Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study
Journal of Travel Medicine, Volume 29, No. 3, Article taac043, Year 2022
Notification
URL copied to clipboard!
Description
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). © 2022 The Author(s) 2022. Published by Oxford University Press on behalf of International Society of Travel Medicine.
Authors & Co-Authors
Dewhirst, Sarah Y.
Unknown Affiliation
Lindsay, Steve W.
United Kingdom, Durham
Durham University
Allen, David James
United Kingdom, London
London School of Hygiene & Tropical Medicine
Baerenbold, Oliver
United Kingdom, London
London School of Hygiene & Tropical Medicine
Bradley, John
United Kingdom, London
London School of Hygiene & Tropical Medicine
Chen-Hussey, Vanessa
Unknown Affiliation
Clifford, Sam
United Kingdom, London
London School of Hygiene & Tropical Medicine
Foley, Erin
Unknown Affiliation
Gezan, Salvador Alejandro
Unknown Affiliation
Gibson, Tim D.
Unknown Affiliation
Kleinschmidt, Immo
United Kingdom, London
London School of Hygiene & Tropical Medicine
Lambert, Sébastien
United Kingdom, London
University of London
Last, Anna R.
United Kingdom, London
London School of Hygiene & Tropical Medicine
Pickett, John Anthony
United Kingdom, Cardiff
Cardiff University
Quilty, Billy J.
United Kingdom, London
London School of Hygiene & Tropical Medicine
Squires, Chelci
Unknown Affiliation
Walker, Martin
United Kingdom, London
University of London
Logan, James G.
United Kingdom, London
London School of Hygiene & Tropical Medicine
Jones, Robert T.
Unknown Affiliation
Assis, Ana Carolina Dantas De
Unknown Affiliation
Kaye, Angela
Unknown Affiliation
Tytheridge, Scott J.
Unknown Affiliation
Shenton, Fiona Cameron
Unknown Affiliation
Hutchins, Harry
Unknown Affiliation
Gaskell, Katherine M.
Unknown Affiliation
Houlihan, Catherine F.
Unknown Affiliation
Margaritis, Marios
Unknown Affiliation
Rampling, Tommy W.
Unknown Affiliation
Rickman, Hannah M.
Unknown Affiliation
Boffito, Marta A.
Unknown Affiliation
Evans, Jessica D.
Unknown Affiliation
Dodgson, Andrew R.
Unknown Affiliation
Wainwright, Tania
Unknown Affiliation
Arenas-Pinto, Alejandro
Unknown Affiliation
Peeling, Rosanna Wai Wan
Unknown Affiliation
Wilson, Anne L.
Unknown Affiliation
Statistics
Citations: 13
Authors: 36
Affiliations: 4
Identifiers
Doi:
10.1093/jtm/taac043
ISSN:
11951982
Research Areas
Disability
Health System And Policy