Health Disparities and SARS-COV-2 Evolution: A Focused Viral Genomics Study
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3U54GM104940-06S2
Grant search
Key facts
Disease
COVID-19Start & end year
20122022Known Financial Commitments (USD)
$737,607Funder
National Institutes of Health (NIH)Principal Investigator
John P KirwanResearch Location
United States of AmericaLead Research Institution
N/AResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Pathogen genomics, mutations and adaptations
Special Interest Tags
Data Management and Data Sharing
Study Type
Clinical
Clinical Trial Details
Unspecified
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Minority communities unspecified
Occupations of Interest
Unspecified
Abstract
Health Disparities and SARS-CoV-2 Evolution: A Focused Viral Genomics Study Project Summary/Abstract We hypothesize that prolonged COVID19 illness, re-infection, and/or post-vaccine infection in patients with chronic conditions are associated with specific SARS-CoV-2 lineages or mutations, and that increasing the awareness of the potential danger posed by variants of concern will improve testing adherence and variant tracking. We propose to use our established FDA- authorized COVID19 sequencing platform in combination with innovative data analytics and clinical bioinformatics as well as our BMI and community engagement KCAs. Our proposal addresses four of the priority areas indicated by NOT-GM-21-031, specifically: • Are there different variants present in the study population, and how has the number of cases caused by different variants changed over time in the study population? • How are different variants distributed among different racial, ethnical, gender, and/or age groups? • Are specific variants associated with different levels of manifestation of COVID19 symptoms? • Do vaccinated study participants still acquire the SARS-CoV-2 virus, and if so, what variants do they carry? We propose these Specific Aims: Specific Aim 1. To improve surveillance of COVID19 by integrating SARS-CoV-2 sequencing and clinical data with a focus on under-represented, vulnerable and remote populations. Using highly automated processes, we will identify variants/mutations associated with clinical phenotypes, including prolonged asymptomatic/antibody-positive individuals, re-infected, and vaccinated populations. All trend data will be integrated in the AWS cloud where it can be accessed by relevant stakeholders including testing and vaccine program partners. Specific Aim 2. To develop and validate simulation models that incorporate SARS-CoV-2 genetic data with clinical outcomes to predict COVID19 case severity in Louisiana by region as vaccination levels increase. Specific Aim 3. To design and deploy culturally and linguistically appropriate outreach material on SARS-CoV-2 and determine whether increased knowledge of the potential danger of adaptive mutations improves acceptance of testing and vaccination.