Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples
| Autor: | Kelley Hall, Lourdes Edlin, John Mills, DeEtta K. Mills, Denise Webb, Kelvin Frank, Julian Mendel, Howard Holness, Kenneth G. Furton |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
K5000-5582 Coronavirus disease 2019 (COVID-19) Hospitalized patients business.industry Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Outbreak COVID-19 Predictive value Pathology and Forensic Medicine Criminal law and procedure Coronavirus Scent discriminating canines Odor Emergency medicine medicine Interdisciplinary Forensics Volatile organic compounds Gas chromatography–mass spectrometry business Law Shut down |
| Zdroj: | Forensic Science International: Synergy Forensic Science International: Synergy, Vol 3, Iss, Pp 100155-(2021) |
| ISSN: | 2589-871X |
| Popis: | The novel coronavirus SARS-CoV-2, since its initial outbreak in Wuhan, China has led to a worldwide pandemic and has shut down nations. As with any outbreak, there is a general strategy of detection, containment, treatment and/or cure. The authors would argue that rapid and efficient detection is critical and required to successful management of a disease. The current study explores and successfully demonstrates the use of canines to detect COVID-19 disease in exhaled breath. The intended use was to detect the odor of COVID-19 on contaminated surfaces inferring recent deposition of infectious material from a COVID-19 positive individual. Using masks obtained from hospitalized patients that tested positive for COVID-19 disease, four canines were trained and evaluated for their ability to detect the disease. All four canines obtained an accuracy >90% and positive predictive values ranging from ~73 to 93% after just one month of training. |
| Databáze: | OpenAIRE |
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