Project Leader, Tom Webster (Boston University School of Public Health)
Developing improved methods for mapping epidemiologic data on reproductive and developmental outcomes while adjusting for known risk factors.
Geographic Information Systems now allow the use of analytic techniques in spatial epidemiology previously not feasible. As a result the mapping of routinely collected health data is now common and often provokes concern when patterns of disease rates appear to have “hot spots,” although it is well understood by epidemiologists that the results may be biased by failure to collect and control for many known risk factors that are unevenly distributed over the area of the map.
Principal Investigator: Thomas Webster, Boston University SPH
Resources availableThe following article discusses methods and analyzes both a synthetic and real data set:
Webster T, Vieira V; Weinberg J; Aschengrau A. Method for mapping population-based case-control studies using Generalized Additive Models. International Journal of Health Geographics 2006, 5:26 (9 June 2006). http://www.ij-healthgeographics.com/content/5/1/26.
The following synthetic data for testing the method is available. This work is available for use under the General Public License.
- Attach:syndata_Scode.txt: text file of S-Plus code for reproducing our analysis using synthetic data
- Attach:syndata.xls(204 kb):excel file of synthetic data
- Attach:syndata-figs.doc (71 kb): word file of crude and adjusted maps of the synthetic data (output from S-Plus mapped using ArcView)
The following article discussed methods and analyzes a real data set:
- Vieira V, Webster T, Weinberg J, Aschengrau A, Ozonoff D. Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: an application of generalized additive models to case-control data. Environ Health. 2005 Jun 14;4:11. http://www.ehjournal.net/content/4/1/11
