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. 2022 Dec 24;258:105825. doi: 10.1016/j.applanim.2022.105825

Is diagnostic performance of SARS-CoV-2 detection dogs reduced -due to virus variation- over the time?

Elcin Ozgur-Buyukatalay a,⁎, Yasemin Salgirli Demirbas b, Gulendam Bozdayi c, Gorkem Kismali d, Mustafa Necmi Ilhan e,f
PMCID: PMC9788989  PMID: 36589678

Abstract

Medical detection dogs have a high potential for use as alternative diagnostic tools not only for organic diseases, but also for infectious diseases. However, new variants emerging over time may affect the accuracy and sensitivity of diagnostic methods including medical detection dogs in case of viral pandemics. To the best of our knowledge, this is a pioneer study aimed to investigate diagnostic performances and generalization ability of SARS-CoV-2 detection dogs against the new variant after being trained with the original virus. Two SARS-CoV-2 detection dogs were used in this study. In total, 1002 samples including the Omicron variant were introduced to the dogs using a double-blinded design. Two different refresher training sessions were conducted to train the dogs to identify the scent of the Omicron variant. In the first refreshment training, mixed samples (original virus and Omicron variant) were used. The diagnostic performances of the dogs were significantly increased only after the second refreshment training where only the Omicron variant was introduced. This study illustrates that diagnostic performances of SARS-CoV-2 detection dogs were not consistent over time with the emerging new variants. Thus, refreshment training with new variant(s) should be conducted with every new variant which may affect the diagnostic performances of those dogs in such infectious outbreaks.

Keywords: Diagnostic performance, Omicron variant, Refreshment, SARS-CoV-2 detection dogs

1. Introduction

Recently, infectious diseases are considered as one of the most important threats to the global public and economy in the global world (WHO, 2007). On one hand, emergence and spread of infectious diseases have accelerated since the 1970s. On the other hand, globalization causes the rapid spread of infectious diseases as a result of new human travel patterns and increased human interaction (WHO, 1997). Therefore, the prevention and diagnosis of new infectious diseases by using accurate, rapid and economical diagnostic methods is of great importance in prevention of viral pandemic (Angle et al., 2016).

The ongoing SARS-CoV-2 pandemic revealed the diagnostic inadequacy of the routine methods for screening infected people in public areas in such epidemics. Studies showed that since up to 70 % of patients, who were diagnosed with SARS-CoV-2 by RT-PCR, showed no or minimal symptoms, they pose a significant risk for spreading infection (Gao et al., 2021). However, none of the currently used methods are reliable and/or applicable for mass screening of this infection in public places (Martinez-Jimenez et al., 2021, Nsawotebba et al., 2021; Sharun et al., 2020; Peeling et al., 2021). The reverse transcription polymerase chain reaction (RT-PCR) test is a routine diagnostic tool to detect patients infected with SARS-CoV-2. However, as this method is expensive and time consuming, it is not possible to use this method as a screening tool. Repeated testing or advanced diagnostic techniques, such as computed tomography (CT) is recommended for a definitive diagnosis with RT-PCR due to high false negative as well as “turn-positive” diagnostic rates (Wikramaratna et al., 2020, Xiao et al., 2020). Moreover, there have been controversial discussions on diagnostic sensitivity of the RT-PCR in case of viruses with high mutation rates. SARS-CoV-2 was reported to have undergone more than 10,000 single mutations up to date with averaging 1 × 10−3 mutations per genomic residue and year (Wu et al., 2020; Domingo and Perales, 2021). Some researchers claim that a mutated virus may reduce the detection sensitivity of RT-PCR in particular if the mutation occurs in certain locations where probes and primers bind (Yang et al., 2014). The new Omicron variant for example was currently considered to pose a significant detection challenge for PCR assays due to a series of mutations in the spike protein including the receptor-binding domain (Metzger et al., 2021). Some researchers, on the other hand, suggest that assay performances are not affected or reduced even though mismatches occur in the primer/probes binding regions of SARS-CoV-2 (Gand et al., 2020).

