Sunday, January 24, 2016

Five Essential Properties of Disease Maps

    Five Essential Properties of Disease Maps 

          Maps are used in a number of different ways to signify countless things. They are especially helpful in understanding patterns in, specifically disease. In the article titled “Five Essential Properties of Disease Maps,” Beyer, Tiwari and Rushton explain the importance of disease maps, and how to make them. It is key that the map is made in the best way possible to fully understand the pattern of disease. Over the past 20 years, they began to recognize the problems with disease maps and were able to classify the problems in 4 categories. These categories include 1) the small numbers problem, 2) the modifiable areal unit problem, 3) the limited variability problem, and 4) the visual impact of large areas problem. They saw that disease maps with these issues were unable to provide useful information when being studied. They decided to develop a methodology in order to create disease maps to make them more adaptive to the area being studied. Their method is called the “adaptive spatial filtering” which means that the map is made based on the density of the population in the area. They argue that this is able to fix the main problems with disease maps.

            Further Beyer et al explain that there are five essential properties of a disease map. These include 1) controlling the population basis of spatial support for estimates of rates, 2) displaying rates continuously through space 3) providing maximum geographic detail across the map, 4) considering directly and indirectly age-sex adjusted rates, and 5) visualizing rates within a relevant place context to enhance interpretation. The maps below show the difference between a map with many of the problems Beyer et al described compared to one with the five essential properties.

The authors of this piece believe that their method is critical when creating a disease map because it allows viewers to better see the patterns of disease. In the future they suggest that the measure of statistical confidence is used to explore implications of disease. Through these maps we can gain an understanding of the spread of disease in order to reduce health inequalities.  

Beyer, K. M., Tiwari, C., & Rushton, G. (2012). Five essential properties of disease maps. Annals of the Association of American Geographers102(5), 1067-1075.

I have acted with honesty and integrity in producing this work and am unaware of anyone who has not
Jolene Klenzendorf 


  1. It's very interesting how we can use GIS to make our maps more accurate and efficient as our understanding of technology increases! Did they explain why these five problems were problematic, and furthermore, would the difference in how we make disease control maps now change the way we gather data about epidemics, do you think?

  2. The authors mention that there are five factors in creating a map like this one. Did they mention the variability of the factors, more specifically, how they determine which factors to prioritize when creating a map and analyzing the map?

  3. One of the authors' criteria that seems very interesting is "Providing maximum geographic detail across the map." I'm curious as to what level of detail they meant. The image above displays roads and urban areas, but not terrain type, or precipitation. Both seem important in mapping the display of certain diseases such as those spread by mosquitos (which would follow moist, highly vegetated or developed areas with no wind.)