As the disease map user group grows, these disease maps should prioritize some essential properties that support public health. The example is the filtered maps based on disease and population data aggregated from the 949 Iowa five digit Zip codes. (1) Control the Population Basis of Spatial Support for Estimates of Rates. In Figure 1, it illustrate the difference between the use of an administratively defined spatial support and a support controlled to be appropriate to the phenomenon of interest. (2) Display Rates Continuously through Space. It is closely related to the previous property like presenting the disease rate visually so that it is easy to estimates the true disease risk pattern might look like on the ground. Also in Figure 1 instead of a spatial pattern that stops at the boundaries of the county, the spatially filtered maps continuously over geographic space. (3) Provide Maximum Geographic Detail across the Map. In Figure 1, more populous counties are able to provide intracounty detail. (4) Consider Directly and Indirectly Age-Sex_adjusted Rates. The traditional disease mapping in the United States has used direct age adjustment. When the purpose of the map is to compare the impact of different disease rates on local populations, the indirect adjustment should be used. (See Figure I Panel 2 and 3). (5) Visualize Rates within a Relevant Place Context to Enhance Interpretation. It is recognized that disease maps can not be produced in a vacuum and hidden from public audiences. Instead, it should be available to public so that they can be used in improving population health. (Figure 2)
Beyer, K. M., Tiwari, C., & Rushton, G. (2012). Five essential properties of disease maps. Annals of the Association of American Geographers, 102(5), 1067-1075.
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Beyer, K. M., Tiwari, C., & Rushton, G. (2012). Five essential properties of disease maps. Annals of the Association of American Geographers, 102(5), 1067-1075.
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