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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

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...

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Autores principales: Grandjean, Dominique, Gallet, Capucine, Julien, Clothilde, Sarkis, Riad, Muzzin, Quentin, Roger, Vinciane, Roisse, Didier, Dirn, Nicolas, Levert, Clement, Breton, Erwan, Galtat, Arnaud, Forget, Alexandre, Charreaudeau, Sebastien, Gasmi, Fabien, Jean-Baptiste, Caroline, Petitjean, Sebastien, Hamon, Katia, Duquesne, Jean-Michel, Coudert, Chantal, Tourtier, Jean-Pierre, Billy, Christophe, Wurtz, Jean-Marc, Chauvin, Anthony, Eyer, Xavier, Ziani, Sabrina, Prevel, Laura, Cherubini, Ilaria, Khelili-Houas, Enfel, Hausfater, Pierre, Devillier, Philippe, Desquilbet, Loic
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8843128/
https://www.ncbi.nlm.nih.gov/pubmed/35157716
http://dx.doi.org/10.1371/journal.pone.0262631
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author Grandjean, Dominique
Gallet, Capucine
Julien, Clothilde
Sarkis, Riad
Muzzin, Quentin
Roger, Vinciane
Roisse, Didier
Dirn, Nicolas
Levert, Clement
Breton, Erwan
Galtat, Arnaud
Forget, Alexandre
Charreaudeau, Sebastien
Gasmi, Fabien
Jean-Baptiste, Caroline
Petitjean, Sebastien
Hamon, Katia
Duquesne, Jean-Michel
Coudert, Chantal
Tourtier, Jean-Pierre
Billy, Christophe
Wurtz, Jean-Marc
Chauvin, Anthony
Eyer, Xavier
Ziani, Sabrina
Prevel, Laura
Cherubini, Ilaria
Khelili-Houas, Enfel
Hausfater, Pierre
Devillier, Philippe
Desquilbet, Loic
author_facet Grandjean, Dominique
Gallet, Capucine
Julien, Clothilde
Sarkis, Riad
Muzzin, Quentin
Roger, Vinciane
Roisse, Didier
Dirn, Nicolas
Levert, Clement
Breton, Erwan
Galtat, Arnaud
Forget, Alexandre
Charreaudeau, Sebastien
Gasmi, Fabien
Jean-Baptiste, Caroline
Petitjean, Sebastien
Hamon, Katia
Duquesne, Jean-Michel
Coudert, Chantal
Tourtier, Jean-Pierre
Billy, Christophe
Wurtz, Jean-Marc
Chauvin, Anthony
Eyer, Xavier
Ziani, Sabrina
Prevel, Laura
Cherubini, Ilaria
Khelili-Houas, Enfel
Hausfater, Pierre
Devillier, Philippe
Desquilbet, Loic
author_sort Grandjean, Dominique
collection PubMed
description 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.
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spelling pubmed-88431282022-02-15 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 Grandjean, Dominique Gallet, Capucine Julien, Clothilde Sarkis, Riad Muzzin, Quentin Roger, Vinciane Roisse, Didier Dirn, Nicolas Levert, Clement Breton, Erwan Galtat, Arnaud Forget, Alexandre Charreaudeau, Sebastien Gasmi, Fabien Jean-Baptiste, Caroline Petitjean, Sebastien Hamon, Katia Duquesne, Jean-Michel Coudert, Chantal Tourtier, Jean-Pierre Billy, Christophe Wurtz, Jean-Marc Chauvin, Anthony Eyer, Xavier Ziani, Sabrina Prevel, Laura Cherubini, Ilaria Khelili-Houas, Enfel Hausfater, Pierre Devillier, Philippe Desquilbet, Loic PLoS One Research Article 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. Public Library of Science 2022-02-14 /pmc/articles/PMC8843128/ /pubmed/35157716 http://dx.doi.org/10.1371/journal.pone.0262631 Text en © 2022 Grandjean et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Grandjean, Dominique
Gallet, Capucine
Julien, Clothilde
Sarkis, Riad
Muzzin, Quentin
Roger, Vinciane
Roisse, Didier
Dirn, Nicolas
Levert, Clement
Breton, Erwan
Galtat, Arnaud
Forget, Alexandre
Charreaudeau, Sebastien
Gasmi, Fabien
Jean-Baptiste, Caroline
Petitjean, Sebastien
Hamon, Katia
Duquesne, Jean-Michel
Coudert, Chantal
Tourtier, Jean-Pierre
Billy, Christophe
Wurtz, Jean-Marc
Chauvin, Anthony
Eyer, Xavier
Ziani, Sabrina
Prevel, Laura
Cherubini, Ilaria
Khelili-Houas, Enfel
Hausfater, Pierre
Devillier, Philippe
Desquilbet, Loic
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8843128/
https://www.ncbi.nlm.nih.gov/pubmed/35157716
http://dx.doi.org/10.1371/journal.pone.0262631
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