Monday, April 20, 2020

Seeing the World Through Different Eyes

Data is more that just a bunch of numbers and names. Data is the result of a focused collection of specific values relative to a subject. In the case of the pandemic (COVID-19), this might include a record of individual infected patients, their location, symptoms, test results, whether they required hospitalization, and whether the infection caused the death of the patient.

Even after collecting focused data, it is still just a list of individual items without any usefulness for responding to the virus. The Coronavirus responsible for COVID-19 causes a respiratory illness with symptoms of coughing and shortness of breath. It is related to viruses that cause the common cold and to more severe diseases like SARS and MERS which also caused widespread infections since 2003. So we might be looking for similarities to how these diseases are treated or suppressed in order to fight COVID 19.

From studying data related to earlier epidemics, researchers uncovered an important relationship between the number of cases of infected people over time and the availability of medical resources. This relationship can be expressed by the now-famous "flattening of the curve" graph.

Source: Wiscontext 

The conclusion we can take from this graph is that if the number of cases exceeds the available treatment resources, it is likely that more severe consequences of the infection  will occur, including death.

The relationship between cases and care was discovered by examining the raw data through a variety of lenses. In the study of data, these lenses include sorting, categorizing, summarizing, and visualization. We look for patterns that may indicate characteristics we can exploit. Humans are more likely to recognize visual patterns than tabular patterns; that is why a graph or a map can lead to quicker realizations of important attributes.

Take for example the case of John Snow and the 1854 Cholera outbreak in London. Snow was an English physician who is considered a founder of epidemiology which studies, among other things, the spread of disease. He took the data indicating incidence and location of patients and plotted them on a map.

Source: The Scientist

The map he created (shown above) shows building addresses darkened where cases occurred. In the center of the map is a pump location where surrounding inhabitants came for fresh water. The coincidence of patients surrounding the pump location led Snow to suspect the water supply as the source of the infection. Snow was familiar with the water supply system for the area and knew that the water coming from the pump had been drawn from sewage-polluted sections of the Thames River. Snow presented his findings to the local council and convinced them to disable the well pump by removing the handle.

Data is important, but transforming data into information is the key to putting data to work solvimg problems and improving responses to challenges. Wikipedia puts it this way:

"Snow's findings inspired the adoption of ... fundamental changes in the water and waste systems of London, which led to similar changes in other cities, and a significant improvement in general public health around the world."

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