Use Of Canine Olfactory Detection For COVID-19 Testing Study On U.A.E. Trained Detection Dog Sensitivity

  1. Dominique Grandjean
  2. Dana Humaid Al Marzooqi
  3. Clothilde Lecoq-Julien
  4. Quentin Muzzin
  5. Hamad Katir Al Hammadi
  6. Guillaume Alvergnat
  7. Kalthoom Mohammad Al Blooshi
  8. Salah khalifa Al Mazrouei
  9. Mohammed Saeed Alhmoudi
  10. Faisal Musleh Al Ahbabi
  11. Yasser Saifallah Mohammed
  12. Nasser Mohammed Alfalasi
  13. Noor Majed Almheiri
  14. Sumaya Mohamed Al Blooshi
  15. Loïc Desquilbet

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Abstract

This study aimed to evaluate the sensitivity of 21 dogs belonging to different United Arab Emirates (UAE) Ministry of Interior (MOI), trained for COVID-19 olfactory detection.

The study involved 17 explosives detection dogs, two cadaver detection dogs and two dogs with no previous detection training. Training lasted two weeks before starting the validation protocol. Sequential five and seven-cone line-ups were used with axillary sweat samples from symptomatic COVID-19 individuals (SARS-CoV-2 PCR positive) and from asymptomatic COVID-19 negative individuals (SARS-CoV-2 PCR negative). A total of 1368 trials were performed during validation, including 151 positive and 110 negative samples. Each line-up had one positive sample and at least one negative sample. The dog had to mark the positive sample, randomly positioned behind one of the cones. The dog, handler and data recorder were blinded to the positive sample location.

The calculated overall sensitivities were between 71% and 79% for three dogs, between83% and 87% for three other dogs, and equal to or higher than 90% for the remaining 15 dogs (more than two thirds of the 21 dogs).

After calculating the overall sensitivity for each dog using all line-ups, “matched” sensitivities were calculated only including line-ups containing COVID-19 positive and negative samples strictly comparable on confounding factors such as diabetes, anosmia, asthma, fever, body pain, diarrhoea, sex, hospital, method of sweat collection and sampling duration. Most of the time, the sensitivities increased after matching.

Pandemic conditions in the U.A.E., associated with the desire to use dogs as an efficient mass-pretesting tool has already led to the operational deployment of the study dogs.

Future studies will focus on comparatives fields-test results including the impact of the main COVID-19 comorbidities and other respiratory tract infections.

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    SciScore for 10.1101/2021.01.20.427105: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: All individuals meeting these inclusion criteria were asked if they were willing to participate in the study and signed an individual informed consent form approved by the national ethics committee.
    IACUC: All individuals meeting these inclusion criteria were asked if they were willing to participate in the study and signed an individual informed consent form approved by the national ethics committee.
    RandomizationThe COVID-19 positive and negative sample locations in the line-up were randomly assigned and samples were placed by one dedicated person who remained in the room.
    BlindingThe data recorder collected data in the room using dedicated software developed by Dubaï Police (Figure 2) and was blinded to the COVID-19 positive and negative sample locations.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using SAS® University Edition (SAS Institute Inc., Cary, NC, USA).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The main limitation of our study was the absence of data on dogs marking COVID-19 negative samples. This prevented us from calculating lower and higher bounds of estimated sensitivities, specificities, and positive and negative predictive values, as recommended for detection dogs studies.[43] Therefore, we cannot rule out that the dogs had a high sensitivity with poor specificity. Although low specificity values are possible, it is not expected based on the training performances. Since around 70% of the samples used in the training line-ups (step 4) were COVID-19 negative, it would not be possible to obtain a low specificity if the sensitivity and global performance during training were high. For example, for the five dogs reaching an overall sensitivity of 100% (Allo, Bolt, Cody, Nox and Ramos) during validation, the lowest performance in step 4 of training was 86% (Nox). If Nox’s sensitivity had been 100% in training, Nox’s specificity would have to be 79% to reach a global performance of 86%. Further studies collecting data for COVID-19 positive and negative samples are necessary to estimate sensitivities and specificities, and to calculate positive and negative predictive values. Since the beginning of the COVID-19 pandemic, RT-PCR has been the reference testing method, and is considered reliable for SARS-CoV-2. However, Axell-House et al. recently evaluated the diagnostic accuracy of the COVID-19 test in a scoping review [44]. They found substantial heterogeneity among a...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2021.01.20.427105v1 on bioRxiv