RAPID:Genomic Variation Analysis of Coronavirus to Better Understand the Spread of COVID-19
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2027667
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$124,386Funder
National Science Foundation (NSF)Principal Investigator
Jing LiResearch Location
United States of AmericaLead Research Institution
Case Western Reserve UniversityResearch 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
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Computer and Information Science and Engineering - Currently, there is a world-wide pandemic of the Coronavirus Disease 2019 (COVID-19) that is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of April 2, 2020, there have been more than one million confirmed cases of COVID-19 and more than 55,000 deaths. These numbers are increasing rapidly. Yet, the short time since the beginning of this outbreak limits our understanding of how SARS-CoV-2 spreads. The objective of this project is to address this gap. In response to evidence that the rate of infections among healthcare providers is alarmingly high, this project will expose transmission patterns in the hospital setting. In collaboration with the Cleveland Clinic, the investigators will have access to genomic, epidemiological, and clinical patient data. Joint computational analysis of this data will result in a computational model that will provide insights into transmission patterns in hospitals, such as from patients to doctors and health workers, or from doctors to doctors.
The activities in this project will be organized along three Aims. Aim 1: Perform whole-genome sequencing of SARS-CoV-2 samples collected at the Cleveland Clinic. The data will be augmented by existing SARS-CoV-2 sequence data from multiple online databases, as well as existing sequence data from other species. Aim 2: Build an analysis pipeline and perform evolutionary analysis of genomic data obtained in Aim 1. Aim 3: Perform joint analysis of genomic, epidemiological, and clinical data to infer transmission patterns. One of the unique advantages of the project is the ability to directly link identified genomic strains to clinical data. The activities have direct clinical implications for better protecting healthcare workers and minimizing the overall rate of infections in the hospital setting. Findings from this project will be shared with the research community at large to aid further analysis in other hospitals as more data becomes available during this pandemic.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
The activities in this project will be organized along three Aims. Aim 1: Perform whole-genome sequencing of SARS-CoV-2 samples collected at the Cleveland Clinic. The data will be augmented by existing SARS-CoV-2 sequence data from multiple online databases, as well as existing sequence data from other species. Aim 2: Build an analysis pipeline and perform evolutionary analysis of genomic data obtained in Aim 1. Aim 3: Perform joint analysis of genomic, epidemiological, and clinical data to infer transmission patterns. One of the unique advantages of the project is the ability to directly link identified genomic strains to clinical data. The activities have direct clinical implications for better protecting healthcare workers and minimizing the overall rate of infections in the hospital setting. Findings from this project will be shared with the research community at large to aid further analysis in other hospitals as more data becomes available during this pandemic.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.