CHICAGO (WBBM NEWSRADIO) -- Researchers at DePaul University are helping the city of Chicago collect more accurate demographic information when it comes to COVID-19 tests.
DePaul said by crunching the data, the researchers were able to bring down the category of “unknown” race in COVID-19 tests in Chicago from 47% to 11%.
DePaul's Center for Community Health Equity said this information is essential for understanding inequities with COVID-19, noting that this has been a local and national issue since the onset of the pandemic.
“Everyone is struggling with missing data, but from what is already available, we know that the burden has been carried in disproportionate ways by minoritized and marginalized communities” said Fernando De Maio, professor of sociology and founding co-director of the Center for Community Health Equity at DePaul.
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DePaul also says deep racial segregation in Chicago neighborhoods is part of what made the predictive analytics possible, saying that using someone’s last name and their address can predict their race and ethnicity with a very high degree of accuracy.
When the Chicago Department of Public Health put out a call for assistance with this problem in April, faculty in DePaul’s College of Computing and Digital Media volunteered to help. Data science professor Daniela Stan Raicu and her research team at the Center for Data Science used an algorithm to analyze U.S. census data and available demographic information.
They are able to predict an individual in Chicago’s race and ethnicity with 81% accuracy, according to Raicu. The team also developed a mobile application that allows city officials to easily and securely input the data with missing values, the university said.
“This was our way to help during the pandemic,” said Raicu, who also serves as associate provost for research at DePaul.