Evaluation of Temporal Aberration Detection Methods in New York City Syndromic Data
Author(s) -
Robert Mathes,
Ramona Lall,
Jessica Sell
Publication year - 2014
Publication title -
online journal of public health informatics
Language(s) - English
Resource type - Journals
ISSN - 1947-2579
DOI - 10.5210/ojphi.v6i1.5101
Subject(s) - outbreak , emergency department , medicine , computer science , medical emergency , data mining , cartography , geography , virology , psychiatry
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.
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