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Recombinant temporal aberration detection algorithms for enhanced biosurveillance.

Sean Patrick Murphy1, Howard Burkom

  • 1The Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723, USA Sean.Murphy@jhuapl.edu

Journal of the American Medical Informatics Association : JAMIA
|October 20, 2007
PubMed
Summary

Novel recombinant algorithms improve outbreak detection in syndromic surveillance systems. By combining components of existing methods, these new approaches enhance performance and cost-effectiveness for public health monitoring.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Computer Science

Background:

  • Automated syndromic surveillance systems are crucial for public health.
  • Existing temporal aberration detection algorithms can be complex and their components' impacts are not fully understood.

Purpose of the Study:

  • To improve outbreak detection performance and cost-effectiveness of automated syndromic surveillance systems.
  • To develop novel, recombinant temporal aberration detection algorithms by combining components of existing detectors.

Main Methods:

  • Decomposition of existing temporal aberration detection algorithms into data forecasting (Stage 1) and anomaly measure (Stage 2) stages.
  • Investigation of individual stage impacts on outbreak detection performance.
  • Use of Monte Carlo simulations to test recombinant algorithms on authentic syndromic time series with injected synthetic aberrations.

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Main Results:

  • Some recombinant methods demonstrated performance improvements over known methods.
  • Improvements were consistent across various data types, outbreak types, and sizes.
  • Specific recombinant algorithms excelled for different outbreak types: WEWD MovAvg7+WEWD Z-Score for gradual outbreaks and HW+WEWD Z-Score for sudden outbreaks.

Conclusions:

  • Decomposition provides valuable insights into aberration detection algorithm effects.
  • Novel combinations of data forecasters and anomaly measures enhance detection performance.
  • Recombinant algorithms offer a promising approach to improve automated syndromic surveillance.