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Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

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Guest, Claire | Dewhirst, Sarah, Y. | Lindsay, Steve, W. | Allen, David, J. | Aziz, Sophie | Baerenbold, Oliver | Bradley, John | Chabildas, Unnati | Chen-Hussey, Vanessa | Clifford, Samuel | Cottis, Luke | Dennehy, Jessica | Foley, Erin | Gezan, Salvador, A. | Gibson, Tim | Greaves, Courtenay, K. | Kleinschmidt, Immo | Lambert, Sébastien | Last, Anna | Morant, Steve | Parker, Josephine, E. A. | Pickett, John | Quilty, Billy, J. | Rooney, Ann | Shah, Manil | Somerville, Mark | Squires, Chelci | Walker, Martin | Logan, James, G.

Edité par CCSD ; Wiley-Blackwell -

International audience. Background: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. Methods: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected

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