An Introduction to Bayesian Disease Mapping
*A Two-Day Course*
*November 17th - 18th 2011*
*Historic Charleston, South Carolina*
*Course content*
This course is designed to provide an introduction to the area of
Bayesian disease mapping in applications to Public Health and
Epidemiology:
The two-day course consists of sessions dealing with:
*DAY 1*
· Basic concepts of Bayesian methods and disease mapping
· Bayesian computation and MCMC
· Basic R and WinBUGS use
· Demonstration of risk estimation and cluster detection using
WinBUGS
*DAY 2*
· Hands-on with simple WinBUGS models: Poisson-gamma; convolution
models
for risk estimation
· Ecological analysis, cluster models and space-time analysis
· infectious disease models and veterinary data
This is designed for those who want to cover more advanced mapping
methods, and includes ecological analysis and the use of WinBUGS
software.
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 human and veterinary
examples will
be covered in the course as well as simple infectious disease
space-time
modelling. Examples will range over congenital anomaly birth data,
influenza in South Carolina, foot-and-mouth disease in the UK and
oral
cancer in Georgia.
*The speaker*
*Professor Andrew B. Lawson* (Div 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* will be a course text for this course. A copy of
the
book is included in the course fee.
*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 disease data. Some statistical/epidemiological
background
would be beneficial but is not essential.
*Why attend*
Participants will gain an in-depth understanding of the basic
issues,
methods and techniques used in the analysis of spatial health data
using
a Bayesian approach. They will gain insight into the detailed
analysis
of practical problems in risk estimation and cluster detection.
The
course is presented by a leading researcher in the field of
disease
mapping and spatial epidemiology.
*course fees*
Two-day Course - $500.00
Two-day course fee includes comprehensive course notes, lunch,
refreshments and a copy of "Bayesian Disease Mapping: Hierarchical
Modeling in Spatial Epidemiology", Lawson, A. B., (2009), CRC
press, New
York.
*Attendees must bring a laptop with R and WinBUGS 1.4 software
preloaded*. Datasets will be provided. R and WinBUGS software can
be
downloaded from the following websites: http://cran.wustl.edu
and/or www.mrc-bsu.cam.ac.uk/bugs
*VENUE*
The course will take place on the campus of the Medical University
of
South Carolina, Division of Biostatistics & Epidemiology, Room
301, 135 Cannon
Street, Charleston, South Carolina.
Additional information on Charleston and area hotel accommodations
may
be found at www.charlestoncvb.com.
Download a campus map at www.musc.edu .
*REGISTRATION INFORMATION*
For further infromation and registration form go to:
http://se.musc.edu/bin/y/v/IBDM%20Advertisement-NOV2011_F.pdf
For general queries contact June Watson: [log in to unmask]
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