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Arnold School of Public Health

Chen Liang awarded new grant to better understand COVID-19 – HIV coinfection through data mining and artificial intelligence

August 19, 2022 | Erin Bluvas,

The National Institute of Allergies and Infectious Diseases has awarded more than $400K to Chen Liang, an assistant professor with the Department of Health Services Policy and Management (HSPM), South Carolina SmartState Center for Healthcare Quality (CHQ) and UofSC Big Data Health Science Center. Liang will use the two-year R21 grant to curate a knowledge base for individuals with coinfection of HIV and SARS-CoV-2 by data mining a nationwide electronic health records repository.

“The COVID-19 pandemic has cast a heavy burden on individuals with HIV infection,” Liang says. “A recent report from the World Health Organization confirms that HIV is a risk factor for severe COVID-19.”

Individuals with certain additional comorbidities (e.g., type 2 diabetes, cardiovascular diseases, obesity, cancers) face an increased risk of even worse outcomes. Further, AIDS-related factors such as unsuppressed viral load, low T-cell counts, adherence to antiretroviral therapy, and disruption to treatment and services further complicate the health of co-infected individuals.

With this study, the researchers will use large data sets (i.e., big data) of electronic health records from the National COVID Cohort Collaborative to establish a cohort for individuals with HIV/SARS-CoV-2 coinfection. They will develop and implement innovative machine learning algorithms to identify and validate factors, such as clinical characteristics, demographics and socio-behavioral patterns, that contribute to severe clinical infection.

Next, Liang and his team will pilot test a Clinical Decision Support prototype to help healthcare providers screen and refer at-risk patients. One of their goals is to examine patterns and traits to assess their ability to predict clinical outcomes and disease prognosis. They also plan to develop machine-learning models to explore real-time predictive associations between certain traits and poor clinical outcomes.

“This project will result in a comprehensive knowledge base that provides detailed information about the risk factors of severe clinical outcomes and disease prognosis in individuals with HIV/SARS-CoV-2,” Liang says. “We’re also excited to be able to create a clinical tool for our partners at Prisma Health and the UofSC School of Medicine to help them identify individuals living with HIV at high risk for severe COVID-19 outcomes and provide options for actional clinical decisions to help reduce the likelihood of adverse health outcomes.”


Arnold School faculty to lead five projects with support from Prisma Health Research Seed Grant Program

Chen Liang brings informatics expertise to Department of Health Services Policy and Management

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