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.

The aim of this study is to evaluate if the sweat produced by COVID-19 persons (SARS-CoV-2 PCR positive) has a different odour for trained detection dogs than the sweat produced by non COVID-19 persons. The study was conducted on 3 sites, following the same protocol procedures, and involved a total of 18 dogs. A total of 198 armpits sweat samples were obtained from different hospitals. For each involved dog, the acquisition of the specific odour of COVID-19 sweat samples required from one to four hours, with an amount of positive samples sniffing ranging from four to ten. For this proof of concept, we kept 8 dogs of the initial group (explosive detection dogs and colon cancer detection dogs), who performed a total of 368 trials, and will include the other dogs in our future studies as their adaptation to samples scenting takes more time.The percentages of success of the dogs to find the positive sample in a line containing several other negative samples or mocks (2 to 6) were 100p100 for 4 dogs, and respectively 83p100, 84p100, 90p100 and 94p100 for the others, all significantly different from the percentage of success that would be obtained by chance alone.We conclude that there is a very high evidence that the armpits sweat odour of COVID-19+ persons is different, and that dogs can detect a person infected by the SARS-CoV-2 virus.

A PCR test of a nasal swab is still the “gold standard” for detecting a SARS-CoV-2 infection. However, PCR testing could be usefully complemented by non-invasive, fast, reliable, cheap methods for detecting infected individuals in busy areas (e.g. airports and railway stations) or remote areas. Detection of the volatile, semivolatile and non-volatile compound signature of SARS-CoV-2 infection by trained sniffer dogs might meet these requirements. Previous studies have shown that well-trained dogs can detect SARS-CoV-2 in sweat, saliva and urine samples. The objective of the present study was to assess the performance of dogs trained to detect the presence of SARS-CoV-2 in axillary-sweat-stained gauzes and on expired breath trapped in surgical masks. The samples were provided by individuals suffering from mild-to-severe coronavirus disease 2019 (COVID-19), asymptomatic individuals, and individuals vaccinated against COVID-19. Results: Seven trained dogs tested on 886 presentations of sweat samples from 241 subjects and detected SARS-CoV-2 with a diagnostic sensitivity (relative to the PCR test result) of 89.6% (95% confidence interval (CI): 86.4-92.2%) and a specificity of 83.9% (95% CI: 80.3-87.0%) - even when people with a low viral load were included in the analysis. When considering the 207 presentations of sweat samples from vaccinated individuals, the sensitivity and specificity were respectively 85.7% (95% CI: 68.5-94.3) and 86.0% (95% CI: 80.2-90.3%). The likelihood of a false-positive result was greater in the two weeks immediately after COVID-19 vaccination. Four of the seven dogs also tested on 262 presentations of mask samples from 98 subjects; the diagnostic sensitivity was 83.1% (95% CI: 73.2-89.9) and the specificity was 88.6% (95% CI: 83.3-92.4%). There was no difference (McNemar's test P=0.999) in the dogs’ abilities to detect the presence of SARS-CoV-2 in paired samples of sweat-stained gauzes vs. surgical masks worn for only 10 minutes. Conclusion: Our findings confirm the promise of SARS-CoV-2 screening by detection dogs and broaden the method’s scope to vaccinated individuals and easy-to-obtain face masks, and suggest that a “dogs + confirmatory rapid antigen detection tests” screening strategy might be worth investigating.

Objectives: Dogs can be trained to identify several substances not detected by humans, corresponding to specific volatile organic compounds (VOCs). The presence of VOCs, triggered by SARS-CoV-2 infection, was tested in sweat from Long COVID patients. Patients and methods: An axillary sweat sample of Long COVID patients and of COVID-19 negative, asymptomatic individuals was taken at home to avoid any hospital contact. Swabs were randomly placed in olfaction detection cones, and the material sniffed by at least 2 trained dogs. Results: Forty-five Long COVID patients, mean age 45 (6-71), 73.3% female, with prolonged symptoms evolving for a mean of 15.2 months (5-22) were tested. Dogs discriminated in a positive way 23/45 (51.1%) Long COVID patients versus 0/188 (0%) control individuals (p<.0001). Conclusion:This study suggests the persistence of a viral infection in some Long COVID patients and the possibility of providing a simple, highly sensitive, non-invasive test to detect viral presence, during acute and extended phases of COVID-19.

Facing the COVID-19 pandemic, testing individuals in order to promptly isolate positive people is one of the key actions. One approach to rapid testing might be to consider the olfactory capacities of trained detection dogs in order to develop a non-invasive, rapid and cheap mass detection approach, through the Volatile Organic Compounds (VOCs) signature of SARS-CoV-2 infection. The goal of this study is to determine the individual values of sensitivity and specificity of trained dogs when performing olfactory detection of COVID-19 on axillary sweat samples. A group of 7 dogs was tested on a total of 218 samples (62 positive and 156 negative), completely unknown to the dogs, following a randomised and double-blinded protocol carried out on olfaction cone line-ups. To ensure a wide olfactory range as close as possible to operational conditions, the samples were retrieved from 13 different sites. Sensitivities vary from 87 to 94p100 for 6 dogs, and are above 90p100 for 3 of them. Only one dog, whose sensitivity was 60p100, was not selected to continue the study and enter the operational stage. Sensitivity results vary from 78 to 92p100, with 6 dogs over 85p100 and 4 over 90p100. Thanks to these results, a virtual approach of Positive and Negative Predilection Values (PPV and NPV) was designed, based on an almost perfect diagnostic tool as reference and for increasing prevalence values of SARS-CoV-2 infection. The studies to come on olfactory detection of COVID-19 by dogs will still face several challenges, but the accumulation of positive and encouraging results suggest that it may play an important part in mass COVID-19 pre-testing situations.