DIMACS Tutorial on Statistical and Other Analytic Health Surveillance Methods

Dates of Tutorial: June 17 - 20, 2003
DIMACS Center, CoRE Building, Rutgers University

David Madigan, Rutgers University, madigan@stat.rutgers.edu
Henry Rolka, CDC, hrr2@cdc.gov
Martin Kulldorff, University of Connecticut, martink@neuron.uchc.edu
Presented under the auspices of the Special Focus on Computational and Mathematical Epidemiology.

Surveillance is a core activity for public health practice. Standard tasks include outbreak detection, post-marketing drug adverse event surveillance, immunization program evaluation and institutional comparisons. Recent concerns about bioterrorism have attracted increased attention to new analytic surveillance methods applied to non-traditional data sources such as over-the-counter drug sales, ambulance dispatches and pre-diagnostic patient encounter summaries. Both the novel methods and new data sources raise significant statistical and computing challenges. The need for innovative statistical methods for surveillance of multiple data streams and the evaluation of utility for new methodologies are especially pressing issues.

This DIMACS tutorial will provide an overview of the challenges and address an array of statistical surveillance tools and techniques. The first two days of the tutorial will focus on hands-on use of specific methodologies through case-studies and elementary introductions. The second two days will concern itself more with current research activities and new research challenges.

The tutorial will address such topics as:

  • Scan statistics
  • Statistical process control
  • Changepoint methods
  • Bayesian approaches
  • Rule-based surveillance
  • False discovery rate and sequential testing
  • Text data surveillance
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    Document last modified on March 14, 2003.