Incorporating indirect standardization in tests for disease clustering in a GIS environment

Public health disease surveillance includes the monitoring of incident disease cases in order to detect geographic and/or temporal trends. One enhances the value of surveillance with respect to a particular disease by incorporating available data on the population at risk regarding various risk factors associated with the disease. Geographic Information Systems (GIS's) allow researchers to easily merge spatially-referenced data including those collected and stored by different agencies and organizations. GIS's may be used in disease surveillance to standardize populations at risk in order to adjust for possible confounding variables. We review basic issues and concepts associated with disease surveillance and outline some questions of public health interest. We illustrate how GIS facilitates the calculation of indirectly standardized disease rates, a common tool in epidemiologic analysis for adjusting for the heterogeneous distribution of common risk factors in a population. We illustrate the approach by refining results from a study involving leukemia incidence around hazardous waste sites in upstate New York.