Improving Methods for Reporting Spatial Epidemiologic Data

To the Editor: A recent perspective in this journal (1) pointed out problems with the present, county-referenced system for reporting spatial epidemiologic data. Problems identi-fi ed included coarse spatial resolution of county-referenced data and differences across the United States in size of counties, making data for the western part of the country coarser in resolution than data for the eastern part. Eisen and Eisen correctly pointed out that these problems complicate spatial analyses of epidemiologic data (1). However, the solutions that they propose , referencing epidemiologic data to ZIP codes or census tracts, partially solve only the fi rst problem. The problem of regional differences in spatial resolution of county -referenced data is, unfortunately, refl ected in counties, ZIP codes, and census tracts, as shown in plots of nearest-neighbor distances among unit centroids as a function of longitude (Figure). Because all 3 region-alizations are based on human populations , the much greater population density in the eastern United States creates fi ner scale dispersion in the east. Thus, a shift to ZIP codes or census tracts does nothing to resolve the problem of regional differences in spatial resolution. The problem of coarse spatial resolution is only partially addressed by the ZIP code or census tract solution. ZIP codes and census tracts cover fi xed areas and can misrepresent the spatial precision of epidemiologic records. A traveling salesperson who covers the state of Wyoming each week would be represented identically as his or her next-door neighbor who is housebound, although spatial precision differs considerably between the 2 persons. Precision of the house-bound neighbor could be better represented than county, ZIP code, or census tract. ZIP codes and census tracts change periodically, and ZIP codes do not have defi ned spatial extents per se (2). Thus, a better and more fl exible solution is needed. The biodiversity world has already addressed this challenge. The point-radius method for georefer-encing locality descriptions (3) estimates a best guess for the exposure site (e.g., residence, workplace) but describes uncertainty in that georefer-ence is a radius that expresses spatial uncertainty in the record (i.e., compare our traveling salesperson with his or her housebound neighbor) and in translation into geographic coordinates (including uncertainty in the locality descriptor, spatial footprint of the locality described, imprecision in the locality identifi ed, and any other sources of imprecision). Point-radius georeferences are easily recorded and reported, are consistent and reproducible , and …