TITLE: Likelihood Ratio Methods for Outbreak Detection in Spatial and
Spatiotemporal Surveillance

SPEAKER: Prof. Kwok Tsui

ABSTRACT:

For public health surveillance, timely detection of a rate
increase in disease incidence is very important. This talks reviews some
popular methods for temporal surveillance and proposes a general
framework for spatial and spatiotemporal surveillance based onlikelihood
ratio statistics over windows of tests. We show that the CUSUM and other
popular likelihood ratio statistics are special cases under such a
general framework. We compare the efficiency of these surveillance
methods in spatial and spatiotemporal cases for detecting clusters of
incidence using both Monte Carlo simulations and a real example.  We
will also discuss the generalization of weighted likelihood ratio tests
for detecting different shift magnitudes under homogeneous and
non-homogeneous populations.