EAGER: Breath-Based Early and Fast Detection of COVID-19 Infection
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$199,359Funder
National Science Foundation (NSF)Principal Investigator
Pelagia GoumaResearch Location
United States of AmericaLead Research Institution
Ohio State UniversityResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Diagnostics
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Unspecified
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Abstract
The aim of this research project is to enable early and rapid detection of infection COVID-19 by sampling human breath. COVID-19 disease is a pandemic currently, according to the World Health Organization (WHO) caused by the 2019-nCoV virus. Without innate immunity to the novel virus and with the lack of therapeutic means to treat it, the only way to contain the spread of this disease further is through early diagnosis. However, for many infected individuals the disease remains asymptomatic, yet they can potentially transmit COVID-19 and unknowingly infect more of the population. This project will lead to new approach to diagnose COVID-19 infection from sampling human breath.
The investigator proposes to use a disruptive approach to infectious disease diagnosis and to the detection of COVID-19 specifically. This approach involves sampling the breath of human-- or animal in the proposed work-- subjects for three gaseous signaling metabolites (i.e. COVID-19 biomarkers). The hypothesis of the project is that the magnitude of the relative change in these biomarkers upon the subject?s infection with the 2019-nCoV virus provides an early and distinct signal of this infection. The PI will test this hypotheses by producing a three-sensor array, utilizing selective resistive gas sensors based on binary metal oxides, and by testing the breath of swine infected by a beta-coronavirus as well as the breath of humans infected by COVID-19. Measurements will be made repeatedly on definitively or potentially infected subjects to map the rise and fall of the biomarkers over time. Correlating the measurements made with the relative concentration of pro-inflammatory cytokines released in them is expected to produce a diagnostic tool for the pandemic infection. The diagnostic prototype tool will be equipped with wireless capability for rapid deployment as point-of-care, early detection means. The proposed research and technology aim to set the stage for the diagnostics of the future. Establishing the pathway for the effective diagnosis of coronavirus diseases through biomarker monitoring and establishing the specifications required for the early detection of COVID-19 before any symptoms appear are expected to be the major outcomes of the proposed research. Promoting breath analysis as a first response, on-site, point-of-care, personalized diagnostics method is envisioned. Training students working on this project on interdisciplinary research is an added benefit of this research project.
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 aim of this research project is to enable early and rapid detection of infection COVID-19 by sampling human breath. COVID-19 disease is a pandemic currently, according to the World Health Organization (WHO) caused by the 2019-nCoV virus. Without innate immunity to the novel virus and with the lack of therapeutic means to treat it, the only way to contain the spread of this disease further is through early diagnosis. However, for many infected individuals the disease remains asymptomatic, yet they can potentially transmit COVID-19 and unknowingly infect more of the population. This project will lead to new approach to diagnose COVID-19 infection from sampling human breath.
The investigator proposes to use a disruptive approach to infectious disease diagnosis and to the detection of COVID-19 specifically. This approach involves sampling the breath of human-- or animal in the proposed work-- subjects for three gaseous signaling metabolites (i.e. COVID-19 biomarkers). The hypothesis of the project is that the magnitude of the relative change in these biomarkers upon the subject?s infection with the 2019-nCoV virus provides an early and distinct signal of this infection. The PI will test this hypotheses by producing a three-sensor array, utilizing selective resistive gas sensors based on binary metal oxides, and by testing the breath of swine infected by a beta-coronavirus as well as the breath of humans infected by COVID-19. Measurements will be made repeatedly on definitively or potentially infected subjects to map the rise and fall of the biomarkers over time. Correlating the measurements made with the relative concentration of pro-inflammatory cytokines released in them is expected to produce a diagnostic tool for the pandemic infection. The diagnostic prototype tool will be equipped with wireless capability for rapid deployment as point-of-care, early detection means. The proposed research and technology aim to set the stage for the diagnostics of the future. Establishing the pathway for the effective diagnosis of coronavirus diseases through biomarker monitoring and establishing the specifications required for the early detection of COVID-19 before any symptoms appear are expected to be the major outcomes of the proposed research. Promoting breath analysis as a first response, on-site, point-of-care, personalized diagnostics method is envisioned. Training students working on this project on interdisciplinary research is an added benefit of this research project.
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.