Can Canine Medical Detection become a new paradigm to control infectious diseases? An analysis of the COVID 19 detector dogs’ results and challenges

Dr Anne-lise Chaber¹, Dr Susan Hazel¹, Professor Dominique Grandjean², Associate Professor Charles Caraguel¹

¹University Of Adelaide, Adelaide, South-Australia, ²National Veterinary School of Alfort, Maisons-Alfort, France

Introduction

RT-PCR is currently the standard diagnostic method to detect symptomatic and asymptomatic individuals infected with SARS-CoV-2. However, RT-PCR results are not immediate and may be falsely negative before an infected individual sheds viral particle in the upper airway where swabs are collected. Infected individuals emit volatile organic compounds in their breath and sweat that are detectable by trained dogs.

Methods

Here we evaluate the diagnostic accuracy of dog detection against SARS-CoV-2 infection.  A group of 15 dogs previously trained to detect volatile organic compounds in axillary sweat samples of individuals infected with SARS-CoV2 at two centres in Australia, were tested on a total of 514 axillary sweat specimens. Detection results were collected on 931 randomised and fully blinded runs carried on olfaction cones line-ups. The infection status of the cases (n=100) and non-cases (n=414) were confirmed based on RT-PCR results including PCR cycle threshold values, as well as clinical history.

Results

Across all 15 dogs, the overall diagnostic sensitivity (DSe) was 95.3% (95%CI: 93.1%-97.6%) and diagnostic specificity (DSp) was 97.1% (95%CI: 90.7%-100.0%). The location of evaluation did not impact the detection performances. The accuracy of detection varied across dogs and experienced dogs revealed a marginally better DSp (P-value = 0.003).

Conclusion

Those results, which follow the current Standards for Reporting Diagnostic Accuracy (STARD), suggest that canine olfactory detection of COVID 19 could play an important role in the screening and mass COVID 19 pre-testing situations. The potential, limitations and challenges of this alternative detection tool are discussed.

Biography:

Dr. Anne-Lise Chaber is a One health Specialist at the University of Adelaide, the University of Liege and the Food and Agriculture Organisation of the United Nations. Anne-Lise carries research on the prevention, detection and management of infectious diseases at the wildlife-livestock-human interface.

Anne-Lise is a Doctor in Veterinary Medicine with a Master in Wild Animal Health and a PhD in epidemiology. She has worked on emerging infectious disease detection and outbreak management in animal and human populations in Europe, Africa, the Middle East and Oceania.