Considering the diagnostic challenges in SARS-CoV-2, authorities highlight the urgency of developing alternative diagnostic methods to prevent new viral outbreaks in upcoming years (Cascella et al., 2022, Pollock and Lancaster, 2020, Rothe et al., 2020). Lately, medical detection dogs have drawn considerable attention among researchers because of their superior olfactory ability to detect certain infectious diseases (Bomers et al., 2012, Janik et al., 2020) and non-infectious diseases (Pickel et al., 2004, McCulloch et al., 2006, Horvath et al., 2010) at their early stages. Authorities believe that once specifically trained for SARS-CoV-2, dogs can be used for mass screening in public areas such as airports, concerts etc. (Angeletti et al., 2021). Thus, the dogs are considered as affordable, fast and mobile early warning diagnostic tools in the case of such pandemic situations (Pirrone and Albertini, 2017, Dickey and Junqueira, 2021). So far, a great deal of research has been published on SARS-CoV-2 detection dogs. According to these studies, dogs can detect SARS-CoV-2 from human secretions such as sweat, saliva, urine, and tracheobronchial secretion, as well as face masks, with greater sensitivity and specificity than routine diagnostic methods (Grandjean et al., 2020, Jendrny et al., 2022, Eskandari et al., 2021, Essler et al., 2021). Moreover, a recent study showed that diagnostic performance of the SARS-CoV-2 detection dogs is higher in comparison to the RT-PCR (Hag-Ali et al., 2021).

Although those results are highly promising, no study has yet been conducted to evaluate whether diagnostic performances of detection dogs would be stable over time in case of viral infections. Thus, it is unknown whether factors such as mutant variants affect the diagnostic accuracy of these dogs once they were trained with the odour which is specific to the original version of SARS-CoV-2. Considering this gap, this research aims to investigate the diagnostic performances of the SARS-CoV-2 detection dogs over time. Accordingly, generalization ability of SARS-CoV-2 detection dogs in case of virus variants were objected to be evaluated.

2. Material and methods

2.1. Sample collection for training

The ethical approvals were obtained from the Local Ethics Committee on Animal Experiments of Gazi University (31.03.2022) and from Clinical Research Ethics Committee of Gazi University (2022/42). Standard disposable surgical face masks with three layers of protection were collected from patients with symptoms, who were admitted to the hospital to be tested for Covid-19 via Polymerase Chain Reaction (PCR) tests. Before the mask collection, each individual was informed about the protocol and they signed an informed consent. Before the masks were collected, the patient had been asked to take in and out 10 deep breaths. Face masks were sealed in plastic bags and transferred to the dog training center.

2.2. Dogs

A Labrador Retriever, Rofle, (4 years old, female) and an English Cocker Spaniel, Firfir, (3 years old, male), which belong to the Republic of Turkey Ministry of Interior Gendarmerie Commando Special Operations, were trained and used in this study. Both dogs had a previous history of SARS-CoV-2 detection training from the face mask samples. The dogs had been trained and tested by using the PCR + samples obtained from the unvaccinated patients and before any virus variants were officially announced. Both dogs were proved to show a high diagnostic accuracy with a high sensitivity and specificity while detecting face masks infected with the SARS-CoV-2 (Salgirli Demirbas et. al., Article in press). The dogs continued to work with training masks regularly every day for a period of six months. This study was initiated 6 months after evaluating the performances of Firfir and Röfle in detecting the positive face masks infected with the original virus.

2.3. Test protocol

The test protocol, which has been carried out for 21 days, included 5 test trials and 2 refresher training. In total 1003 test masks were presented to both dogs during the test protocol ( Table 1). A number was assigned to each test sample before the trials. Test samples were recorded to the system with the assigned number and status (positivity/negativity). Only the positive masks infected with Omicron variants (n = 371) were used as positive test samples in this study. The positive training masks (n = 29) obtained from SARS-CoV-2 patients in the study by Salgirli Demirbas et. al. (Article in press) were used as control samples. MAHATON (Beijing,China) fold tableware sterilizer was used to decontaminate the masks before presenting them to the dogs.

Table 1.

The number of face masks used in each trial and the duration of the test protocol.

PCR + masks PCR - masks Total Masks Duration
Trial 1 136 112 248 5 days
Trial 2 77 157 234 4 days
Trial 3 32 72 104 2 days
Trial 4 102 201 303 5 days
Trial 5 24 90 114 3 days
Total 371 632 1003 19
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2.4. Test trials

Five separate test sessions per day have been conducted for both dogs at the dog-training center of the Republic of Turkey Ministry of Interior Gendarmerie Commando Special Operations. Double blind test design was used in all trials. Namely, test samples were unknown to the trainer and the test person. In each test session, the scent platform was presented 5–10 times to the dogs depending on the motivation of the dog. In each session, different test masks were introduced to the dog. One positive control sample was presented to the dogs every 3–5 introductions of samples in order to keep the dog motivated during the search.

