or reference, series of counts. The suitability of the background time series in decreasing the false-alarm rate will be shown to be related mathematically to the so-called mutual information that exists between the random variables representing the syndromic and background time series of counts. The method can be understood as a noise cancellation filter technique in which one noisy (reference) channel is used to cancel the background noise of the monitored (measured) channel. The issues discussed here may also be relevant to the appropriate use of rates in epidemiology and biostatistics. Copyright © 2011 John Wiley & Sons, Ltd.