How The Coronavirus (COVID-19) Might be Stopped by Data Science

We know that data and analytics play a role in everyday products — from recommendations on what music we might like to hear to automated re-routing by our GPS system. But how might the power of analytics be brought to bear on a disease that is currently threatening the health and economic welfare of people across the globe?

If we rewind the clock to the 1850s, there are two significant examples of how early pioneers in data science made incredible impacts on the world that can provide some insight into what we might see happen next.

A powerful case of data and analytics being leveraged to drive a significant change to the course of a disease spreading.

It was 1852, and the cholera pandemic had made its way to London. Over 23,000 people had died already. To make matters worse, unbalanced press reporting led people to believe that victims were more likely to die in the hospital than their homes, and that doctors would kill their patients for anatomical dissection, an outcome known as “Burking.”

John Snow, who is frequently described as the father of epidemiology, began to geospatially analyze the deaths that were occurring in London and isolated the source of the disease, a contaminated well that supplied water in the Soho area of London — the Broad Street Pump.

Map of cholera spread in London

(Map of John Snow's recordings of cholera cases in London.) 

Using his analysis, he convinced local officials to remove the handle to the pump, and the cholera cases rapidly dropped, ending the spread of the disease in London.

Just a few years later, in nearly the same geography, a young nurse, Florence Nightingale, solved another significant medical problem. The British Empire was at war against the Russian Empire, and thousands of soldiers were being hospitalized. The conditions at the hospitals were horrid and the odds of surviving once admitted were less than 60%.

Nightingale was data driven, and as she implemented new procedures (like hand washing), she methodically recorded data on how each performed and analyzed the results. One of the most famous reports showed how her practices in these field hospitals reduced the mortality rates from 42% to 2%. And if that wasn’t compelling enough, Nightingale gathered data on these same rates from the best London hospitals to show that these innovative practices needed to be instituted everywhere.

Many of these methods used to reduce the spread of disease are still practiced today. Believe it or not, during that period, most believed that foul odors were the causes of how diseases spread. 

These two early pioneers in data science set the stage for many that followed. In both cases, they were domain experts trained in medicine. They had access to data and an understanding of how to analyze the data to drive outcomes. And this pattern continues to repeat in more modern-day examples.

In a different kind of disease outbreak, during the avian flu pandemic in 2009, we saw Alteryx leveraged by the USDA to respond with incredible speed to stop the outbreak. Utilizing geospatial data and the modern-day analytics platform Alteryx, the agency was able to drive analysis to the field faster than before, helping to end the outbreak quickly and reduce the economic impact.

What Breakthroughs Might Occur to Slow Down or End the Coronavirus (Covid-19)?

There are current reports out of China that one of the biggest enablers to slowing down the spread has been the use of Artificial Intelligence (AI). By logging where reported cases were occurring and joining that data with GPS movement of cell phones, the government was able to create analytic models to predict what neighborhoods were most likely to have future cases. With this information, they could rapidly quarantine and put measures in place to reduce and/or stop the spread of the disease. While this level of data sharing would likely not occur in many other countries, early indications suggest the actions have meaningfully reduced the impact of the disease, with China already reporting fewer new cases than several other countries.

Case in Point

Deanna Sanchez, a phenomenal data scientist who is focused on geospatial relationships, also has domain knowledge, with a concentration in Medical Geography. Applying this to the coronavirus, she’s already seeing patterns in the data.

“By using Alteryx we were able to create the maps below, showing the spread of the coronavirus in the U.S. over the period of a few weeks. Each dot represents confirmed cases of the disease with color variations illustrating one or more instances of the disease.

 Map of Coronavirus spread  Map of Coronavirus spread

Note: Maps show data of confirmed cases as of 02/11/20 10:50.

“The spread and reach of the disease are both visually palpable while providing instant insights, such as the disease’s limited impact, its containment to major cities, and its non-contiguous spread. The 'where' of the coronavirus, its propagation patterns and the types of people it affects can also be effectively analyzed using GIS.”

— Deanna Sanchez, Alteryx ACE, Practice Manager – Intelligence & Analytics, PK – the Experience Engineering Firm (How Spatial Analytics Can Help Fight the Coronavirus)

Might Data Science Continue to be Leveraged to Stop the Spread of the Coronavirus? 

When I was debarking a plane recently, I was interviewed by the CDC based on analytics that showed I had traveled to a high-risk area. Certainly, this is a great analytic use case and one that is incredibly easy to implement on modern-day analytic platforms. But I believe there are still more breakthroughs to come with even more significant effects, whether in vaccine analytics or containment methodologies, in treatment efficacy analysis, or new procedures to protect first responders. 

I expect amazing people with great subject matter experience and knowledge to continue to leverage advanced analytic tools and techniques to change the world, and fully expect to hear more examples of how COVID-19 meets its match with today’s superhero – the knowledge worker with data science skills. 

Key Takeaways

  • Analytics and Big Data are critical to understanding and combating the spread of deadly diseases.
  • Domain knowledge and access to data along with an understanding of how to analyze the data are key drivers of positive outcomes.
  • Data science and Alteryx can help you change the world.

Stay Put. 

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Here's another great article highlighting how companies are helping the government respond to COVID-19. 

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