ABSTRACT
The introduction of trained sniffer dogs for COVID-19 detection could be an opportunity, as previously described for other diseases. Dogs could be trained to detect volatile organic compounds (VOCs), the whiff of COVID-19. Dogs involved in the study were three, one male and two females from different breeds, Black German Shepherd, German Shepherd, and Dutch Shepherd. The training was performed using sweat samples from SARS-CoV2 positive patients and from SARS-Cov2 free patients admitted at the University Hospital Campus Bio-medico of Rome. Gauze with sweat was collected in a glass jar with a metal top and put in metal boxes used for dog training. The dog training protocol was performed in two phases: the olfactory conditioning and the olfactory discrimination research. The training planning was focused on the switch moment for the sniffer dog, the moment when the dog was able to identify VOCs specific for COVID-19. At this time, the dog was able to identify VOCs specific for COVID-19 with significant reliability, in terms of the number of correct versus incorrect (p < 0.0001) reporting. In conclusion, this protocol could provide a useful tool for sniffer dogs' training and their introduction in a mass screening context. It could be cheaper and faster than a conventional testing method.
Subject(s)
COVID-19/diagnosis , Learning/physiology , Smell/physiology , Working Dogs/physiology , Animals , COVID-19/pathology , Dogs , Female , Humans , Male , Middle Aged , Reproducibility of Results , SARS-CoV-2/isolation & purification , Sweat/chemistry , Volatile Organic Compounds/analysis , Volatile Organic Compounds/isolation & purificationABSTRACT
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.