Announcing the first European offering of this successful course
previously offered only in North America:
Notification of an advance WInBUGS-based disease mapping course
Advanced Bayesian Disease Mapping
A Two-Day Course
October 23rd - 24th
University of Copenhagen, Copenhagen, Denmark
COURSE CONTENT
This course is designed to provide advanced coverage
of Bayesian disease mapping topics in applications to
Public Health and Epidemiology: It is intended as an extension
to the course: ‘An Introduction to Bayesian Disease Mapping’.
Emphasis on the course is placed on spatial and spatio-temporal
Bayesian modeling issues, and some knowledge of Bayesian computation
and WinBUGS is assumed.
The two-day course consists of sessions dealing with:
DAY 1 Spatial topics
• Spatial models and simple variants: convolution, proper CAR, full MVN
• Special applications: sparse count data: zip and factorial regression
• Special applications: latent structure (L&C and mixtures)
• Spatial survival modelling
• Measurement error, SEMS and Joint modelling.
• WinBUGS, R2winBUGS and BRugs
DAY 2 Spatio-temporal modelling topics
• Basic ST models: Bernardinelli, Knorr-Held, Waller; seasonal effects
• ST latent structure modeling
• Infectious disease models: FMD and influenza outbreaks
This is designed for those who want to cover advanced BDM methods,
and includes advanced use of WinBUGS and related R functions:
R2WinBUGS, BRugs. The course will include theoretical input,
but also practical elements and participants will be involved
hands-on in the use of R and WinBUGS in disease mapping applications.
Both spatial and spatio-temporal analyses will be considered.
Examples will range over childhood asthma data from Georgia,
influenza in South Carolina, foot-and-mouth disease in the UK
and prostate cancer in Louisiana.
THE SPEAKER
Professor Andrew B. Lawson (Division of Biostatistics &
Epidemiology,
College of Medicine, Medical University of South Carolina)
is a World Health Organization (WHO) advisor on Disease Mapping
and organized with the WHO an International workshop on this
topic which has led to an edited volume “Disease Mapping and Risk
Assessment for Public Health”. He has published a number of books
focused on disease mapping and spatial epidemiology. In particular,
a new volume entitled Bayesian Disease Mapping: hierarchical modeling
in spatial epidemiology will be a course text for this course.
WHO SHOULD ATTEND
The course is intended for epidemiologists and public health workers
who need to analyse geographical disease incidence. In addition,
the course may be of interest to statisticians or geographers and
planners who deal with spatial and spatio-temporal disease data.
Some statistical/epidemiological background would be beneficial
but is not essential.
For more information, the brochure and application form go to
http://www.iph.life.ku.dk/Aktiviteter/2009/231009_241009_Advanced_Bayesian_Disease_Mapping.aspx
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