Scent dog identification of samples from COVID-19 patients - a pilot study.
BMC Infect Dis
; 20(1): 536, 2020 Jul 23.
Article
in English
| MEDLINE | ID: covidwho-1072981
ABSTRACT
BACKGROUND:
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.METHODS:
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.RESULTS:
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.CONCLUSIONS:
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.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Mass Screening
/
Coronavirus Infections
/
Betacoronavirus
/
Odorants
Type of study:
Diagnostic study
/
Experimental Studies
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Limits:
Animals
/
Humans
Language:
English
Journal:
BMC Infect Dis
Journal subject:
Communicable Diseases
Year:
2020
Document Type:
Article
Affiliation country:
S12879-020-05281-3
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