Recombinant Temporal Aberration Detection Algorithms for Enhanced Biosurveillance

Recombinant Temporal Aberration Detection Algorithms for Enhanced Biosurveillance

Methods: This study decomposes existing temporal aberration detection algorithms into two sequential stages and investigates the individual impact of each stage on outbreak detection performance. The data forecasting stage (Stage 1) generates predictions of time series values a certain number of time steps in the future based on historical data. The anomaly measure stage (Stage 2) compares feat...

Research Paper: Recombinant Temporal Aberration Detection Algorithms for Enhanced Biosurveillance

OBJECTIVE Broadly, this research aims to improve the outbreak detection performance and, therefore, the cost effectiveness of automated syndromic surveillance systems by building novel, recombinant temporal aberration detection algorithms from components of previously developed detectors. METHODS This study decomposes existing temporal aberration detection algorithms into two sequential stage...

Decoupling Temporal Aberration Detection Algorithms for Enhanced Biosurveillance

Comparison of Aberration Detection Algorithms for Biosurveillance Systems

National syndromic surveillance systems require optimal anomaly detection methods. For method performance comparison, we injected multi-day signals stochastically drawn from lognormal distributions into time series of aggregated daily visit counts from the U.S. Centers for Disease Control and Prevention's BioSense syndromic surveillance system. The time series corresponded to three different sy...

Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

BioSense is a US national system that uses data from health information systems for automated disease surveillance. We studied 4 time-series algorithm modifications designed to improve sensitivity for detecting artificially added data. To test these modified algorithms, we used reports of daily syndrome visits from 308 Department of Defense (DoD) facilities and 340 hospital emergency department...