# Data Disparities Supplement to Johns Hopkins Institute for Clinical and Translational Research

> **NIH NIH UL1** · JOHNS HOPKINS UNIVERSITY · 2020 · $492,704

## Abstract

The SARS-CoV-2 coronavirus, which causes a respiratory illness known as Coronavirus Disease 2019
(COVID-19), has caused a global pandemic of unprecedented proportion. As of April 28, 2020, there were over
3 million confirmed COVID-19 cases worldwide, including over 1 million cases within the United States. In
addition, there has been over 213,000 COVID-19 related deaths globally, including 57,000 deaths in the United
States. The COVID-19 pandemic is disproportionately impacting racial/ethnic minority communities, as well as
those who face socioeconomic disadvantage. Reasons for this disproportionate impact among racial/ethnic
minorities include a greater burden of the chronic health conditions that place persons at risk of severe disease
and death from COVID-19, poorer access to primary and specialty care, an increased risk of contracting
COVID-19 due to barriers to practicing social distancing behaviors, and shortages of testing resources in
disadvantaged communities. This pandemic has presented unprecedented needs for timely access to health-
related data. The State of Maryland and surrounding regions including the District of Columbia are fortunate to
have a well-functioning health information exchange, CRISP. During the COVID-19 pandemic, CRISP data
have the potential to serve an essential function in tracking and understanding the care and outcomes of
COVID-19 infections. This resource would be unique among COVID registries in that it includes all health
events and findings among the entire population of a geographic area, regardless where a health service was
delivered. As such, it is ideally suited to address questions of health disparities. The Specific Aims of this
administrative supplement are to (1) develop the CRISP data resource as a unique, population-based COVID-
19 registry on the highly secure Johns Hopkins Precision Medicine Analytics Platform, and (2) evaluate
COVID-19 care and outcomes by race, neighborhood and socioeconomic status such that targeted strategies
can be deployed to reduce emerging disparities.

## Key facts

- **NIH application ID:** 10158718
- **Project number:** 3UL1TR003098-02S2
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Daniel Ernest Ford
- **Activity code:** UL1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $492,704
- **Award type:** 3
- **Project period:** 2020-05-05 → 2021-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10158718

## Citation

> US National Institutes of Health, RePORTER application 10158718, Data Disparities Supplement to Johns Hopkins Institute for Clinical and Translational Research (3UL1TR003098-02S2). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10158718. Licensed CC0.

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