Title: | Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples |
Author(s): | Mendel J; Frank K; Edlin L; Hall K; Webb D; Mills J; Holness HK; Furton KG; Mills D; |
Address: | "Department of Biological Sciences, Florida International University, OE 167, 11200 SW 8th Street, Miami, FL, 33199, USA. Department of Chemistry and Biochemistry, Florida International University, CP 302, 11200 SW 8th Street, Miami, FL, 33199, USA. International Forensic Research Institute, Florida International University, OE 116, 11200 SW 8th Street, Miami, FL, 33199, USA. Innovative Detection Concepts, 22290 SW 266th St, Homestead, FL, 33031, USA" |
DOI: | 10.1016/j.fsisyn.2021.100155 |
ISSN/ISBN: | 2589-871X (Electronic) 2589-871X (Linking) |
Abstract: | "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" |
Keywords: | Covid-19 Coronavirus Scent discriminating canines Volatile organic compounds; |
Notes: | "PubMed-not-MEDLINEMendel, Julian Frank, Kelvin Edlin, Lourdes Hall, Kelley Webb, Denise Mills, John Holness, Howard K Furton, Kenneth G Mills, DeEtta eng Netherlands 2021/06/16 Forensic Sci Int Synerg. 2021; 3:100155. doi: 10.1016/j.fsisyn.2021.100155. Epub 2021 Jun 9" |