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Updated: May 18, 2026

Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model
Published on: April 6, 2021
Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy
Karen Elizabeth Cheng1, David J Crary, Jaideep Ray
1Health Effects and Medical Response Group, Applied Research Associates, Inc, Arlington, VA 22203-1729, USA. kcheng@ara.com
Objective:
We discuss the use of structural models for the analysis of biosurveillance related data.
Methods And Results:
Using a combination of real and simulated data, we have constructed a data set that represents a plausible time series resulting from surveillance of a large scale bioterrorist anthrax attack in Miami. We discuss the performance of anomaly detection with structural models for these data using receiver operating characteristic (ROC) and activity monitoring operating characteristic (AMOC) analysis. In addition, we show that these techniques provide a method for predicting the level of the outbreak valid for approximately 2 weeks, post-alarm.
Conclusions:
Structural models provide an effective tool for the analysis of biosurveillance data, in particular for time series with noisy, non-stationary background and missing data.
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