2.5. Refresher training

Because the diagnostic accuracy of both dogs was measured as “bad” (Šimundić, 2009), a refresher training was decided to be carried out after the first trial. The training samples were chosen among the positive samples (n = 20) from the first trial (Omicron samples) and also among the positive samples (n = 20) from the initial training (Original virus). The training masks were presented to the dogs in a randomized order. Since the diagnostic accuracy of the both dogs were still not sufficient after three test trials, another refresher training was decided to be proceeded before the fifth trial. In the second refresher training, only the masks with Omicron variant were used as positive samples and positive masks infected with the original SARS-CoV-2 were excluded. Each refresher training lasted 1 day for each dog.

2.6. Statistical analyses

Statistical analysis was performed with IBM SPSS Statistics for Windows, Version 23.0 (IBM Corp., Armonk, NY). The area under the curve (AUC), sensitivity or true positive rate (TPR), specificity or true negative rate (TNR), positive and negative predictive values (PPR/NPR), positive and negative likelihood ratios (LR+/LR-) and accuracy were calculated to determine diagnostic performance of the dogs in predicting COVID+ samples. Delong et al. (1988) method was used for comparison of AUCs. A p-value less than 0.05 was considered statistically significant.

3. Results

3.1. Diagnostic performances of the dogs

In the first trial, diagnostic accuracy of the dogs were 53.63 % and 48.79 % with low diagnostic sensitivity (50 % and 42.65 %) and diagnostic specificity (58.04 % and 56.25 %). In the last trial, diagnostic accuracy of the dogs were increased to 67.52 % and 69.40 % with higher diagnostic sensitivity ( 81.82 % and 83.12 %) and diagnostic specificity (60.51 % and 62.58 %) (Table 1).

Table 2.

Diagnostic performance of the both dogs (Röfle and Fırfır) to predict COVID +.

Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR+ LR- Accuracy (%)
Röfle
Time 1 50 58.04 59.13 48.87 1.19 0.86 53.63
Time 2 61.77 63.68 46.32 76.65 1.70 0.60 63.04
Time 3 56.25 54.17 35.29 73.59 1.23 0.81 54.81
Time 4 58.33 67.78 32.56 85.92 1.81 0.62 65.79
Time 5 81.82 60.51 50.4 87.16 2.07 0.30 67.52
Overall 60.92 61.39 48.09 72.80 1.58 0.64 61.22
Fırfır
Time 1 42.65 56.25 54.21 44.68 0.98 1.02 48.79
Time 2 61.77 63.68 46.32 76.65 1.70 0.60 63.04
Time 3 53.13 58.33 36.17 73.68 1.28 0.80 56.73
Time 4 58.33 68.89 33.33 86.11 1.88 0.61 66.67
Time 5 83.12 62.58 52.46 88.18 2.22 0.27 69.40
Overall 58.22 62.22 47.58 71.66 1.54 0.67 60.74
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Face masks were further categorized according to the virus load of the patients and diagnostic performances of the dogs were evaluated accordingly ( Table 2, Table 3, Table 4).

Table 3.

Diagnostic performance of the dogs to predict SARS-CoV-2 with low viral load.

Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR+ LR- Accuracy (%)
Röfle
Time 1 52.07 58.04 57.27 52.85 1.24 0.83 54.94
Time 2 53.97 63.68 31.78 81.53 1.49 0.72 61.36
Time 3 42.11 54.17 19.51 78 0.92 1.07 51.65
Time 4 42.86 67.78 9.38 93.85 1.33 0.84 65.98
Time 5 85.71 60.51 40.39 93.14 2.17 0.24 66.51
Overall 57.92 61.39 38.07 78.07 1.50 0.69 60.38
Fırfır
Time 1 45.46 56.25 52.89 48.84 1.04 0.97 50.64
Time 2 53.97 63.68 31.78 81.53 1.49 0.72 61.36
Time 3 36.84 58.33 18.92 77.78 0.88 1.08 53.85
Time 4 42.86 68.89 9.68 93.94 1.38 0.83 67.01
Time 5 87.76 62.58 42.57 94.18 2.35 0.20 68.63
Overall 54.83 62.22 37.37 77.01 1.45 0.73 60.07
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PPV; positive predictive value, NPV; negative predictive value, LR+ ; positive likelihood ratio, LR-; negative likelihood ratio.

