Evaluation of Alerting Sparse-Data Streams of Population Healthcare-Seeking Data

Objective This presentation discusses the problem of detecting small-scale events in biosurveillance data that are relatively sparse in the sense that the median count of monitored time series values is zero. Research goals are to understand conditions when methods adapted for sparseness are warranted, to examine adaptations of control charts and other algorithms under these scenarios, and to compare the detection performance of these algorithms.