Algorithm Combination for Improved Performance in Biosurveillance

Univariate Monitoring
  • Inbal Yahav
  • Thomas Lotze
  • Galit Shmueli
Part of the Integrated Series in Information Systems book series (ISIS, volume 27)

Chapter Overview

This chapter proposes an enhancement to currently used algorithms for monitoring daily counts of pre-diagnostic data. Rather than use a single algorithm or apply multiple algorithms simultaneously, our approach is based on ensembles of algorithms. The ensembles lead to better performance in terms of higher true alert rates for a given false alert rate. Combinations can be employed at the data preprocessing step and/or at the monitoring step. We discuss the advantages of such an approach and illustrate its usefulness using authentic modern biosurveillance data.


Control charts Monitoring Ensemble methods Optimization Pre-diagnostic data 


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Online Resources

  1. R code for simulating or mimicking multivariate time series of biosurveillance data and outbreak signatures. Also includes semi-authentic data.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Inbal Yahav
    • 1
  • Thomas Lotze
    • 2
  • Galit Shmueli
    • 1
  1. 1.Department of Decision, Operations & Information TechnologiesRobert H Smith School of Business, University of MarylandCollege ParkUSA
  2. 2.Applied Mathematics & Scientific Computation ProgramUniversity of MarylandCollege ParkUSA

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