Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

Abstract

Background: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry.

Methods: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening.

Results: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95-100) to 100% and specificity from 99% (95% CI 97-100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76-87) to 94% (95% CI 89-98) and specificity ranging from 76% (95% CI 70-82) to 92% (95% CI 88-96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only.

Conclusions: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people.Trial Registration NCT04509713 (clinicaltrials.gov).

Keywords: COVID-19; infection control; public health; rapid screening.

© The Author(s) 2022. Published by Oxford University Press on behalf of International Society of Travel Medicine.

Figures

Figure 1

Principal component analysis of odour samples by organic semi-conducting (OSC) sensors on two different days; (A) Day 1 and (B) Day 2. Where red circles SARS-CoV-2 infected samples and green triangles are SARS-CoV-2 uninfected odour samples

Figure 2

Modelling the effectiveness of a Rapid Screen and Test strategy. The Ct-dependent sensitivity was estimated by fitting a logistic regression model to the results of the double-blind testing (this study) for dogs and to the data presented for the lateral flow test (LFT) in Peto. Results show that sensitivity is independent of Ct for dogs (panel A; P = 0.570) whereas sensitivity decreases with increasing Ct values for LFT (panel B; P < 0.0001). The cycle threshold (Ct) is considered a proxy for viral load and is repeatedly simulated from a distribution defined by a starting Ct, a peak Ct and a total duration of infection with a random time since initial exposure. Panel C shows the relationship between Ct and time since exposure for a typical symptomatic individual (asymptomatic individuals having 40% shorter duration of infection). Inset panel shows that both symptomatic and asymptomatic individuals have Ct values between 35 and 40 for approximately one third of the duration of infection. The modelled relationship between sensitivity and Ct for PCR, LFT and dogs is shown in panel D. The sensitivity-Ct relationship for dogs (light green line, 80%; green line, 85%; dark green line, 90%) and LFT (orange line) was informed from data as shown in panels (A) and (B). The sensitivity for PCR was assumed to be 100% up to a Ct of 35, either remaining at this level to a Ct of 40 (yellow solid line) or declining to 0% between 35 and 40 (yellow dotted line). This uncertainty of sensitivity between Ct values of 35 and 40 was also considered for the dogs, with different sensitivity estimated from the data of the double-blind testing (green dotted lines) and representing variability in dog performance. The percentage of cases detected by different strategies is shown in panel E, where baseline corresponds to isolation of symptomatic individuals only and PCR corresponds to the (hypothetical) screening of all individuals with PCR. LFT + PCR and Dogs + PCR indicate, respectively, rapid mass screening with LFTs or dogs followed by confirmatory PCR of positively identified cases. The ratio of the transmission averted by these scenarios compared to baseline is shown in panel F. In panels E and F, filled and open points correspond to a Ct detection limit of 35 and 40 respectively

Figure 3

Exemplar of (A) Current SARS-CoV-2 Strategy for red list countries and unvaccinated travellers (10-day quarantine and PCR tests) and (B) Proposed Rapid Screen and Test Strategy. Schematic outlining the number of true negatives (black) and true positives (red) and false negatives (blue) as a result of screening people, with 1% SARS-CoV-2 prevalence, followed by confirmatory PCR testing. Assuming 100% sensitivity and specificity of RT-PCR, and 90% sensitivity and 89% specificity of dogs (values used in the mathematical modelling). ‘Inconvenienced’ refers to virus-negative passengers required to be in quarantine (red dotted line)