Bayesian Methods for Monitoring Public Health Surveillance Data

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Bayesian Methods for Monitoring Public Health
Surveillance Data
October 17, 2002
Owen Devine Division of STD Prevention National
Center for HIV, STD and TB Prevention Centers for
Disease Control and Prevention
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(No Transcript)
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Mapping Surveillance Data
Observed rates can be unstable estimates of
the true underling risk
Num.
Of Rate per County 1998 Pop. Events /100000
Rich 1793 1 56 Davis 229393
128 56 Rich 1793
2 112
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Bayesian Smoothing
Underlying true risk of disease in area i
Prior
Likelihood
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Bayesian Smoothing
Updated (Posterior) distribution of
Fully Bayesian
Empirical Bayes
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Bayesian Smoothing for Detecting Spatial
Aberrations
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Bayesian Smoothing for Detecting Spatial
Aberrations
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An Approach to Bayesian Aberration Detection in
Temporally Referenced Health Surveillance Data
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An Approach to Bayesian Aberration Detection in
Temporally Referenced Health Surveillance Data
Posterior
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An Approach to Bayesian Aberration Detection in
Temporally Referenced Health Surveillance Data
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Bayesian Aberration Detection For Health
Surveillance Data
Bayesian Approach
Pros
Cons
Stabilization Lack of Portability Etiologic
Evaluation Lack of Transparency Intuitive Models
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Bayesian Decision Making
Suppose some rule, , leads to a
decision, for example
Sound alarm
Do not sound alarm
Let be the loss due to
making an incorrect decision, then choose
to minimize the posterior risk,
, where