Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study

Dominique Grandjean, Riad Sarkis, Clothilde Lecoq-Julien, Aymeric Benard, Vinciane Roger, Eric Levesque, Eric Bernes-Luciani, Bruno Maestracci, Pascal Morvan, Eric Gully, David Berceau-Falancourt, Pierre Haufstater, Gregory Herin, Joaquin Cabrera, Quentin Muzzin, Capucine Gallet, Hélène Bacqué, Jean-Marie Broc, Leo Thomas, Anthony Lichaa, Georges Moujaes, Michele Saliba, Aurore Kuhn, Mathilde Galey, Benoit Berthail, Lucien Lapeyre, Anthoni Capelli, Steevens Renault, Karim Bachir, Anthony Kovinger, Eric Comas, Aymeric Stainmesse, Erwan Etienne, Sébastien Voeltzel, Sofiane Mansouri, Marlène Berceau-Falancourt, Aimé Dami, Lary Charlet, Eric Ruau, Mario Issa, Carine Grenet, Christophe Billy, Jean-Pierre Tourtier, Loïc Desquilbet, Dominique Grandjean, Riad Sarkis, Clothilde Lecoq-Julien, Aymeric Benard, Vinciane Roger, Eric Levesque, Eric Bernes-Luciani, Bruno Maestracci, Pascal Morvan, Eric Gully, David Berceau-Falancourt, Pierre Haufstater, Gregory Herin, Joaquin Cabrera, Quentin Muzzin, Capucine Gallet, Hélène Bacqué, Jean-Marie Broc, Leo Thomas, Anthony Lichaa, Georges Moujaes, Michele Saliba, Aurore Kuhn, Mathilde Galey, Benoit Berthail, Lucien Lapeyre, Anthoni Capelli, Steevens Renault, Karim Bachir, Anthony Kovinger, Eric Comas, Aymeric Stainmesse, Erwan Etienne, Sébastien Voeltzel, Sofiane Mansouri, Marlène Berceau-Falancourt, Aimé Dami, Lary Charlet, Eric Ruau, Mario Issa, Carine Grenet, Christophe Billy, Jean-Pierre Tourtier, Loïc Desquilbet

Abstract

The aim of this proof-of-concept study was to evaluate if trained dogs could discriminate between sweat samples from symptomatic COVID-19 positive individuals (SARS-CoV-2 PCR positive) and those from asymptomatic COVID-19 negative individuals. The study was conducted at 2 sites (Paris, France, and Beirut, Lebanon), followed the same training and testing protocols, and involved six detection dogs (three explosive detection dogs, one search and rescue dog, and two colon cancer detection dogs). A total of 177 individuals were recruited for the study (95 symptomatic COVID-19 positive and 82 asymptomatic COVID-19 negative individuals) from five hospitals, and one underarm sweat sample per individual was collected. The dog training sessions lasted between one and three weeks. Once trained, the dog had to mark the COVID-19 positive sample randomly placed behind one of three or four olfactory cones (the other cones contained at least one COVID-19 negative sample and between zero and two mocks). During the testing session, a COVID-19 positive sample could be used up to a maximum of three times for one dog. The dog and its handler were both blinded to the COVID-positive sample location. The success rate per dog (i.e., the number of correct indications divided by the number of trials) ranged from 76% to 100%. The lower bound of the 95% confidence interval of the estimated success rate was most of the time higher than the success rate obtained by chance after removing the number of mocks from calculations. These results provide some evidence that detection dogs may be able to discriminate between sweat samples from symptomatic COVID-19 individuals and those from asymptomatic COVID-19 negative individuals. However, due to the limitations of this proof-of-concept study (including using some COVID-19 samples more than once and potential confounding biases), these results must be confirmed in validation studies.

Conflict of interest statement

DiagNose, Cynopro Detection Dogs, ICTS Europe, Biodesiv SAS, and Mario K9 provided support in the form of salaries for authors. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products associated with this research to declare.

Figures

Fig 1. Individual informed consent form.
Fig 1. Individual informed consent form.
Fig 2. Underarm sampling.
Fig 2. Underarm sampling.
Fig 3. Sampling materials.
Fig 3. Sampling materials.
Fig 4. Anonymous form for each coded…
Fig 4. Anonymous form for each coded sample.
Fig 5. Testing equipment.
Fig 5. Testing equipment.
Fig 6. 4-olfactory cone line-up.
Fig 6. 4-olfactory cone line-up.
Fig 7. A dog marking a cone…
Fig 7. A dog marking a cone on a 4-cone lineup.

