What is HealthVis?

Map-based exploration of georeferenced health statistics (using static printed maps) has, in the past, lead to insights concerning health/environment interaction. Print maps have been a primary visual thinking tool used to identify geographic clusters (i.e., “hot spots” and other regular features of disease and to compare these features with patterns of potential etiologic agents. For example, a map of oral cancer death rates among white females in the U.S. prompted a study of occupation and lifestyle in North Carolina that identified snuff dipping as a major risk factor for this tumor (see: Winn, Blot et al., 1981). Dynamic geovisualization methods extend traditional cartographic approaches for representing georeferenced health statistics and related information in at least two ways: by emphasizing the use of maps and other representation forms to construct knowledge (not just to present it) and by dynamically linking the visual map display with both the underlying geographic data structures and the system users (resulting in maps that change in response to changes in data and/or to actions on the part of users).

A screenshot of an exploratory health visualization tool developed at the GeoVISTA Center. This image provides an example of linking traditional statistical graphics (a scatterplot) and mapped heath data.

In a series of studies supported by the U.S. Centers for Disease Control, National Center for Health Statistics, members of our research team investigated a series of questions associated with design and symbolization for disease atlases, and worked on production of a NCHS mortality atlas. This work was (and continues to be) followed by a series of studies focused on dynamic geovisualization methods that offer the potential to extend substantially the role of maps and related visualization methods in analysis of health statistics, as well as analysis of socioeconomic statistics more generally (supported by NCHS, the National Cancer Institute, and the National Science Foundation). One focus of this work has been to understand the cognitive aspects of map use in the context of health data analysis. Another has been to develop a suite of visual analysis tools that integrate principles from cartography, GIS, and exploratory data analysis (EDA) and to test the usability of these tools. The initial tangible product of this later research is a set of extensions to ESRI’s ArcView GIS to support dynamically linked views, focusing, brushing, and animation.

These images show an animation of heart disease mortalilty rates over a fifteen-year period. Click the first image to start the sequence of images or view each image independently.

-More about HealthVis

-Multivariate Representation Methods for Time Series Geo-referenced Health Statistics Data
-For details of National Cancer Institute supported research
-More about our NCHS-funded research
-Read about the Mortality Atlas
-Read about other projects worked on by GeoVISTA

These visual-oriented studies are complemented by related work on the integration of visual and analytical methods for finding clusters in point pattern data (see the images below) as well as recent work in GeoComputation.

These images are screenshots of a software prototype facilitating the visual exploration of point patterns at various scales of analysis. Follow this link for more information.


Further Reading

For more about our health data visualization and analysis research, check out the following:

Brewer, C. A., and A. M. MacEachren. 1995. Evaluation of map color schemes for the NCHS mortality atlas. Proceedings, International Symposium on Computer Mapping in Epidemiology, Tampa, FL, February 12-15.

Brewer, C. A., A. M. MacEachren, and L. W. Pickle. 1995. Evaluation of map color schemes for the NCHS mortality atlas, in Cognitive Aspects of Statistical Mapping, vol. Cognitive Methods Staff, Working Papers Series, No. 18. Edited by L. W. Pickle and D. J. Herrmann, pp. 191-200. Washington, D. C.: Centers for Disease Control, National Center for Health Statistics. MacEachren, A. M., C. A.

Brewer, and L. Pickle. 1995. Mapping health statistics: Representing data reliability. Proceedings of the 17th International Cartographic Conference, Barcelona, Spain, September 3-9.

Brewer, C. A., A. M. MacEachren, L. W. Pickle, and D. Herrmann. 1997. Mapping mortality: Evaluating color schemes for choropleth maps. Annals of the Association of American Geographers 87:411-438.

Haug, D., A. M. MacEachren, F. Boscoe, D. Brown, M. Marrara, C. Polsky, and J. Beedasy. 1997. Implementing exploratory spatial data analysis methods for multivariate health statistics. Proceedings of GIS/LIS '97, Cincinnati, OH, Oct. 28-30, 1997, pp. 205-212.

MacEachren, A. M., C. Polsky, D. Haug, D. Brown, F. Boscoe, J. Beedasy, L. Pickle, and M. Marrara. 1997. Visualizing spatial relationships among health, environmental, and demographic statistics: interface design issues. Proceedings, 18th International Cartographic Conference, Stockholm, June 23-27, pp. 880-887.

MacEachren, A. M., F. P. Boscoe, D. Haug, and L. W. Pickle. 1998. Geographic Visualization: Designing Manipulable Maps for Exploring Temporally Varying Georeferenced Statistics. Proceedings, Information Visualization '98, Reliegh-Durham, NC, Oct. 19-20, 1998, pp. 87-94.

MacEachren, A. M., C. A. Brewer, and L. Pickle. 1998. Visualizing Georeferenced data: Representing reliability of health statistics. Environment and Planning: A 30:1547-1561.