Accès ouvert déclaré 2022 article

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

Claire Marie Guest, Sarah Y. Dewhirst, Steve W. Lindsay, David James Allen, Sophie Aziz, Oliver Baerenbold, John D. Bradley, Unnati Chabildas, Vanessa Chen-Hussey, Samuel Clifford, Luke Cottis, Jessica Dennehy, Erin E. B. Foley, Salvador Alejandro Gezan, Tim D. Gibson, Courtenay K Greaves, Immo Kleinschmidt, Sébastien Lambert, Anna R. Last, S. V. Morant, Josephine E. A. Parker, John Anthony Pickett, Billy J. Quilty, Ann Rooney, Manil Shah, Mark H. Somerville, Chelci Squires, Martin Walker, James G. Logan, Robert Thomas Jones, Ana Elisa Spaolonzi Queiroz Assis, Ewan Borthwick, Laura Caton, Rachel Edwards, Janette Heal, David R. Hill, Nazifa Jahan, Cecelia Johnson, Angela Kaye, Emily Rose Kirkpatrick, Sarah Kisha, Zaena Ledeatte Williams, Robert Moar, Tolulope Owonibi, Benjamin Purcell, Christopher Rixson, Freya I Spencer, Anastasios Stefanidis, Sophie Stewart, Scott J. Tytheridge, Sian Wakley, Shanice Wildman, Catherine Aziz, Helen Care, Emily Curtis, Claire Dowse, A.R. Makepeace, Sally-Anne Oultram, Jayde Smith, Fiona C. Shenton, H. B. Hutchins, Robert J. Mart, Jo-Anne Cartwright, Miranda Forsey, Kerry Goodsell, Lauren Kittridge, Anne Nicholson, Angelo Ramos, Joanne Ritches, Niranjan Ananda Setty, Mark Vertue, Malin Bergström, Zain Chaudhary, Angus de Wilton, Kate Gaskell, Catherine F. Houlihan, Imogen Jones, Marios Margaritis, Patricia Miralhes, Leah A. Owens, Tommy Rampling, Hannah Rickman, Marta Boffito, Candida Fernandez, Bryony Cotterell, Anne-Marie Guerdette, Georgios Tsaknis, Margaret Turns, Joanne Walsh, Lisa Frankland, Raha West, Maureen Holland, Natalie Keenan, Helen Wassall, Megan M. Lacy Young, Jade Rangeley, Gwendolyn Saalmink, Sanjay Adlakha, Philip Buckley, Lynne Allsop, Susan Smith, D. Sowter, Alison Campbell, Julie P. Jones, Steve Laird, Sarah E. O'Toole, Courteney Ryan, Jessica Evans, James Rand, Natasha Schumacher, T Hazelton, Andrew R. Dodgson, Susannah Glasgow, Denise Kadiu, Orianne Lopuszansky, Anu Mary Oommen, Joshi Navis Prabhu, Molly Pursell, Jane Turner, H. B. G. Walton, Robert Andrews, Irena Cruickshank, Catherine Thompson, Tania Wainwright, Alun Roebuck, Tara Lawrence, Kimberley Netherton, Claire Hewitt, S Shephardson, Winston Crasto, Judith Lake, Rosemary Musanhu, R J Walker, Karen E. A. Burns, Andrew D. Higham, Julie Le Bas, Nicola Mackenzie, Hilary Thatcher, Shannen Beadle, Sarah Buckley, Gail Castle, Aimee Fletcher, Sara Holbrook, Patricia Kane, Kate Lindley, Tracey Lowry, Stephanie Lupton, Sharon Oddy, Lynda Slater, Martin Sylvester, Kenneth Agwuh, Veronica Maxwell, Stephen Ryder, Kirsty Topham, Obi Egbuniwe, Rebecca L. Matthews, Alejandro Arenas‐Pinto, Paulina Prymas, Abigail Severn, Amber Shaw, Safia Begum, Daniel Lenton, James E. Scriven, Lucy Leeman, Karen Rudge, Emma Storr, Ana Elena Perche Álvarez, Kate Forster, Daniel Hind, Natalie Cook, Rosanna Wai Wan Peeling, Peter E. Carey, Anne V. Wilson, Jane Davis

30Citations signalées, ce qui n’est pas une note de qualité

10Institutions déclarées

4Pays d’affiliation déclarés

Rattachement africain : gb, fr, th, vn. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

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 individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. RESULTS: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95-100) to 100% and specificity from 99% (95% CI 97-100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76-87) to 94% (95% CI 89-98) and specificity ranging from 76% (95% CI 70-82) to 92% (95% CI 88-96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. CONCLUSIONS: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people.Trial Registration NCT04509713 (clinicaltrials.gov).

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref: Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study
Date Crossref: 24/03/2022
Éditeur: Oxford University Press (OUP)
Type: journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

Durham University pays non établi dans la notice
Université ou école supérieure
London School of Hygiene & Tropical Medicine pays non établi dans la notice
Université ou école supérieure
Biology of Infection pays non établi dans la notice
Structure de recherche
MRC Epidemiology Unit pays non établi dans la notice
Structure de recherche
University of London pays non établi dans la notice
Université ou école supérieure
Royal Veterinary College pays non établi dans la notice
Université ou école supérieure
Cardiff University pays non établi dans la notice
Université ou école supérieure
St Helens Hospital pays non établi dans la notice
Établissement de santé
Department of Disease Control pays non établi dans la notice
Organisme public
Hospital for Tropical Diseases pays non établi dans la notice
Établissement de santé
Medical Detection Dogs pays non établi dans la notice
Institution
Arctech Innovation pays non établi dans la notice
Institution

Durham University, London School of Hygiene & Tropical Medicine et Biology of Infection, avec 9 autres affiliations.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Advanced Chemical Sensor TechnologiesOlfactory and Sensory Function StudiesSARS-CoV-2 detection and testing

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