Schulich/SEEC faculty helping to track the global spread of COVID-19

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People experience the current pandemic on a local and personal level, but to best understand it, one must observe its behaviour on a global scale.

That’s why a team of data scientists and analysts at Schulich has created a dashboard that predicts the spread of the disease to different regions as it moves across the globe.

The dashboard team consists of Professor Murat Kristal, director of Schulich’s Artificial Intelligence and Business Analytics programs, Ikjyot Singh Kohli, senior data scientist and mathematical physicist, and David Elsner, a visual analytics and modelling instructor. All three are faculty on SEEC’s Masters Certificate in Analytics for Leaders.

Since December when China reported its first cases of COVID-19, more than 1,870,000 novel coronavirus cases have been reported in more than 200 countries worldwide. Accurate reporting on the virus has become a crucial scientific tool for its elimination. The dashboard is updated daily and gives highly accurate readings of the movement and scope of the virus.

“These numbers could help decision makers make informed decisions,” said Kristal. “Even though our five-day accuracy is currently 67 per cent, the one-day accuracy is over 90%. Given how fast things are changing this will be very helpful to them. We also expect the five-day accuracy rate to improve as more data becomes available. The important thing is the order of magnitude and our predictions provide that.”

Currently the data is obtained from sources such as the Johns Hopkins Center for Systems Science and Engineering, and is inputted manually, but the updates will soon be an automated process. For more information about the dashboard, contact Murat Kristal.

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The topic of this article is inspired by the curriculum for the SEEC program Masters Certificate in Analytics for Leaders (starting Sept. 14, 2020). This 13-day program for non-data specialists, is designed to quickly round out your knowledge of all the technical, managerial and organizational dimensions required to generate insights from data and translate them into action.

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