Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study
Authors: 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 ,   COVID Dogs Research Team, Jones Robert , Assis Ana , Borthwick Ewan , Caton Laura , Edwards Rachel , Heal Janette , Hill David , Jahan Nazifa , Johnson Cecelia , Kaye Angela , Kirkpatrick Emily , Kisha Sarah , Ledeatte Williams Zaena , Moar Robert , Owonibi Tolulope , Purcell Benjamin , Rixson Christopher , Spencer Freya , Stefanidis Anastasios , Stewart Sophie , Tytheridge Scott , Wakley Sian , Wildman Shanice , Aziz Catherine , Care Helen , Curtis Emily , Dowse Claire , Makepeace Alan , Oultram Sally-Anne , Smith Jayde , Shenton Fiona , Hutchins Harry , Mart Robert , Cartwright Jo-anne , Forsey Miranda , Goodsell Kerry , Kittridge Lauren , Nicholson Anne , Ramos Angelo , Ritches Joanne , Setty Niranjan , Vertue Mark , Bergstrom Malin , Chaudhary Zain , De Wilton Angus , Gaskell Kate , Houlihan Catherine , Jones Imogen , Margaritis Marios , Miralhes Patricia , Owens Leah , Rampling Tommy , Rickman Hannah , Boffito Marta , Fernandez Candida , Cotterell Bryony , Guerdette Anne-Marie , Tsaknis George , Turns Margaret , Walsh Joanne , Frankland Lisa , West Raha , Holland Maureen , Keenan Natalie , Wassall Helen , Young Megan , Rangeley Jade , Saalmink Gwendolyn , Adlakha Sanjay , Buckley Philip , Allsop Lynne , Smith Susan , Sowter Donna , Campbell Alison , Jones Julie , Laird Steve , O’Toole Sarah , Ryan Courteney , Evans Jessica , Rand James , Schumacher Natasha , Hazelton Tracey , Dodgson Andrew , Glasgow Susannah , Kadiu Denise , Lopuszansky Orianne , Oommen Anu , Prabhu Joshi , Pursell Molly , Turner Jane , Walton Hollie , Andrews Robert , Cruickshank Irena , Thompson Catherine , Wainwright Tania , Roebuck Alun , Lawrence Tara , Netherton Kimberley , Hewitt Claire , Shephardson Sarah , Crasto Winston Andrew , Lake Judith , Musanhu Rosemary , Walker Rebecca , Burns Karen , Higham Andrew , Le Bas Julie , Mackenzie Nicola , Thatcher Hilary , Beadle Shannen , Buckley Sarah , Castle Gail , Fletcher Aimee , Holbrook Sara , Kane Patricia , Lindley Kate , Lowry Tracey , Lupton Stephanie , Oddy Sharon , Slater Lynda , Sylvester Martin , Agwuh Kenneth , Maxwell Veronica , Ryder Stephen , Topham Kirsty , Egbuniwe Obi , Matthews Rebecca , Arenas-Pinto Alejandro , Prymas Paulina , Severn Abigail , Shaw Amber , Begum Safia , Lenton Daniel , Scriven James , Leeman Lucy , Rudge Karen , Storr Emma , Alvarez Ana , Forster Kate , Hind Daniel , Cook Natalie , Peeling Rosanna , Carey Peter , Wilson Anne , Davis Jane 
Published: March 2022

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).