How 19th Century Analytics Stopped Deadly Cholera Outbreak

What lessons can our busy, modern business execs learn from events from the mid-19th century?


To find out more, let’s pick up on this excerpt from a late night conversation over hot cocoa and donuts taken from a surveillance scanner at the Bat Cave between Batman and Robin.


Holy Business Intelligence, Batman, I was just reading about John Snow. Did he really use Analytics to cure cholera in the 18th century?


Well, not exactly Robin, but his efforts went a long way to solving the problem of cholera epidemics in general  and, yes, saving thousands, perhaps hundreds of thousands, of lives in London and, ultimately, all over the world!


Really Batman? How did that happen?



Well, this is how it started. As you know, Robin, Analytics is a process we still use in business and science today.


Aw, Batman, is this just another one of your bedtime stories?


No Robin, this is an exciting development in Medical Science that became part of the foundation that modern Analytics is built upon.

And, besides that, Robin, Snow used some of the earliest examples of geocoding and heat mapping!


What are heat mapping and geocoding, Batman?


We’ll get to that a little later Robin. First,Let’s talk about who John Snow was.

Without a doubt he was a visionary man. His genius extended far beyond Analytics. Some of his other accomplishments included pushing for the adoption of anaesthesia and medical hygiene before these concepts were the conventional wisdom of the day.

Let’s review the problem that John Snow set out to solve.

A cholera epidemic had broken out in London in 1850 and people were dying in droves. Worst of all, nobody knew why! Microbes had yet to be discovered. Doctors thought that cholera was carried by the “vapors” of the air instead of by germs.

The scientific community was mystified how cholera was transmitted. No one knew what steps to take to end the epidemic. But, fortunately, Snow also was the Father of Modern Epidemiology which is a science that employs an assortment of statistical tools to establish the association between exposures and health outcomes.

John Snow was looking for even deeper insights in this epidemic. He was intent on establishing causal relationships (employing a heavy reliance of analytics) in order to derive many of his conclusions.

Robin, for the sake of clarity, the term Analytics, as we’re using it here, signifies the discovery and communication of meaningful patterns in data.

While this approach was key to John Snow’s success, it is even more useful in areas rich with recorded information (such as modern businesses with their continuously streaming business data sources).

By it’s nature, analytics often favors data visualization to communicate insights quickly and concisely. Fortunately, this was another area in which John Snow excelled naturally.

Now, modern day analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Let’s see how Dr. Snow used Analytics to find the answers in tracing the source of the cholera outbreak in Soho, London, in 1854.

He placed the disease data into a visualization. His visualizations became a (heat)map that was stunningly clear. He used this heat map to portray his findings graphically with each cholera occurrence geocoded for location.

A heat map is a graphical representation of data where the individual values contained in a matrix are represented as colors. Heat maps provide relevant and trustworthy statistics. His map was accurately geocoded to identify the exact locations. It was this geocoding that led him to the source of the disease vector.

His findings were so irrefutable that they inspired fundamental changes in the water and waste systems of London. This, in turn, led to similar changes in other cities worldwide.

This was a huge accomplishment. Overall the sum total of these changes led to a significant improvement in public health around the world. More amazing is the fact that all of this took place before the disease vector that was the source of cholera had been identified!


What is geocoding again, Batman?


Good question Robin! Geocoding is the process of clarifying the description of a location, using such descriptors as a postal address or place name, or with geographic coordinates from spatial reference data such as building polygons, land parcels, street addresses, ZIP codes etc.

Remember, Robin, that microbes were not understood to be the source of disease at that time. Physicians, in Snow’s century, still believed that illnesses, such as cholera, were carried by “humors” through the air. If Snow had relied on conventional wisdom, control of cholera would never have been achieved.

Dr Snow’s map of the cholera outbreak in nineteenth century London changed how we see disease today while, at the same time, giving modern data journalists a successful model on which to base their work in the present.


