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Scent dog identification of samples from COVID-19 patients - a pilot study.

Authors :
Jendrny, Paula
Schulz, Claudia
Twele, Friederike
Meller, Sebastian
von Köckritz-Blickwede, Maren
Osterhaus, Albertus Dominicus Marcellinus Erasmus
Ebbers, Janek
Pilchová, Veronika
Pink, Isabell
Welte, Tobias
Manns, Michael Peter
Fathi, Anahita
Ernst, Christiane
Addo, Marylyn Martina
Schalke, Esther
Volk, Holger Andreas
Source :
BMC Infectious Diseases; 7/23/2020, Vol. 20 Issue 1, p1-7, 7p, 2 Charts, 1 Graph
Publication Year :
2020

Abstract

<bold>Background: </bold>As the COVID-19 pandemic continues to spread, early, ideally real-time, identification of SARS-CoV-2 infected individuals is pivotal in interrupting infection chains. Volatile organic compounds produced during respiratory infections can cause specific scent imprints, which can be detected by trained dogs with a high rate of precision.<bold>Methods: </bold>Eight detection dogs were trained for 1 week to detect saliva or tracheobronchial secretions of SARS-CoV-2 infected patients in a randomised, double-blinded and controlled study.<bold>Results: </bold>The dogs were able to discriminate between samples of infected (positive) and non-infected (negative) individuals with average diagnostic sensitivity of 82.63% (95% confidence interval [CI]: 82.02-83.24%) and specificity of 96.35% (95% CI: 96.31-96.39%). During the presentation of 1012 randomised samples, the dogs achieved an overall average detection rate of 94% (±3.4%) with 157 correct indications of positive, 792 correct rejections of negative, 33 incorrect indications of negative or incorrect rejections of 30 positive sample presentations.<bold>Conclusions: </bold>These preliminary findings indicate that trained detection dogs can identify respiratory secretion samples from hospitalised and clinically diseased SARS-CoV-2 infected individuals by discriminating between samples from SARS-CoV-2 infected patients and negative controls. This data may form the basis for the reliable screening method of SARS-CoV-2 infected people. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712334
Volume :
20
Issue :
1
Database :
Complementary Index
Journal :
BMC Infectious Diseases
Publication Type :
Academic Journal
Accession number :
144730182
Full Text :
https://doi.org/10.1186/s12879-020-05281-3