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University of Dayton Mechanical Engineering Researchers Develop Reliable Predictive COVID-19 Model with 95% Accuracy Rating

By Morgan Brewster, marketing communications intern

At the University of Dayton School of Engineering during the fall 2020 semester, graduate student, Taylor Zehring, had the opportunity to research COVID-19 public policies and prediction factors for his Case Study in Engineering Management. With the help of Dr. Kevin Hallinan, professor, Department of Mechanical and Aerospace Engineering, Zehring was able to develop a reliable predictive model for COVID-19 with a 95% accuracy rating. 

Zehring gathered over 1.5 million data points from public health experts and policies from across the globe, including the World Health Organization (WHO), Johns Hopkins University, the National Institute of Health (NIH) and the Center for Disease Control (CDC). 

Zehring’s motivation was to help communicate the importance and scientific accuracy of the COVID-19 policies being put into place throughout the past year. “Engineers, scientists and medical professionals often fail to communicate in a manner that the general public can fully understand,” Zehring explains. “We were able not only to make a considerable leap into utilizing modern technologies in the medical field but also to bridge the divide between conveying medical discovery and policy to the public.”

After the model was built, Zehring and Hallinan were able to try many different scenarios to predict the different possible outcomes of COVID-19. The results of the experiment indicated that the public policies put in place, including wearing a mask, social distancing and limiting gatherings, are effective. 

“I have always had a passion surrounding machine learning and artificial intelligence,” says Zehring. “My hope is that in this work, we are honoring all those who have lost so much to this pandemic through doing our part as engineers and researchers in an ethical, sustainable and data-based way.”

For more in-depth information, view Zehring's LinkedIn presentation here: https://www.linkedin.com/feed/update/urn:li:activity:6739187315308052480/

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