Monday, February 9, 2015

         Recently, there have been several worldwide disease outbreaks.  These contagious diseases soon turned into epidemics that have claimed many lives.  Fortunately, doctors and scientists are able to track these diseases using GIS software, such as WebDMAP.  This program uses a process called adaptive spatial filtering.  This method relies on adaptive bandwidth filter  “that increases in size inversely with population density rate calculation”. 
There are five essential properties that scientists should use when analyzing disease maps.
            First, these disease maps need to be analyzed with using different base maps.  The figure below illustrates three different maps monitoring colorectal cancer in Iowa.

The next step requires that the disease-infected regions be displayed on the map.  This gives scientists a clear view as to where they should concentrate their efforts.
            Attention to geographic detail is essential when analyzing disease maps.  Geography can act as a highway for disease to spread.  One such example is a contaminated water source;  which can infect a large population of people and/or animals.
            The population’s age and gender need to be measured and recorded for accuracy.   Diseases have the potential to effect men and women differently.   A person’s age is a very important factor that determines the patient’s ability to resist the effects disease or infection.  
            The data collected and the disease/mortality maps created need to be made available to the public.   This is in an effort to offer an outside perspective that can be beneficial in preventing future epidemics.
Researchers have been able to use these maps to identify environmental characteristics and measure disease risk.

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


  1. Can you explain "This method relies on adaptive bandwidth filter 'that increases in size inversely with population density rate calculation'." I'm not 100% on if that is some sort of raster thing or just a calculation using a formula?

  2. Does colorectal cancer really count as a disease though? I suppose it might, but it's not necessarily contagious. Were there other diseases mentioned here that could've been mapped?

  3. How many epidemics can be prevented using this method? In the time that it could take to gather and compile data, couldn't an extremely contagious disease spread even further before the data analysis is complete, requiring more data to be collected and thus giving the disease more time to spread?