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 Kalman-filtering
• 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 (Dept of Biostatistics, Bioinformatics & 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 and refreshments.

* Attendees must bring a laptop with R and WinBUGS 1.4.3 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, Department of Biostatistics, Bioinformatics and Epidemiology, Room 301, 135 Cannon Street, Charleston, South Carolina.

AREA ACCOMODATIONS:

Additional information on Charleston and area hotel accommodations may be found at www.charlestoncvb.com. Download a campus map at www.musc.edu.

Registration Form