DEPARTMENT OF STATISTICS
Statistics Colloquium
University of Connecticut
Storrs, Connecticut
The Department of Statistics Cordially invites you to a Colloquium
Jian Zou
Assistant Professor
Worcester Polytechnic Institute
Bayesian Spatio-Temporal Methodology for Biosurveillance
ABSTRACT
The complexity of spatio-temporal data in epidemiology and surveillance presents challenges
such as low signal-to-noise ratio and generating high false positive rate for researchers and public
health agencies. Central to the problem in the context of disease outbreaks is a decision structure
that requires trading off false positives for delayed detections. We describe a novel Bayesian
hierarchical model capturing the spatio-temporal dynamics in public health surveillance data sets.
We further quantify the performance of the method to detect outbreaks by incorporating different
criteria, including false alarm rate, timeliness and cost functions. Our data set is derived from
emergency department (ED) visits for Influenza-like illness and respiratory illness in the Indiana
Public Health Emergency Surveillance System (PHESS). The methodology incorporates Gaussian
Markov random field (GMRF) and spatio-temporal conditional autoregressive (CAR) modeling.
Features of this model include timely detection of outbreaks, robust inference to model
misspecification, reasonable prediction performance, as well as attractive analytical and
visualization tool to assist public health authorities in risk assessment. Our numerical results show
that the model captures salient spatio-temporal dynamics that are present in public health
surveillance data sets, and that it appears to detect both “annual” and “atypical” outbreaks in a
timely, accurate manner. We present visualizations that help make model output accessible and
comprehensible to public health authorities. We use an illustrative family of decision rules to show
how output from the model can be used to inform false positive and delayed detection tradeoffs.
DATE: Wednesday, February 18, 2015
TIME: 4:00 p.m.
PLACE: Philip E. Austin Building – Room 105
Coffee will be served at 3:30 in room 326
For more information, contact: Tracy Burke at tracy.burke@uconn.edu