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Speaker: Harriet Black Nembhard, Ph.D., The Pennsylvania State University
Time: Tuesday October 23, 2007; 11:00AM
Location: Executive Classroom 228, Main
Title: Syndromic Surveillance: Improving Public Health Systems Preparedness through Advances in Statistical Modeling
Abstract: Syndromic Surveillance has emerged as a new public health surveillance paradigm to identify disease clusters earlier than would conventional reporting of confirmed cases. The approaches used in syndromic surveillance are similar to those in traditional statistical monitoring. We develop the multivariate cuscore (MCS) control chart and the high density (HD) control chart to aid in early detection. Existing relevant approaches in the literature include nonparametric analogues and the multivariate changepoint (MCP). We demonstrate how these statistical methods can be applied on influenza-like illnesses (ILI) data from the US and France. Challenges are presented by the fact that ILI data are non-normal, not independent, and often nonstationary. In addition, we explore how these statistical methods can be refined to take advantage of prior information about health system characteristics such as increases in over-the-counter medication sales and seasonal patterns of outbreaks.
Biosketch: Harriet Black Nembhard is an associate professor of industrial and manufacturing engineering at the Pennsylvania State University and director of the Laboratory for Quality Engineering and System Transitions (QUEST). Dr. Nembhard
