# COvid Post-Exposure Evaluation and Symptomatology (COPES) Center: Identifying Post-COVID Phenotypes and Related Health Inequities

> **NIH VA I01** · VA SALT LAKE CITY HEALTHCARE SYSTEM · 2024 · —

## Abstract

Background: An estimated 10-50% of patients with a history of COVID-19 infection (C+) experience PASC.
PASC presents as a multisystem syndrome, with symptoms ranging in severity and regularity that can last
weeks to months after acute infection. These symptoms can lead to mild to severe functional limitations that
adversely impact quality of life. Emerging evidence suggests that inequities in PASC are experienced
especially by historically underserved populations (as with acute COVID-19). The lack of a standard case
definition risks burdening patients by delaying access to treatment and management. Yet currently there are no
evidence-based practices (EBP) for managing and treating PASC. Efforts to define PASC are urgently needed
to address knowledge gaps, advance discovery of EBPs, and improve care.
Significance: Our long-term goal is to ensure that every Veteran with PASC receives appropriate, timely, and
effective EBP to reduce PASC-related morbidity and maintain Veterans’ quality of life. Since the cumulative
cases of COVID-19 exceed 520,000 in VA, and 146 million in the US, and many are still at risk, our findings will
have broad public health impact within and beyond VA.
Innovation and Impact: VA has a unique opportunity to play a central role in defining PASC by leveraging its
multiple high-quality data sources, such as the COVID-19 Shared Data Resource. PASC definitions can be
derived from: 1) International Classification of Disease diagnosis codes, 2) electronic health record (EHR) chart
review, and 3) Veteran-reported symptom surveys. We propose to integrate these VA data sources and
mechanisms to identify a unified phenotypic description of PASC. Interviews with Veterans and other
stakeholders will further enrich our understanding of PASC. Collectively, these data will address research gaps
in understanding current PASC treatment models and assess variability and inequities in care.
Specific Aims: 1. Define and characterize PASC in the VA C+ population using EHR and survey data.
2. Characterize clinical management strategies and care delivery models for PASC, including pharmacological
and non-pharmacological treatments (e.g., Whole Health, Pain, Rehabilitation). 3. Assess health inequities in
PASC phenotypes, symptom trajectories, and management.
Methodology: In Aim 1 we will identify distinct symptom clusters among C+ Veterans in VA using
unsupervised clustering and examine the consequences of applying different criteria for PASC on estimation of
PASC incidence and on the relationship between PASC and symptom clusters. In Aim 2 we will characterize
clinical management leveraging EHR data and Veterans’ self-care via survey data. We will also conduct key
informant interviews in facilities with high and low C+ prevalence to determine how healthcare teams identify
PASC and select management and care delivery approaches. In Aim 3 we will examine relationships between
Aims 1-2 metrics and social determinants of health. We will also evaluate ...

## Key facts

- **NIH application ID:** 10610797
- **Project number:** 1I01HX003668-01
- **Recipient organization:** VA SALT LAKE CITY HEALTHCARE SYSTEM
- **Principal Investigator:** Sara J Knight
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2024-02-01 → 2028-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10610797

## Citation

> US National Institutes of Health, RePORTER application 10610797, COvid Post-Exposure Evaluation and Symptomatology (COPES) Center: Identifying Post-COVID Phenotypes and Related Health Inequities (1I01HX003668-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10610797. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*