Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

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 synd...

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Bibliographic Details
Main Authors: Jerome I. Tokars, Howard Burkom, Jian Xing, Roseanne English, Steven Bloom, Kenneth Cox, Julie A. Pavlin
Format: Article
Language:English
Published: Centers for Disease Control and Prevention 2009-04-01
Series:Emerging Infectious Diseases
Subjects:
Surveillance
algorithms
statistics
data analysis
outbreak detection
research
Online Access:https://wwwnc.cdc.gov/eid/article/15/4/08-0616_article

Internet

https://wwwnc.cdc.gov/eid/article/15/4/08-0616_article

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