Identifying SARS-COV-2 infected patients through canine olfactive detection on axillary sweat samples; study of observed sensitivities and specificities within a group of trained dogs - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue PLoS ONE Année : 2022

Identifying SARS-COV-2 infected patients through canine olfactive detection on axillary sweat samples; study of observed sensitivities and specificities within a group of trained dogs

Dominique Grandjean
Capucine Gallet
  • Fonction : Auteur
Clothilde Julien
  • Fonction : Auteur
Riad Sarkis
  • Fonction : Auteur
Quentin Muzzin
  • Fonction : Auteur
Vinciane Roger
  • Fonction : Auteur
Didier Roisse
  • Fonction : Auteur
Nicolas Dirn
  • Fonction : Auteur
Clement Levert
  • Fonction : Auteur
Erwan Breton
  • Fonction : Auteur
Arnaud Galtat
  • Fonction : Auteur
Alexandre Forget
  • Fonction : Auteur
Sebastien Charreaudeau
  • Fonction : Auteur
Fabien Gasmi
  • Fonction : Auteur
Caroline Jean-Baptiste
  • Fonction : Auteur
Sebastien Petitjean
  • Fonction : Auteur
Katia Hamon
  • Fonction : Auteur
Jean-Michel Duquesne
  • Fonction : Auteur
Chantal Coudert
  • Fonction : Auteur
Jean-Pierre Tourtier
  • Fonction : Auteur
Christophe Billy
  • Fonction : Auteur
Jean-Marc Wurtz
  • Fonction : Auteur
Anthony Chauvin
  • Fonction : Auteur
Xavier Eyer
  • Fonction : Auteur
Sabrina Ziani
  • Fonction : Auteur
Laura Prevel
  • Fonction : Auteur
Ilaria Cherubini
  • Fonction : Auteur
Enfel Khelili-Houas
  • Fonction : Auteur
Pierre Hausfater
  • Fonction : Auteur
Loic Desquilbet

Résumé

There is an increasing need for rapid, reliable, non-invasive, and inexpensive mass testing methods as the global COVID-19 pandemic continues. Detection dogs could be a possible solution to identify individuals infected with SARS-CoV-2. Previous studies have shown that dogs can detect SARS-CoV-2 on sweat samples. This study aims to establish the dogs’ sensitivity (true positive rate) which measures the proportion of people with COVID-19 that are correctly identified, and specificity (true negative rate) which measures the proportion of people without COVID-19 that are correctly identified. Seven search and rescue dogs were tested using a total of 218 axillary sweat samples (62 positive and 156 negative) in olfaction cones following a randomised and double-blind protocol. Sensitivity ranged from 87% to 94%, and specificity ranged from 78% to 92%, with four dogs over 90%. These results were used to calculate the positive predictive value and negative predictive value for each dog for different infection probabilities (how likely it is for an individual to be SARS-CoV-2 positive), ranging from 10–50%. These results were compared with a reference diagnostic tool which has 95% specificity and sensitivity. Negative predictive values for six dogs ranged from ≥98% at 10% infection probability to ≥88% at 50% infection probability compared with the reference tool which ranged from 99% to 95%. Positive predictive values ranged from ≥40% at 10% infection probability to ≥80% at 50% infection probability compared with the reference tool which ranged from 68% to 95%. This study confirms previous results, suggesting that dogs could play an important role in mass-testing situations. Future challenges include optimal training methods and standardisation for large numbers of detection dogs and infrastructure supporting their deployment.

Dates et versions

hal-04260534 , version 1 (26-10-2023)

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Dominique Grandjean, Capucine Gallet, Clothilde Julien, Riad Sarkis, Quentin Muzzin, et al.. Identifying SARS-COV-2 infected patients through canine olfactive detection on axillary sweat samples; study of observed sensitivities and specificities within a group of trained dogs. PLoS ONE, 2022, 17 (2), pp.e0262631. ⟨10.1371/journal.pone.0262631⟩. ⟨hal-04260534⟩
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