Role of data aggregation in biosurveillance detection strategies with applications from ESSENCE.

Howard S. Burkom, Y. Elbert, A. Feldman, J. Lin

Research output: Contribution to journalArticle

Abstract

INTRODUCTION: Syndromic surveillance systems are used to monitor daily electronic data streams for anomalous counts of features of varying specificity. The monitored quantities might be counts of clinical diagnoses, sales of over-the-counter influenza remedies, school absenteeism among a given age group, and so forth. Basic data-aggregation decisions for these systems include determining which records to count and how to group them in space and time. OBJECTIVES: This paper discusses the application of spatial and temporal data-aggregation strategies for multiple data streams to alerting algorithms appropriate to the surveillance region and public health threat of interest. Such a strategy was applied and evaluated for a complex, authentic, multisource, multiregion environment, including >2 years of data records from a system-evaluation exercise for the Defense Advanced Research Project Agency (DARPA). METHODS: Multivariate and multiple univariate statistical process control methods were adapted and applied to the DARPA data collection. Comparative parametric analyses based on temporal aggregation were used to optimize the performance of these algorithms for timely detection of a set of outbreaks identified in the data by a team of epidemiologists. RESULTS: The sensitivity and timeliness of the most promising detection methods were tested at empirically calculated thresholds corresponding to multiple practical false-alert rates. Even at the strictest false-alert rate, all but one of the outbreaks were detected by the best method, and the best methods achieved a 1-day median time before alert over the set of test outbreaks. CONCLUSIONS: These results indicate that a biosurveillance system can provide a substantial alerting-timeliness advantage over traditional public health monitoring for certain outbreaks. Comparative analyses of individual algorithm results indicate further achievable improvement in sensitivity and specificity.

Original languageEnglish (US)
Pages (from-to)67-73
Number of pages7
JournalMMWR. Morbidity and mortality weekly report
Volume53 Suppl
StatePublished - Sep 24 2004

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ASJC Scopus subject areas

  • Epidemiology
  • Health(social science)
  • Health, Toxicology and Mutagenesis
  • Health Information Management

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