Space-Time Analysis of Health Data Workshop

October 21 and 22, 2010
(8:00 AM to 5:00 PM)

Location
TerraSeer Office
3526 W. Liberty, Suite 100
Ann Arbor, MI 48103

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"Space-Time Analysis of Health Data, was very useful and informative workshop. Dr. Jacquez presented exploratory space-time data analysis, including map animation and cluster analysis, as well as geographically weighted regression in a clear, concise manner and provided examples and tutorials relating the methodology to our work."
Linda Schieb, MSPH
Epidemiologist
Division for Heart Disease and Stroke Prevention
Centers for Disease Control and Prevention

This workshop will introduce spatial statistics for the analysis of health and environmental data, using time as an integral part of analysis and visualization. The two days will include time-dynamic disease clustering analysis, geographically weighted regression, geostatistical analysis of environmental data, and analysis of aggregated and individual level health outcomes.

The workshop will feature hands-on training with our Space Time Intelligence System (STIS) software, and is recommended for public health professionals, researchers, and academics. Participants should have experience using spatial data and familiarity with geostatistical analysis. The software will be provided on the participants’ personal computers and include a one-year license.

Day One Instructor:

Geoffrey Jacquez, Ph.D.
Geoffrey Jacquez, Ph.D.

Overview:

This workshop will introduce participants to space-time analysis both conceptually and operationally. The day will include descriptions of public health analyses that have both spatial and temporal dimensions, challenges and solutions in performing such analyses, and an introduction to the Space Time Intelligence System (STIS) software from TerraSeer.

Learning Objectives:

By the end of the day participants will:

  • Load data into the software including case-control data, mobility histories (e.g. residential histories with time-dynamic covariates and risk factors), morphing polygons (e.g. representing municipal water supplies whose boundaries and contaminant concentrations change through time) and boundary files (e.g. representing census geographies);
  • Visualize the data in space-time, including map animation, and statistical and cartographic brushing in order to reveal data relationships;
  • Quantify space-time patterns using time-dynamic cluster analysis;
  • Undertake aspatial and geographically weighted regression with time-dynamic data.

Day Two Instructor:

Pierre Goovaerts, Ph.D.
Pierre Goovaerts, Ph.D.

Overview:

Conceptual and operational introduction to the geostatistical analysis of environmental and health outcomes. The day will include descriptions of geostatistical applications in environmental epidemiology (analysis of both aggregated and individual-level health outcomes), challenges and solutions in performing such analyses. Participants will use the Space Time Intelligence System (STIS) software from TerraSeer in hands-on training exercises.

Learning Objectives:

By the end of the day participants will be able to:

  • Analyze and model the spatial variability of their data (estimation of range of autocorrelation and detection of anisotropy);
  • Map sparsely sampled environmental attributes, and characterize the reliability of those maps;
  • Apply geostatistical smoothers to maps of cancer rates and create isopleths maps (spatial disaggregation);
  • Map probability of occurrence of health outcomes (e.g. late-stage diagnosis) from geocoded data.