References

    1. Hasell J. Testing early, testing late: four countries’ approaches to COVID-19 testing compared. 2020; .
    1. Angle C, Waggoner LP, Ferrando A, Haney P, Passler T. Canine Detection of the Volatilome: A Review of Implications for Pathogen and Disease Detection. Front Vet Sci 2016,3:47 10.3389/fvets.2016.00047
    1. Bijland LR, Bomers MK, Smulders YM. Smelling the diagnosis: a review on the use of scent in diagnosing disease. Neth J Med 2013,71:300–307.
    1. Edwards TL, Brown CM, Schoon A, Cox C, Poling A. Animal olfactory detection of human diseases: Guidelines and systematic review. J Vet Behav 2017,20:59–73.
    1. Pirrone F, Albertini M. Olfactory detection of cancer by trained sniffer dogs: A systematic review of the literature. J Vet Behav 2017,19:105–117.
    1. Williams H, Pembroke A. Sniffer dogs in the melanoma clinic? Lancet 1989,1:734 10.1016/s0140-6736(89)92257-5
    1. McCulloch M, Jezierski T, Broffman M, Hubbard A, Turner K, Janecki T. Diagnostic accuracy of canine scent detection in early- and late-stage lung and breast cancers. Integr Cancer Ther 2006,5:30–39. 10.1177/1534735405285096
    1. Willis CM, Britton LE, Harris R, Wallace J, Guest CM. Volatile organic compounds as biomarkers of bladder cancer: Sensitivity and specificity using trained sniffer dogs. Cancer Biomark 2010,8:145–153. 10.3233/CBM-2011-0208
    1. Willis CM, Church SM, Guest CM, Cook WA, McCarthy N, Bransbury AJ, et al. Olfactory detection of human bladder cancer by dogs: proof of principle study. BMJ 2004,329:712 10.1136/bmj.329.7468.712
    1. Sonoda H, Kohnoe S, Yamazato T, Satoh Y, Morizono G, Shikata K, et al. Colorectal cancer screening with odour material by canine scent detection. Gut 2011,60:814–819. 10.1136/gut.2010.218305
    1. Boedeker E, Friedel G, Walles T. Sniffer dogs as part of a bimodal bionic research approach to develop a lung cancer screening. Interact Cardiovasc Thorac Surg 2012,14:511–515. 10.1093/icvts/ivr070
    1. Buszewski B, Ligor T, Jezierski T, Wenda-Piesik A, Walczak M, Rudnicka J. Identification of volatile lung cancer markers by gas chromatography-mass spectrometry: comparison with discrimination by canines. Anal Bioanal Chem 2012,404:141–146. 10.1007/s00216-012-6102-8
    1. Ehmann R, Boedeker E, Friedrich U, Sagert J, Dippon J, Friedel G, et al. Canine scent detection in the diagnosis of lung cancer: revisiting a puzzling phenomenon. Eur Respir J 2012,39:669–676. 10.1183/09031936.00051711
    1. Bjartell AS. Dogs sniffing urine: a future diagnostic tool or a way to identify new prostate cancer markers? Eur Urol 2011,59:202–203. 10.1016/j.eururo.2010.10.033
    1. Cornu JN, Cancel-Tassin G, Ondet V, Girardet C, Cussenot O. Olfactory detection of prostate cancer by dogs sniffing urine: a step forward in early diagnosis. Eur Urol 2011,59:197–201. 10.1016/j.eururo.2010.10.006
    1. Taverna G, Tidu L, Grizzi F, Torri V, Mandressi A, Sardella P, et al. Olfactory system of highly trained dogs detects prostate cancer in urine samples. J Urol 2015,193:1382–1387. 10.1016/j.juro.2014.09.099
    1. Kitiyakara T, Redmond S, Unwanatham N, Rattanasiri S, Thakkinstian A, Tangtawee P, et al. The detection of hepatocellular carcinoma (HCC) from patients’ breath using canine scent detection: a proof-of-concept study. J Breath Res 2017,11:046002 10.1088/1752-7163/aa7b8e
    1. Pickel D, Manucy GP, Walker DB, Hall SB, Walker JC. Evidence for canine olfactory detection of melanoma. Appl Anim Behav Sci 2004,89:107–116.
    1. Campbell LF, Farmery L, George SM, Farrant PB. Canine olfactory detection of malignant melanoma. BMJ Case Rep 2013,2013 10.1136/bcr-2013-008566
    1. Rooney NJ, Guest CM, Swanson LCM, Morant SV. How effective are trained dogs at alerting their owners to changes in blood glycaemic levels?: Variations in performance of glycaemia alert dogs. PLoS One 2019,14:e0210092 10.1371/journal.pone.0210092
