Originally published in The Forefront 8/4/2020

The COVID-19 pandemic has mobilized the world’s scientific community like no other recent crisis, including many researchers using the most modern data science and artificial intelligence approaches. At the University of Chicago, public health experts, computer scientists, economists and policy analysts have launched projects using computational tools to better detect, diagnose, treat and prevent the spread of the deadly virus.

This summer, three of these projects received seed funding from the C3.ai Digital Transformation Institute (DTI), a new partnership of technology companies and universities committed to accelerating the benefits of artificial intelligence for business, government and society. The research attacks the pandemic from several angles: helping policymakers control disease spread by identifying and addressing key social factors, physicians detect the disease at earlier stages, and hospitals decide which patients require admission. A fourth project, a collaboration led by UChicago Medicine’s Maryellen Giger, was funded by the organization in spring.

The awards were part of $5.4 million in funding distributed by DTI, after their inaugural call for proposals in March. The group also provides AI software tools and a “data lake” of COVID-19 datasets to aid researchers studying the pandemic.

“The enthusiastic response among scientists and researchers coupled with the diverse, high-quality and compelling proposals we’ve received suggests that we have the potential to alter the course of this global pandemic,” said Thomas M. Siebel, CEO of C3.ai. “In the face of this crisis, the Institute is proud to bring together the best and brightest minds and provide direction and leadership to support objective analysis and AI-based, data-driven science to mitigate COVID-19.”

Modeling health disparities

The early toll of the COVID-19 pandemic revealed severe health inequities in who catches the disease and who suffers death and morbidity. Latin and African Americans are more than three times as likely to catch the virus and twice as likely to die as white Americans, according to CDC data. Many experts believe this disparity goes beyond medical comorbidities, to social determinants such as housing, jobs and neighborhood features.

Anna Hotton, MD, PhD, a research assistant professor at UChicago Medicine, previously studied the relationship between social factors and viral spread in the context of other infectious diseases. With her DTI grant, she’s working with fellow UChicago researchers Aditya Khanna, PhD, Harold Pollack, PhD, and John Schneider, MD, MPH, to adapt that work to COVID-19, with help from agent-based modeling experts Jonathan Ozik and Charles Macal at Argonne National Laboratory.

“A lot of my substantive work focuses around understanding social and structural factors as they impact HIV transmission,” Hotton said. “With COVID-19, there are a lot of similarities in terms of the social factors that shape people’s vulnerability to infection, and I’m motivated to shed light on some of these social issues and help guide work around reducing health inequities.”

Agent-based modeling is a powerful form of computer simulation for studying complex systems, from molecular interactions to traffic congestion. Over the last decade, Argonne researchers Ozik and Macal have gradually assembled a computer model for the entire city of Chicago and its population, using it to observe and predict the spread of diseases both real (MRSA, influenza) and imagined (a zombie outbreak). Recently, the team has focused their ChiSIM model on the spread of COVID-19, looking for types of buildings and areas of the city where people gather and disease transmission risk is high.