# Curating a Knowledge Base for Individuals with Coinfection of HIV and SARS-CoV-2: EHR-based Data Mining

> **NIH NIH R21** · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2022 · $222,943

## Abstract

PROJECT SUMMARY
The COVID-19 pandemic has cast a heavy burden on individuals with HIV infection. Based on data of 15,522
hospitalized patients with the coinfection of HIV and SARS-CoV-2 from 24 countries, a recent World Health
Organization (WHO) report for the first time confirmed that HIV to be an independent risk factor for severe
COVID-19. Despite a generally high risk of severe COVID-19 clinical course in individuals with HIV, the
interactions between SARS-CoV-2 and HIV infections remain unclear. For example, the severity of COVID-19 in
individuals with HIV is correlated with certain comorbidities in which some of these comorbidities are more
prevalent in patients with HIV than other populations. Yet, several contradictory findings suggested the
predominant role of comorbidities in the severity of COVID-19 regardless of HIV infection. Individuals with low
CD4+ T-cell count (e.g., <200~500 cells/µL) and unsuppressed viral load are associated with severe clinical
course, yet the role of antiretroviral therapy (ART) exposure and adherence in the context of COVID-19 exposure
needs to be examined. Risk factors for the severe clinical course of the coinfection are undetermined because
individuals with the same or similar severity level of COVID-19 show different clinical characteristics. To fill
address these knowledge gaps, this study will establish an EHR-based cohort for individuals with HIV/SARS-
CoV-2 coinfection and develop large-scale EHR-based data mining to examine the interactions between HIV and
SARS-CoV-2 infections and systematically identify and validate factors contributing to the severe clinical course
of the coinfection. Ultimately, collected clinical evidence will be implemented and used to pilot test a Clinical
Decision Support (CDS) prototype to assist providers in screening and referral of at-risk patients in real-world
clinics.

## Key facts

- **NIH application ID:** 10481286
- **Project number:** 1R21AI170171-01
- **Recipient organization:** UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
- **Principal Investigator:** Xiaoming Li
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $222,943
- **Award type:** 1
- **Project period:** 2022-07-13 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10481286

## Citation

> US National Institutes of Health, RePORTER application 10481286, Curating a Knowledge Base for Individuals with Coinfection of HIV and SARS-CoV-2: EHR-based Data Mining (1R21AI170171-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10481286. Licensed CC0.

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