+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

A simulation study comparing aberration detection algorithms for syndromic surveillance

A simulation study comparing aberration detection algorithms for syndromic surveillance

Bmc Medical Informatics and Decision Making 7: 6

The usefulness of syndromic surveillance for early outbreak detection depends in part on effective statistical aberration detection. However, few published studies have compared different detection algorithms on identical data. In the largest simulation study conducted to date, we compared the performance of six aberration detection algorithms on simulated outbreaks superimposed on authentic syndromic surveillance data. We compared three control-chart-based statistics, two exponential weighted moving averages, and a generalized linear model. We simulated 310 unique outbreak signals, and added these to actual daily counts of four syndromes monitored by Public Health--Seattle and King County's syndromic surveillance system. We compared the sensitivity of the six algorithms at detecting these simulated outbreaks at a fixed alert rate of 0.01. Stratified by baseline or by outbreak distribution, duration, or size, the generalized linear model was more sensitive than the other algorithms and detected 54% (95% CI = 52%-56%) of the simulated epidemics when run at an alert rate of 0.01. However, all of the algorithms had poor sensitivity, particularly for outbreaks that did not begin with a surge of cases. When tested on county-level data aggregated across age groups, these algorithms often did not perform well in detecting signals other than large, rapid increases in case counts relative to baseline levels.

Please choose payment method:

(PDF emailed within 0-6 h: $19.90)

Accession: 048119318

Download citation: RISBibTeXText

PMID: 17331250

DOI: 10.1186/1472-6947-7-6

Related references

Comparison of statistical algorithms for daily syndromic surveillance aberration detection. Bioinformatics 35(17): 3110-3118, 2019

Pilot simulation study using meat inspection data for syndromic surveillance: use of whole carcass condemnation of adult cattle to assess the performance of several algorithms for outbreak detection. Epidemiology and Infection 143(12): 2559-2569, 2015

A systematic review of aberration detection algorithms used in public health surveillance. Journal of Biomedical Informatics 94: 103181, 2019

Comparing syndromic surveillance detection methods: EARS' versus a CUSUM-based methodology. Statistics in Medicine 27(17): 3407-3429, 2008

An Observational Study Using English Syndromic Surveillance Data Collected During the 2012 London Olympics - What did Syndromic Surveillance Show and What Can We Learn for Future Mass-gathering Events?. Prehospital and Disaster Medicine 31(6): 628-634, 2016

A simulation model for assessing aberration detection methods used in public health surveillance for systems with limited baselines. Statistics in Medicine 24(4): 543-550, 2005

Evaluation of a continuous indicator for syndromic surveillance through simulation. application to vector borne disease emergence detection in cattle using milk yield. Plos one 8(9): E73726, 2013

Multifaceted syndromic surveillance in a public health department using the early aberration reporting system. Journal of Public Health Management and Practice 11(4): 274-281, 2005

A simulation study on the statistical monitoring of condemnation rates from slaughterhouses for syndromic surveillance: an evaluation based on Swiss data. Epidemiology and Infection 143(16): 3423-3433, 2015

Evaluation of outbreak detection performance using multi-stream syndromic surveillance for influenza-like illness in rural Hubei Province, China: a temporal simulation model based on healthcare-seeking behaviors. Plos one 9(11): E112255, 2014

Syndromic surveillance using minimum transfer of identifiable data: the example of the National Bioterrorism Syndromic Surveillance Demonstration Program. Journal of Urban Health 80(2 Suppl 1): I25-I31, 2003

Epidemic simulation for syndromic surveillance. Health Care Manager 26(4): 297-302, 2007

Evaluating the utility of syndromic surveillance algorithms for screening to detect potentially clonal hospital infection outbreaks. Journal of the American Medical Informatics Association 18(4): 466-472, 2011

Evaluation of a syndromic surveillance system using the WSARE algorithm for early detection of an unusual, localized summer outbreak of influenza B: implications for bioterrorism surveillance. Israel Medical Association Journal 9(1): 3-7, 2007

Evaluation of syndromic surveillance systems--design of an epidemic simulation model. Mmwr Supplements 53: 137-143, 2004