The video maps presented here are for a time period going on several years of age by now. Every seven to ten years, enough changes have occurred, in small increments per year of that time frame, for some changes in secondary and occasionally primary diffusion routes to occur. Some writers like to claim that technological changes are significant every six months to two years. If this is the case, then the big businesses are in fact several generations behind in the knowledge base related to mapping their results using GIS.
A good example of just how behind the times corporations have become is demonstrated by the lack of implementation of GIS as a major and primary tool for their projects. Due to the slow learning curve business leaders often have with new technologies like GIS, combined with stubbornness on their behalf expressed by those who see no use for this new technology during the early years, we are left with companies that are no longer innovative, and which lack the base knowledge needed to make the best use of this new technology.
These images are by no means the final evidence for the existence of this problem within non-innovative business settings. But they do exemplify how far ahead of the time these business could and should be. For disease and public health analyses, a disease is going to behave differently across time and space, not exist as some monolithic public health problem with just one or a very few set of unique numebrs that can be assigned to it. By knowing the details about how health and disease behave over time and space, we can develop more effective intervention, treatment and prevention programs, and even save ourselves a few dollars in the attached costs for health care linked to these diseases every now and then.
The limiting factor for now is lack of adequate understanding and insight into the value of this potential application for spatial analysis in population health mapping. We are not just redefining our outcomes again, only spatially this next time through, we are defining changes over time and space, not simple dollar value differences or probability figures applied to big versus small areas, and points depicting towns or cities on a map. The goal with this method of mapping spatial statistics is to generate a statistical probability map depicting the distribution of health and then define exact places or regions where specific changes have to be made for a specific group of people. Not just another figure using decades old concepts to illustrate where too much money is being spent and where more money should in turn be made.
To better understand the source for this data it is recommended that the readers go to the following recent article on the history of the Big Data movement.
Information Week. Health Care. Accessed 1/3/2013.
Suffice it to say, a picture is worth a thousand words, or in this case, a map worth approximately 2800 grid cells or spatial measures used to report local or national population health.
Click on Icons or Symbols to see examples