GIS@SU

Five Essential Properties of Disease Maps

            The current model for creating a disease map needs reform according to this article. There are five essential properties that the article suggests will help GIS create a more accurate and easier map for the viewer to read. Every map that is created needs to be different and specialized for the type of map it is. Disease maps need to be easy to read and understand so the viewer does not need to be trained to read a map in order to learn what the map is trying to convey.

            According to the article the five essential properties to making a good disease map include: control of the population basis of spatial support for estimating rates, display rates continuously through space, provide maximum geographic detail across the map, consider directly and indirectly age-sex adjusted rates, and visualize rates within a relevant place of context. Within the last decade there has been a lot of growth in disease and mortality maps. The problem with the model of these maps are they are too hard to read the numbers that they are trying to convey and they are less reliable based off of the structure of how these maps are made.

            The system that this article is suggesting is to use these five essential properties. It breaks down to some easy guidelines that the GIS map makers need to follow. They need to use an adaptive bandwidth filter of uniform shape that increases in size inversely with the population density for disease rate calculation. They need to use gradual transitions and break up the population more so the map is more accurate and less generalized. The disease rates need to be presented visually so the viewer will understand what the map is trying to convey. The current boundaries on the disease maps are removing too much spatial detail. They need to use local populations instead of basing the disease rates off of the overall county averages. Some counties are less populated than others, yet still as wide so basing the rates off of a full county average, it is representing false information and does not paint as good as a picture as breaking up the population and using local populous for the rates. Lastly the article states that everyone should have a right to view the disease maps because it will allow the population to improve their health because they know what the disease rates are and can make decisions based on those numbers.

            Disease maps provide the context within which policy questions are raised and resolved. The maps will show the disease patterns. And by following this model for the disease maps, it allows the GIS operators to use the same guideline that will provide a productive map while allowing room for the operator to design each map differently in order to effectively show what they are trying to convey.

Bibliography:

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.