When heat maps are effective, they can tell a story in a language that everyone can understand. Snow’s map had a huge impact on its own because it was dramatic and a great data visualisation in a time when such tools were not typically used! It was the cluster of ticks (representing cholera victims) around the Broad street pump that alerted Snow to the source of the problem behind the outbreak.

Cholera Pic

Fig. 1 How We Got to Now, Episode 1, still image. 

The map essentially represented each death as a bar. Even with casual observation, it quickly became apparent that the cases were clustered around the pump on Broad Street. So, instead of traveling through the air, the pathogen was traveling through the water: specifically through the Broad Street pumping station!


That’s fine Batman, but how did Snow account for inconsistencies? There must have been inconsistencies, right?


You’re right, Robin, that’s a good insight. Not everything was completely straightforward. Snow reasoned his way through the inconsistencies.

There were some outliers. Of these, Snow wrote that: “ In some of the instances, where the deaths are scattered a little further from the rest on the map, the malady was probably contracted at a nearer point to the pump”

To illustrate his point, Snow spoke of one 59-year-old woman who sent daily for water from the Broad street pump because she liked its taste. He says: “I was informed by this lady’s son that she had not been in the neighbourhood of Broad Street for many months. A cart went from Broad Street to West End every day and it was the custom to take out a large bottle of the water from the pump in Broad Street, as she preferred it. The water was taken on Thursday 31st August., and she drank of it in the evening, and also on Friday. She was seized with cholera on the evening of the latter day, and died on Saturday”

In another illustration, at a nearby brewery Dr. Snow chronicled how the workers were allowed all the beer they could drink. These workers may not have drunk any water at all. At any rate, it didn’t matter much because the brewery had it’s own water supply. Consequently, there were fewer cases of cholera. There was also a workhouse nearby. It was surrounded by cholera cases but appeared unaffected. And, once again, the workhouse had a separate water supply.

Upon further investigation of the Broad Street pump, Robin, it turned out that the water for the pump was polluted by sewage from a nearby cesspit where a baby’s nappy (diaper) contaminated with cholera had been dumped.

The map gave an impressive overview of the distribution of the cholera cases. But Snow didn’t just produce a map; it was just one part of his detailed statistical analysis. He made an accounting for all of the possibilities.

Snow was born more than 200 years ago. His work stopped cholera, an unseen disease, before the existence of microbes were even officially acknowledged. He did this by pioneering modern analytic methods which have only been refined further over time!

As the Public Health Perspectives blog says, he changed how we see data visualisations, and how we see microbes (before we knew that they even existed for certain). John Snow used what he did know as a platform from which to discover and to track the unknown!


Today, Robin, when we work with Analytics, we have many advantages that John Snow didn’t have. That’s because of the many talented people who have contributed in developing and perfecting the methods and systems  that he first pioneered in the 19th century.

Their efforts have resulted in a clarity and ease of use with Analytics that Snow could only have imagined. Because of these advances, all business managers or executives can choose to use powerful analytic tools. This will give them their own insights.


Gee, Batman, with modern analytics any forward-thinking manager can look like a prophet or make decisions like the President!


Let’s not get ahead of ourselves, Robin. Analytics allow us to enhance our natural abilities and insights and build on a foundation of solid facts and interrelationships which may have, otherwise, been obscured. They permit you to look at all of the links in the data chain, an audit trail of events and connections, if you will.


Golly Batman, that was fascinating! Who should I talk to if I want to learn more about Analytics? How does Business Intelligence work with analytics?


Just as analytics has evolved, these tools have matured as well. Once you start to use them, you’ll find it hard to believe that you ever lived without them! Enter the modern analytics age to find the solution to your own mysteries using the best tools available!

(The Cholera outbreak from 1848-49 killed approximately 54,000-62,000 in London, and the outbreak from 1853-54 killed an estimated 31,000 in London.[3])


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