Year: 1987
Type: article
Abstract: In attempting to analyze geographic clusters of disease, one is obliged to take account of varying population density.Customary methods, for example calculation of rates for subregions, are unsatisfactory: if subregions are too large, geographic detail is lost; if too small, stable rates cannot be calculated.In either case, adjacency relationships among cases are not easily analyzed.The usual difficulties are avoided by using an innovative projection technique.On a transformed map, population density is equalized while preserving adjacency relationships, so that clusters of cases can be easily recognized and their statistical significance measured.In this paper a density-equalizing computer algorithm is briefly described, and its use illustrated in representative applications.
Authors: S. Selvin, D.W. Merrill, John Schulman, Gary M. Shaw, William M. Benson, Marcus Mohr
Language: English
Subfield: Geography, Planning and Development
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
Funder: U.S. Department of Energy
Awards: G1398330795, G1643223109, G193590374
OpenAlex ID: W151051345