Table 4.

Diagnostic performance of the dogs to predict SARS-CoV-2 with high viral load.

Sensitivity (%) Specificity (%) PPV (%) NPV (%) LR+ LR- Accuracy (%)
Röfle
Time 1 33.33 58.04 9.62 86.67 0.79 1.15 55.12
Time 2 74.36 63.68 28.43 92.75 2.05 0.40 65.42
Time 3 76.92 54.17 23.26 92.86 1.68 0.43 57.65
Time 4 64.71 67.78 27.5 91.95 2.01 0.52 67.29
Time 5 75 60.51 25.3 93.14 1.90 0.41 62.70
Overall 67.86 61.39 23.75 91.51 1.76 0.52 62.37
Fırfır
Time 1 20 56.25 5.77 84 0.46 1.42 51.97
Time 2 74.36 63.68 28.43 92.75 2.05 0.40 65.42
Time 3 76.92 58.33 25 93.33 1.85 0.40 61.18
Time 4 64.71 68.89 28.21 91.18 2.08 0.51 68.22
Time 5 75 62.58 26.58 93.27 2 0.40 64.48
Overall 66.07 62.22 23.72 91.16 1.75 0.55 62.80
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PPV; positive predictive value, NPV; negative predictive value, LR+; positive likelihood ratio, LR-; negative likelihood ratio.

3.2. Comparison of diagnostic performances of the dogs between the first and last trials

Diagnostic performances of the dogs between the first and last trials were compared with each other ( Table 5). Significant increase in diagnostic performances of both dogs was detected in the fifth trial (p ≤ 0.01).

Table 5.

Comparison of diagnostic performances of the dogs between the first and last trials.

Accuracy (%)
 Difference
First Trial Last Trial p-value
Röfle 55.12 62.70 ≤0.01
Fırfır 51.97 65.42 ≤0.01
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4. Discussion

Current SARS-CoV-2 pandemic showed that diagnostic challenges of the routine diagnostic methods pose significant risk for transmission of those kinds of viral infections. Although RT-PCR is a common diagnostic method used in SARS-CoV-2, there are certain limitations of using this method for mass screening in case of such a pandemic. Besides being expensive and time consuming, its diagnostic performance can negatively be affected by different factors such as phase of infection and variants (Hay et al., 2022). SARS-CoV-2 detection dogs were suggested as alternative diagnostic tools considering their high diagnostic performances in many studies (Grandjean et al., 2020, Jendrny et al., 2022, Eskandari et al., 2021). However, it is unknown whether those performances were negatively affected over time due to similar factors as in RT-PCR. This study was the first study to investigate the diagnostic performances of SARS-CoV-2 detection dogs with new variants over time, which had been trained with the original version of the virus.

Both dogs in our study had been trained using face masks from patients infected with the original SARS-CoV-2. They showed high diagnostic performances while finding the positive masks infected with the original SARS-CoV-2 virus (Salgirli Demirbas et. al., 2022) This study was conducted six months after the training of the dogs with the original virus, which was after the Omicron variant had been classified as a Variant of Concern (Metzger et al., 2021). Analyses for diagnostic performances of the dogs revealed that diagnostic accuracies of both dogs were below the sufficient measures at the first trial in which samples infected with Omicron variant were used. Since the dogs in this study were exposed to a new variant for the first time and, further, they were only working with the original virus in the meanwhile, lower diagnostic performances were rather expected. A recent study showed that diagnostic performances of the SARS-CoV-2 dogs decreased in case of introducing different, i.e. heated samples (Jendryn et al., 2020). Furthermore, generalization of the new samples was reported to only be achieved after several days of training in SARS-CoV-2 dogs (Jendrny et al., 2020). It is well known that the Omicron variant includes different mutations in the receptor-binding domain of the spike protein, which causes increased transmission rate and immune evasion after natural infection and vaccination (Andrews et al., 2022). It also differed from the original virus by a lower intrinsic virulence and reduced effect on the lower respiratory system (Brüssow, 2022). As a result, it is reasonable to expect that Omicron variants will cause different reactions in body cells, altering the composition of volatile organic compounds caused by the original virus. As medical detection dogs were trained to smell volatile organic compounds in body fluids or breath which are assumed to be specific to infection (Shirasu and Touhara, 2011), the decrease in diagnostic performance of SARS-CoV-2 detection dogs over time can be explained by changes in odor caused by different volatile organic compounds due to the Omicron variant. However, this assumption can only be confirmed by comparing the diagnostic performance of the same dog when identifying the positive masks infected with Omicron variant and the original virus, which was not conducted in this study.

