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Places remain for a new multi-day Course Sequence:

Introduction to Bayesian Disease Mapping (IBDM)
Bayesian Disease Mapping with INLA (BDMI)
Advanced Bayesian Disease Mapping  (ABDM)

**Offering of Introductory and Advanced BDM courses and BDM with INLA in 
MUSC, Charleston, SC, USA**

Historic Charleston, South Carolina

  *Course content*

These courses are designed to provide a comprehensive introduction to 
the area of Bayesian disease mapping in applications to Public Health 
and Epidemiology:
The IBDM course will run on March 14th - 15th, the BDMI course will run 
on March 16th
and the ABDM course will run on March 17th - 18th 2016.

The BDMI course provides a hands-on introduction to spatial health 
modeling with INLA, while more advanced INLA examples are included in 
the ABDM course.
Both spatial and spatio-temporal analyses using WinBUGS and INLA will be 
considered.
Examples will range over childhood asthma data from Georgia, influenza 
in South Carolina, foot-and-mouth disease in the UK and Ohio respiratory 
cancer.

  *The speaker*

Professor Andrew B. Lawson (Department of Public Health Sciences, 
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, the 2nd Edition of the volume
*Bayesian Disease Mapping* will be a course text for the IBDM course, 
and is included in the IBDM course fee.


  *REGISTRATION INFORMATION*

Detailed information and registration form is available from

http://academicdepartments.musc.edu/phs/docs/march2016.pdf

Phone registration to:

Department of Public Health Sciences

  (843) 876-1578

  Fax registration form to:

  Department of Public Health Sciences

  (843) 792-6000

  Booking Enquiries can be made by
  E-mail to June Watson at [log in to unmask]

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