    1. Rooney NJ, Morant S, Guest C. Investigation into the value of trained glycaemia alert dogs to clients with type I diabetes. PLoS One 2013,8:e69921 10.1371/journal.pone.0069921
    1. Wilson C, Morant S, Kane S, Pesterfield C, Guest C, Rooney NJ. An Owner-Independent Investigation of Diabetes Alert Dog Performance. Front Vet Sci 2019,6:91 10.3389/fvets.2019.00091
    1. Kirton A, Winter A, Wirrell E, Snead OC. Seizure response dogs: evaluation of a formal training program. Epilepsy Behav 2008,13:499–504. 10.1016/j.yebeh.2008.05.011
    1. Wallner WE, Ellis TL. Olfactory detection of gypsy moth pheromone and egg masses by domestic canines. Environ Entomol 1976,5:183–186.
    1. Richards KM, Cotton SJ, Sandeman RM. The use of detector dogs in the diagnosis of nematode infections in sheep feces. J Vet Behav 2008,3:25–31.
    1. Guest C, Pinder M, Doggett M, Squires C, Affara M, Kandeh B, et al. Trained dogs identify people with malaria parasites by their odour. Lancet Infect Dis 2019,19:578–580. 10.1016/S1473-3099(19)30220-8
    1. Bomers MK, van Agtmael MA, Luik H, Vandenbroucke-Grauls CM, Smulders YM. A detection dog to identify patients with Clostridium difficile infection during a hospital outbreak. J Infect 2014,69:456–461. 10.1016/j.jinf.2014.05.017
    1. Maurer M, McCulloch M, Willey AM, Hirsch W, Dewey D. Detection of Bacteriuria by Canine Olfaction. Open Forum Infect Dis 2016,3:ofw051. 10.1093/ofid/ofw051
    1. Angle TC, Passler T, Waggoner PL, Fischer TD, Rogers B, Galik PK, et al. Real-Time Detection of a Virus Using Detection Dogs. Front Vet Sci 2016,2:1–6. 10.3389/fvets.2015.00079
    1. Elliker KR, Sommerville BA, Broom DM, Neal DE, Armstrong S, Williams HC. Key considerations for the experimental training and evaluation of cancer odour detection dogs: lessons learnt from a double-blind, controlled trial of prostate cancer detection. BMC Urol 2014,14:22 10.1186/1471-2490-14-22
    1. Johnen D, Heuwieser W, Fischer-Tenhagen C. An approach to identify bias in scent detection dog testing. Appl Anim Behav Sci 2017,189:1–12.
    1. Jendrny P, Schulz C, Twele F, Meller S, von Kockritz-Blickwede M, Osterhaus A, et al. Scent dog identification of samples from COVID-19 patients—a pilot study. BMC Infect Dis 2020,20:536 10.1186/s12879-020-05281-3
    1. Amann A, Costello Bde L, Miekisch W, Schubert J, Buszewski B, Pleil J, et al. The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. J Breath Res 2014,8:034001 10.1088/1752-7155/8/3/034001
    1. Grabowska-Polanowska B, Miarka P, Skowron M, Sulowicz J, Wojtyna K, Moskal K, et al. Development of sampling method and chromatographic analysis of volatile organic compounds emitted from human skin. Bioanalysis 2017,9:1465–1475. 10.4155/bio-2017-0128
    1. Wysocki CJ, Preti G. Facts, fallacies, fears, and frustrations with human pheromones. Anat Rec A Discov Mol Cell Evol Biol 2004,281:1201–1211. 10.1002/ar.a.20125
    1. Troccaz M, Starkenmann C, Niclass Y, van de Waal M, Clark AJ. 3-Methyl-3-sulfanylhexan-1-ol as a major descriptor for the human axilla-sweat odour profile. Chem Biodivers 2004,1:1022–1035. 10.1002/cbdv.200490077
    1. Hasegawa Y, Yabuki M, Matsukane M. Identification of new odoriferous compounds in human axillary sweat. Chem Biodivers 2004,1:2042–2050. 10.1002/cbdv.200490157
    1. Zeng XN, Leyden JJ, Lawley HJ, Sawano K, Nohara I, Preti G. Analysis of characteristic odors from human male axillae. J Chem Ecol 1991,17:1469–1492. 10.1007/BF00983777
    1. Zeng XN, Leyden JJ, Spielman AI, Preti G. Analysis of characteristic human female axillary odors: Qualitative comparison to males. J Chem Ecol 1996,22:237–257. 10.1007/BF02055096
    1. Bernier UR, Kline DL, Barnard DR, Schreck CE, Yost RA. Analysis of human skin emanations by gas chromatography/mass spectrometry. 2. Identification of volatile compounds that are candidate attractants for the yellow fever mosquito (Aedes aegypti). Anal Chem 2000,72:747–756. 10.1021/ac990963k
