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Comparison of Aberration Detection Algorithms for Biosurveillance Systems


Use of robust and broadly applicable statistical alerting methods is essential for a public health Biosurveillance system. We compared several algorithms related to the Early Aberration Reporting System C2 (adaptive control chart) method for practical detection sensitivity and timeliness using a realistic but stochastic signal inject strategy with a variety of data streams. The comparison allowed detail examination of strategies for adjusting daily syndromic counts for day-of-week effects and the total daily volume of facility visits. Adjustment for the total visit volume allows monitoring of surrogate rates instead of just counts, and the use of real data with both syndromic and total visit counts enables this adjustment.


We compared several aberration detection algorithms using a set of syndromic data streams from a large number of treatment facilities in the CDC Biosense 1.0 system. A realistic signal injection strategy was devised to compare different ways of adjusting for total facility visits and background day-of-week effects.

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