Bayesian Spatial and Spatio-Temporal Health Modeling

The Data Science Institute of Hasselt University is excited to offer a Bayesian Workshop: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling.  The workshop is designed to provide a comprehensive introduction to the area of Bayesian Disease mapping using R in applications to Public Health and Epidemiology.   This course sequence is designed for those who want to cover mapping methods, and the use of a variety of software and variants in application to small area health data.

Introduction

Workshop: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling 

The Data Science Institute of Hasselt University is excited to offer a Bayesian Workshop: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling The workshop is designed to provide a comprehensive introduction to the area of Bayesian Disease mapping using R in applications to Public Health and Epidemiology.   This course sequence is designed for those who want to cover mapping methods, and the use of a variety of software and variants in application to small area health data. The speaker is Prof. Andrew Lawson, international renowned expert in disease mapping and spatial epidemiology.

The course will include theoretical input, but also practical elements and participants will be involved in hands-on in the use of R, BRugs (OpenBUGS), Nimble, CARBayes and INLA in disease mapping applications. Both human and veterinary examples will be covered in the course. Examples will range over congenital anomaly birth defects, cancer, foot and mouth disease, influenza and Covid-19 space-time modeling.

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 with R. They will gain insight into the detailed analysis of practical problems in risk estimation and cluster detection.

WHEN?   October 3-4 2022

WHERE?  Hasselt University, Campus Diepenbeek, Building D, Room C110, Belgium

SPEAKER?  Professor Andrew Lawson

Speaker

Andrew B. Lawson is MUSC Distinguished Professor Emeritus of Biostatistics in the Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, College of Medicine. He is ASA Fellow and guest professor at Hasselt University.

He has over 200 journal papers on the subject of spatial epidemiology, spatial statistics and related areas. In addition to a number of book chapters, he is the author of a number of books in areas related to spatial epidemiology and health surveillance. The most recent of these is Lawson, A. B. (2021) Using R for Bayesian Spatial and Spatio-Temporal Health Modeling. CRC Press. This book will be a course text for the workshop. A copy of this book is included in the fee for the course.

Prof. Lawson is founding editor of the Elsevier journal Spatial and Spatio-temporal Epidemiology, and advisor in disease mapping and risk assessment for the World Health Organization (WHO). Prof. Lawson has delivered many short courses in different locations over the last 25 years on Bayesian Disease Mapping with Win/OpenBUGS, CARBayes and INLA, Spatial Epidemiology and disease Clustering.

Day 1: Monday 3 October 2022

The first part of the course consists of sessions dealing with:

  • Basic Concepts of Bayesian methods and disease mapping
  • Bayesian computation: MCMC and alternatives
  • R graphics for spatial Health Data
  • Bayesian Hierarchical Models for disease mapping (BHMs): both simple models including the Poisson-gamma, log-normal,  and convolution model, as well variants including Leroux, mixture, and BYM2 models
  • Model goodness of fit
  • Demonstration of risk estimation and using BRugs/OpenBUGS

Day 2: Tuesday 4 October 2022

In the second part of the course, alternative software packages in R and more advanced models will be discussed. This will include:

  • Nimble
  • CARBayes
  • INLA
  • Space-time modeling with MCMC (Nimble)
  • Space-time modeling with INLA
  • Clustering in space and space-time
  • Infectious disease modeling and surveillance

Registration Information

Registrations are closed!

Registration rates:

Early bird rate (deadline 1 August):

PhD students UHasselt: € 400

Academic staff (non-UHasselt):  € 500

Private sector: € 600

Regular rate (from 1 August):

PhD students UHasselt: € 500

Academic staff (non-UHasselt):  € 600

Private sector: € 700

The registration fee includes courses, handbook and catering (coffee breaks and lunches).

Deadline for registration is 15 September 2022

Venue

The 2-day workshop will take place at Hasselt University, Campus Diepenbeek, Building D, Room C110, Agoralaan, 3590 Diepenbeek, Belgium.

Accommodation

You can find tourist info at: https://www.visithasselt.be/en

Some hotels in Hasselt:

Holiday Inn Express

Thonissenlaan 37, 3500 Hasselt

Yup Hotel

Thonissenlaan 52, 3500 Hasselt

Data Science Institute

+32-11-26 82 98 martine.machiels@uhasselt.be

Agoralaan Gebouw D

3590 Diepenbeek