The rapid increase in the capabilities of computers has made it possible for desktop GIS users to obtain and analyze geographic information from the U.S. Census, USGS, the EPA, and a variety of other sources. The Connecticut Department of Public Health's (CT DPH) Environmental Epidemiology GIS (EEGIS) facilitates the integration of environmental, demographic, and base layers with health outcome data. We present the data model and spatial algorithms developed for the integration, analysis, and visualization of the spatial and relational information obtained from disparate sources.
The CT DPH has developed methods to analyze geographic data without the limitation of geo-political boundaries (usually a postal code, town or census boundary). CT DPH staff now have the ability to analyze health outcome data against exposure plumes and other environmental exposure models. The goals of the EEGIS are to enable the CT DPH to use its readily available surveillance data to respond efficiently to citizen concerns about the disease clusters, to visualize disease patterns statewide for the purpose of health risk communication, and to generate hypotheses about disease etiology. The EEGIS has also demonstrated the value of surveillance data in helping evaluate the distribution of the pollution burden by race, ethnicity, and income.
Learning Objectives: 1. Describe a model for integrating environmental, demographic, and base layers with health outcome data 2. Identify three biases and problems inherent in the topographic visualization of health outcomes, and methodologic approaches to solving those problems. 3. List the goals and limitations of an environmental health GIS
Keywords: Geographic Information Systems, Survey
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.