Evaluation of Temporal Aberration Detection Methods in New York City Syndromic Data

Authors

  • Robert Mathes New York City Department of Health and Mental Hygiene, Queens, NY, United States
  • Ramona Lall New York City Department of Health and Mental Hygiene, Queens, NY, United States
  • Jessica Sell New York City Department of Health and Mental Hygiene, Queens, NY, United States

DOI:

https://doi.org/10.5210/ojphi.v6i1.5101

Abstract

The New York City (NYC) syndromic surveillance system has been monitoring syndromes from city emergency department (ED) visits for over a decade. We applied four aberration detection methodologies to a time series of ED visits in NYC spiked with synthetic outbreaks. Among the methods tested, performance varied by outbreak type and size; sudden large one-day spikes in cases were the most commonly detected, although sensitivity was low.  The methods tested did not perform well; variability in method performance by outbreak type suggests multiple methods may be ideal for detecting different outbreak features.

Author Biography

Robert Mathes, New York City Department of Health and Mental Hygiene, Queens, NY, United States

Robert Mathes is the Director of the Syndromic Surveillance Unit in the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene.

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Published

2014-03-09

How to Cite

Mathes, R., Lall, R., & Sell, J. (2014). Evaluation of Temporal Aberration Detection Methods in New York City Syndromic Data. Online Journal of Public Health Informatics, 6(1). https://doi.org/10.5210/ojphi.v6i1.5101

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Section

Lightning Talks