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Statistical Challenges Facing Early Outbreak Detection in Biosurveillance

Summary: [This abstract is based on the authors' abstract.] Biosurveillance, the practice of monitoring data to detect and respond to disease outbreaks, has borrowed some of the tools used in classical disease surveillance, but the new types of data, processes, and applications encountered vary from the setting for which these tools were originally intended. Other challenges include multiple dimensions, performance evaluation, and system usage and requirements. The focus of this study is on monitoring of time series to provide early alerts of anomalies indicating potential outbreaks. A brief summary is given of methods used to detect spatial and spatiotemporal case clusters. In addition, recent biosurveillance literature is surveyed.

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  • Topics: Statistics
  • Keywords: Biotechnology, Health care, Monitoring, Event detection, Preventative action, Statistical process control (SPC), Data analysis, Time series
  • Author: Shmueli, Galit; Burkom, Howard
  • Journal: Technometrics