A System for Simulation: Introducing Outbreaks into Time Series Data



Several authors have described ways to introduce artificial outbreaks into time series for the purpose of developing, testing, and evaluating the effectiveness and timeliness of anomaly detection algorithms, and more generally, early event detection systems. While the statistical anomaly detection methods take into account baseline characteristics of the time series, these simulated outbreaks are introduced on an ad hoc basis and do not take into account those baseline characteristics. Our objective was to develop statistical-based procedures to introduce artificial anomalies into time series, which thus would have wide applicability for evaluation of anomaly detection algorithms against widely different data streams.

Original Publication Year: 
Event/Publication Date: 
October, 2006

July 30, 2018

Contact Us

NSSP Community of Practice

Email: syndromic@cste.org


This website is supported by Cooperative Agreement # 6NU38OT000297-02-01 Strengthening Public Health Systems and Services through National Partnerships to Improve and Protect the Nation's Health between the Centers for Disease Control and Prevention (CDC) and the Council of State and Territorial Epidemiologists. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC. CDC is not responsible for Section 508 compliance (accessibility) on private websites.

Site created by Fusani Applications