Author:
Jendrny Paula,Twele Friederike,Meller Sebastian,Schulz Claudia,von Köckritz-Blickwede Maren,Osterhaus Albertus Dominicus Marcellinus Eras,Ebbers Hans,Ebbers Janek,Pilchová Veronika,Pink Isabell,Welte Tobias,Manns Michael Peter,Fathi Anahita,Addo Marylyn Martina,Ernst Christiane,Schäfer Wencke,Engels Michael,Petrov Anja,Marquart Katharina,Schotte Ulrich,Schalke Esther,Volk Holger Andreas
Abstract
Abstract
Background
The main strategy to contain the current SARS-CoV-2 pandemic remains to implement a comprehensive testing, tracing and quarantining strategy until vaccination of the population is adequate. Scent dogs could support current testing strategies.
Methods
Ten dogs were trained for 8 days to detect SARS-CoV-2 infections in beta-propiolactone inactivated saliva samples. The subsequent cognitive transfer performance for the recognition of non-inactivated samples were tested on three different body fluids (saliva, urine, and sweat) in a randomised, double-blind controlled study.
Results
Dogs were tested on a total of 5242 randomised sample presentations. Dogs detected non-inactivated saliva samples with a diagnostic sensitivity of 84% (95% CI: 62.5–94.44%) and specificity of 95% (95% CI: 93.4–96%). In a subsequent experiment to compare the scent recognition between the three non-inactivated body fluids, diagnostic sensitivity and specificity were 95% (95% CI: 66.67–100%) and 98% (95% CI: 94.87–100%) for urine, 91% (95% CI: 71.43–100%) and 94% (95% CI: 90.91–97.78%) for sweat, 82% (95% CI: 64.29–95.24%), and 96% (95% CI: 94.95–98.9%) for saliva respectively.
Conclusions
The scent cognitive transfer performance between inactivated and non-inactivated samples as well as between different sample materials indicates that global, specific SARS-CoV-2-associated volatile compounds are released across different body secretions, independently from the patient’s symptoms. All tested body fluids appear to be similarly suited for reliable detection of SARS-CoV-2 infected individuals.
Publisher
Springer Science and Business Media LLC
Cited by
23 articles.
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