Using GeoHealth to Make the World Healthy
Dr. Snow’s methodology manually applied mapping to solve the cholera epidemic puzzle. His data sets included geography, sewage disposal patterns, drinking water sources, use of water patterns, peoples’ living patterns, and victim locations. Dr. Snow did not find it was filth, poor living conditions, nor by contact that people contracted the disease. He noted that most of the deaths from the prior outbreak occurred in people living in south part of London, where the water supply was nearest where the city discharged sewage. Yet, the mainstream medical establishment was fixated on the air as the transmitter of disease. Snow firmly believed it was the water, but needed to prove it.
Snow mapped the deaths and their proximity to different water sources in the area. At the end, nearly 700 deaths (in less than 2 weeks) were recorded of people living within 250 yards of one water pump near a leaky sewage outlet. Thus Snow was able to deduce the source of the outbreak by observing statistically unusual patterns that occurred during the outbreak. Thus cholera was spread by drinking fouled water, not by contact or aerosols. While Snow’s approach was with paper and pencil, the approach today is now with computers and GIS programs, a GeoHealth approach. With technology, many data sets can be processed, effectively layering one data set upon another for evaluation and solution.
In 2010, an article in the ESRI newsletter (ArcNews, v32, Spring 2010) noting a presentation by Bill Davenhall in which he said he wanted to see health care and medicine to collide with geography and the environment. The idea was that a patient’s health should not only be involved in medical interventions, but also in the impact from their living environment — their geography (with risks associated with toxic air, water, ground, and food exposures). This is no longer an idea; GeoHealth, the use of GIS in healthcare is now; Its time has come! The amount of data that is now generated in the clinic for patients and the added factors that are involved in after-hospital recovery are overwhelming those whose job is patient care. Without new electronic approaches, the collection, management, dissection, evaluation, and effective use of the massive data download is impossible for the clinician.
Today, we find the processing of multiple Big Data sets (collectively coined as OmniDatum) feasible. This ability provides a means to sort data to find answers to questions about patients asked by the medical community. Before the advent of GIS processing, it was like finding the proverbial needle-in-a-haystack. A near impossible task given the time and cost needed to sort and manage OmniDatum. There are now protocols to input both clinical/medical data and social and community determinants into computations to optimally support the health and welfare of patients post clinical treatment. This GeoHealth approach provides a powerful means to offer full-spectrum health to our population and to our communities.
PS: If you want to read The Ghost Map but cannot take the time now, you can read my blog summary (under Books, March 04, 2012, The Ghost Map)
©Dr. Baldwin H Tom, FIMC