The Omicron variant was reported to be the most prevalent variant around the world (Mostafavi et al., 2022) which was recently announced as the Variant of concern (VOC) (Metzger et al., 2021). Thus, in this study only the samples infected with Omicron variants were used to test generalization ability of the dogs in case of different variants. Two different refresher trainings were conducted in order to evaluate the changes in diagnostic performances of the dogs. In the first refresher training, the original virus and its Omicron variant (mix samples) were used as positive targets in a randomized order. Three consecutive trials were carried out following the first refresher training. No improvement was observed in diagnostic performances of the dogs. Therefore, another refresher training, where only samples infected with Omicron variant were used as positive targets, was conducted. Diagnostic performances of both dogs were significantly increased after the second refresher training. This result shows that in case of emergence of new variants, a refresher training in which the new variant was introduced, would be helpful to increase diagnostic accuracies of infection detection dogs. It was however worth noting that diagnostic performances of the dogs were still below the initial performances, i.e. while detecting the original virus.

Two reasons can be hypothesized to explain lower diagnostic performances of the dogs despite refresher training. This result can be related to generalization performances of the SARS-CoV-2 detection dogs. It is known that a failure to generalize the smell may cause detection dogs to miss the targeted smell, whereas high generalization level may increase the rate of false responses (Moser et al., 2019). Accordingly, considering the high false positive rates of the both dogs, high level of generalization can be a contributing factor to reduced diagnostic performances. Another possible contributing factor of reduced diagnostic performances of the dogs may be the false negative results of the RT-PCR. RT-PCR was reported to give false negative results due to several different reasons including suboptimal or inappropriate sample collection, testing in early phase of infection, low analytic sensitivity, low viral load and viral shedding (Arevalo-Rodriguez et al., 2020, Kanji et al., 2021). Authorities emphasize the lack of gold standards for evaluating RT-PCR performance (Kanji et al., 2021). To overcome all those limitations of RT-PCR, repeated testing was recommended for the patients who display symptoms of SARS-CoV-2 (WHO, 2020). In this study, face masks were collected from patients who were admitted to hospital with possible SARS-CoV-2 symptoms. Thus, it is possible that false positive rates of the dogs reflect false negative rates of the RT-PCR. However, as no further screening was conducted for PCR - patients, the reason for high false positivity remained unknown in this study. Further studies comparing the repeated PCR results with detection dogs would contribute significantly to the literature.

5. Conclusion

This study showed that Omicron variant reduced diagnostic performances of the dogs, which had been trained with samples infected with original SARS-CoV-2. Generalization was only achieved after a refreshment training in which the Omicron variant was introduced to the dogs although diagnostic performances of the dogs were still below. As a result, while virus detection dogs are excellent alternatives to routine diagnostic methods in the event of a pandemic, refreshment and generalization training should be conducted if new variants emerge. Future studies comparing diagnostic performances of RT-PCR and medical detection dogs would be beneficial to understand the main reason for increased high false positive rates of SARS-CoV-2 detection dogs over time. ( Fig. 1).

Fig. 1.

Fig. 1

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Sensitivity and Specificity of Diagnostic performance of the both dogs (Röfle and Fırfır) to predict COVID +.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors acknowledge the technical support provided by the Republic of Turkey Ministry of Interior Gendarmerie Commando Special Operations Command. Authors express their gratitude to Yusuf Ziyaddin Cavlak (Gendarmerie Commando Special Public Security Commander Brigadier), Faruk Kasar (Gendarmerie Commando Special Public Security Deputy Commander), Mehmet Gördü (Gendarmerie Senior Sergeant Canine Unit Company Commander), Hakan Gül (Gendarmerie Sergeant, Dog handler).

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