    1. Taylor NA, Machado-Moreira CA. Regional variations in transepidermal water loss, eccrine sweat gland density, sweat secretion rates and electrolyte composition in resting and exercising humans. Extrem Physiol Med 2013,2:4 10.1186/2046-7648-2-4
    1. Murota H, Matsui S, Ono E, Kijima A, Kikuta J, Ishii M, et al. Sweat, the driving force behind normal skin: an emerging perspective on functional biology and regulatory mechanisms. J Dermatol Sci 2015,77:3–10. 10.1016/j.jdermsci.2014.08.011
    1. Walczak M, Jezierski T, Górecka-Bruzda A, Sobczyńska M, Ensminger J. Impact of individual training parameters and manner of taking breath odor samples on the reliability of canines as cancer screeners. J Vet Behav 2012,7:283–294.
    1. Lippi G, Cervellin G. Canine olfactory detection of cancer versus laboratory testing: myth or opportunity? Clin Chem Lab Med 2012,50:435–439. 10.1515/CCLM.2011.672
    1. Woidtke L, Dressler J, Babian C. Individual human scent as a forensic identifier using mantrailing. Forensic Sci Int 2018,282:111–121. 10.1016/j.forsciint.2017.11.021
    1. Propper RE. Is sweat a possible route of transmission of SARS-CoV-2? Exp Biol Med (Maywood) 2020,245:997–998.
    1. Sit THC, Brackman CJ, Ip SM, Tam KWS, Law PYT, To EMW, et al. Infection of dogs with SARS-CoV-2. Nature 2020. 10.1038/s41586-020-2334-5
    1. IDEXX. SARS-CoV-2 (COVID-19) RealPCR Test. .
    1. Temmam S, Barbarino A, Maso D, Behillil S, Enouf V, Huon C, et al. Absence of SARS-CoV-2 infection in cats and dogs in close contact with a cluster of COVID-19 patients in a veterinary campus. BioRxiv 2020:2020.2004.2007.029090.
    1. Centers for Disease Control and Prevention. COVID-19 and Animals. 2020 [updated June 22, 2020]; .
    1. Lai MY, Cheng PK, Lim WW. Survival of severe acute respiratory syndrome coronavirus. Clin Infect Dis 2005,41:e67–71. 10.1086/433186
    1. Ren SY, Wang WB, Hao YG, Zhang HR, Wang ZC, Chen YL, et al. Stability and infectivity of coronaviruses in inanimate environments. World J Clin Cases 2020,8:1391–1399. 10.12998/wjcc.v8.i8.1391
    1. Brown LD, Cai TT, DasGupta A. Interval Estimation for a Binomial Proportion. Stat Sci 2001,16:101–117.
    1. Xiao AT, Tong YX, Zhang S. False negative of RT-PCR and prolonged nucleic acid conversion in COVID-19: Rather than recurrence. J Med Virol 2020. 10.1002/jmv.25855
    1. Li Y, Yao L, Li J, Chen L, Song Y, Cai Z, et al. Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19. J Med Virol 2020,92:903–908. 10.1002/jmv.25786
    1. Tahamtan A, Ardebili A. Real-time RT-PCR in COVID-19 detection: issues affecting the results. Expert Rev Mol Diagn 2020,20:453–454. 10.1080/14737159.2020.1757437
    1. Venter M, Richter K. Towards effective diagnostic assays for COVID-19: a review. J Clin Pathol 2020,73:370–377. 10.1136/jclinpath-2020-206685
    1. Concha A, Mills DS, Feugier A, Zulch H, Guest C, Harris R, et al. Using sniffing behavior to differentiate true negative from false negative responses in trained scent-detection dogs. Chem Senses 2014,39:749–754. 10.1093/chemse/bju045
    1. Williams M, Johnston JM. Training and maintaining the performance of dogs (Canis familiaris) on an increasing number of odor discriminations in a controlled setting. Appl Anim Behav Sci 2002,78:55–65.
    1. Haze S, Gozu Y, Nakamura S, Kohno Y, Sawano K, Ohta H, et al. 2-Nonenal newly found in human body odor tends to increase with aging. J Invest Dermatol 2001,116:520–524. 10.1046/j.0022-202x.2001.01287.x
    1. Chen D, Haviland-Jones J. Human olfactory communication of emotion. Percept Mot Skills 2000,91:771–781. 10.2466/pms.2000.91.3.771
    1. Mitro S, Gordon AR, Olsson MJ, Lundstrom JN. The smell of age: perception and discrimination of body odors of different ages. PLoS One 2012,7:e38110 10.1371/journal.pone.0038110

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