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Monday, May 25, 2009
All Workshops take place at the Fairmont Chateau Laurier unless otherwise indicated.
MORNING WORKSHOPS, 09:00-12:00
Workshop #1 - Risk Assessment and Prion Diseases, Dr. Dan Krewski - CANCELLED
Workshop #2 - Causal Inference in Epidemiology , Dr. Robert Platt, Department Epidemiology & Biostatistics, McGill University
This workshop explores issues related to causal inference from a statistical and conceptual perspective. A formal definition of causal effects is presented using counterfactual random variables. This is extended to a consideration of causal diagrams, confounding, and selection bias. Lastly, the session will examine the use of inverse probability weighting and marginal structural models for causal inference.
Workshop #3 - Putting Public Health on the Map: An Introduction to GIS for Public Health Epidemiologists
Location: GIS lab at the University of Ottawa (Room 039)
Note: This workshop is repeated in the afternoon from 13:00-16:00
Description: The epidemiology of disease is often characterized in terms of “person, place, and time”. Important clues about the determinants of disease and disease risk can often be gained by carefully evaluating the “place” component of epidemiology and surveillance. Geographic information systems (GIS) are a group of computer-based tools that allow population, disease, and risk factor data to be integrated, manipulated, and represented on maps that may vary in scale from the extremely local (disease events within a hospital), to the global. Often, public health epidemiologists wish to explore the distribution of health information on a map of a particular jurisdiction, such as a health unit. This workshop will provide epidemiologists with little or no prior experience with GIS with a hands-on, case-based introduction to the creation of maps using health data.
Goals of the workshop:
- Introduce public health epidemiologists to the ArcGIS software package.
- Provide participants with information on different ways to represent data spatially (vector vs. raster, different coordinate systems).
- Introduce basic tools for mapping: opening, manipulating tabular data to create new digital layers, saving data files in ArcGIS, adding attribute data, doing “joins and relates”.
- Introduce participants to the graphical representation of varying levels of disease risk on a map using smoothing methods, in order to create density surfaces.
Course organizers:
Dr. Mike Sawada is the director of the GIS lab at the University of Ottawa; he is interested in a broad range of GIS applications, including the use of spatial methods to evaluate climate change and health services issues. He is a recipient of the 2006 Young Researcher of the Year Award from the University of Ottawa.
Victoria Ng is a doctoral student in epidemiology at The Australian National University, Canberra. Her doctoral thesis evaluates spatial and temporal determinants of Ross River virus infection in Australia.
Melanie Zahab is a doctoral student in geography at the University of Ottawa. Her interests are in the application of GIS to problems in archeology. She is a recipient of the Barry Wellar Award for Outstanding Methodological Achievements in Geomatics.
Dr. David Fisman is a medical epidemiologist at the Ontario Agency for Health Protection and Promotion and a scientist at the Research Institute of the Hospital for Sick Children, Toronto.
AFTERNOON WORKSHOPS, 13:00-16:00
Workshop #3 - Putting Public Health on the Map: An Introduction to GIS for Public Health Epidemiologists
Location: GIS lab at the University of Ottawa (Room 039)
Note: This workshop is a repeat of the morning workshop
Workshop #4 – Introduction to Bayesian Methods, Dr. Michael Escobar, School of Public Health, University of Toronto
In 1990, there was a breakthrough in Bayesian computational methods. Previously, most Bayesian analyses were restricted to simple, limited applications. With the development of Markov Chain Monte Carlo (MCMC) methods, Bayesian inference has become an important applied technique and has been able to handle complex problems. In fact, some problems are now easier to compute with Bayesian methods than with frequentist methods.
The purpose of this course is to introduce applied Bayesian methods to a wide audience. The basic Bayesian philosophy will be discussed and the underlying principles of the MCMC algorithm will be explained. From there, this course will also introduce some methods for computing and making inferences on complex data problems using these methods.
Workshop #5 - Spatial Statistics for Public Health Applications, Dr. Lauren Scott, ESRI Canada
Description: An important GIS development in recent years is the addition of statistical analysis methods designed, specifically, for use with spatial data. This workshop will introduce a variety of core spatial statistics tools available in ArcGIS and will show specifically how they might be applied to Public Health applications. The first part of the workshop will focus on spatial pattern analysis. The second part will introduce the new regression tools added with the latest release of ArcGIS.
Goals of the workshop:
- Explain what spatial statistics are and how they differ from traditional (non-spatial) statistics.
- Introduce a variety of core spatial statistics tools available in ArcGIS, including Standard Deviational Ellipse, Hot Spot Analysis, and Regression.
- Demonstrate the utility of these tools for a range of public health application areas.
- Introduce the basic objectives, terminology, and strategies for performing regression analysis with Spatial Data in ArcGIS 9.3.
- Outline the challenges of regression modeling with spatial data, and the variety of diagnostic tools available in ArcGIS to help overcome these challenges.
- Outline additional resources for learning more about the spatial statistics tools in ArcGIS.
Dr. Lauren Scott has over 23 years experience in software development and GIS. She currently works at ESRI as a product engineer on the Geoprocessing team where she is responsible for software support, education, documentation, and development of spatial statistics tools in ArcGIS. She has been invited to deliver presentations, workshops, and short courses at both national and international agencies, including the Centers for Disease Control, Johns Hopkins, New York City Department of Health, National Institute of Justice, London Health Protection Agency, University College London (UCL) Jill Dando Institute of Crime Science, Sault Ste. Marie Innovation Center, and the University of Copenhagen Institute of Geography. She received her Ph.D. in 1999 from the Joint Doctoral Program at the University of California, Santa Barbara, and San Diego State University. She holds both an M.A. and a B.A. in geography from California State University, Fullerton.
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