Category-Specific Comparison of Univariate Alerting Methods for Biosurveillance Decision Support
DOI:
https://doi.org/10.5210/ojphi.v5i1.4411Abstract
We compared detection performance of univariate alerting methods on real and simulated events in different types of biosurveillance data. Both kinds of detection performance analysis showed the method based on Holt-Winters exponential smoothing superior on non-sparse time series with day-of-week effects. The adaptive CUSUM and Shewhart methods proved optimal on sparse data and data without weekly patterns.Published
2013-03-23
How to Cite
Elbert, Y., Hung, V., & Burkom, H. (2013). Category-Specific Comparison of Univariate Alerting Methods for Biosurveillance Decision Support. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4411
Issue
Section
Oral Presentations: Temporal or Spatio-temporal