The Role of Scent Dogs in COVID-19 Screening and Testing

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The COVID-19 pandemic has presented numerous challenges to public health systems worldwide. Efficient and accurate testing methods are crucial for early detection, isolation, and quarantine of infected individuals to minimize the spread of the virus. Traditional testing methods, such as RT-PCR, have limitations in terms of turnaround time and sensitivity.

This article explores an alternative approach to COVID-19 screening and testing, involving the use of scent dogs. Scent dogs possess remarkable olfactory capabilities and have shown promising results in various applications, including disease detection.

This comprehensive review aims to evaluate the effectiveness of scent dog testing compared to RT-PCR and rapid antigen (RAG) tests, and assess its potential for widespread implementation in public health screening.

Why utilize medical scent dogs?

A dog’s sense of smell is its most important sense and the one that enables its use for disease detection [4], [5], [6]. A dog senses and differentiates a broad range of molecules with extremely small concentrations. This capability can be attributed to several factors: (1) a dog’s nose is generally proportionately large; (2) it has 1,094 olfactory receptors compared with a human’s 802; (3) it has 125–300 million olfactory cells compared to 5–6 million for a human; (4) a dog has separate sets of inflow nostrils and outflow folds, enabling efficient odor sampling; and (5) one-third of a dog’s brain is devoted to interpretation of odors compared with only 5 % for a human [4], [5], [6].

It is interesting to note that it has been reported that dogs can detect one part per trillion in n-amyl acetate (nAA), which is about three orders of magnitude better than possible with scientific instrumentation [7].

For illustration, a dog could detect the equivalent of one drop of a liquid in 20 Olympic-size swimming pools or 5 × 1010 mL [7]. Dogs can detect odors/volatile organic compounds (VOCs), which are produced by human tissues that evolve into particular pathologic states associated with specific diseases.

The VOCs may originate from flaked-off skin or hair cells, blood, breath, saliva, sweat, tears, nasal mucous, urine, semen, or feces. Dogs likely process and store this odorous information as patterns or smell ‘images’ in their brains. They have already proven successful for the identification of diseases, including malaria, some types of cancers, diabetes, epilepsy, and Parkinson’s disease [6, 8], [9], [10].

Rapid Results and Early Detection:

The time between RT-PCR sampling and the return of results can be up to several days, whereas RAG tests provide results within approximately 15 minutes. However, scent dog testing offers even faster results, with seconds to minutes required for accurate detection.

Research by Crozier et al. demonstrated that the infectious/symptomatic stage of COVID-19 occurs within a few days of exposure to the virus. Hence, early and frequent screening is essential for detecting low viral loads and achieving fast results. The ability of scent dogs to sniff individuals directly enables the detection of viral infections within seconds or minutes, making them a valuable tool for quick identification of asymptomatic, presymptomatic, or subclinical cases.

Importance of Rapid Test Results:

Rapid return of testing or screening results is crucial for effective isolation and quarantining of infected individuals. Timely identification of positive cases allows for immediate implementation of necessary measures to minimize interactions with uninfected individuals, preventing further transmission.

The criticality of speedy test results cannot be overemphasized, as highlighted by multiple studies. Utilizing tests like RAG or scent dog methods, which provide fast results, can significantly enhance public health efforts to curb the spread of the virus.

Comparative Analysis: RT-PCR, RAG, and Scent Dog Tests:

Each testing method has its merits, and several studies support the efficacy of scent dog testing. Hag-Ali challenged the notion of RT-PCR being the “Gold Standard” COVID-19 test, citing Bayesian statistical analyses in their scent dog study. They found that the sensitivity of the scent dog-based test surpassed that of RT-PCR, while the specificity was comparable.

This study, along with others included in the review, suggests that scent dog testing offers a superior alternative to RT-PCR for screening asymptomatic individuals. Additionally, scent dog testing is cost-effective, noninvasive, and environmentally friendly, further contributing to its advantages over traditional methods.

Limitations and Considerations:

Although scent dog testing shows promise, limitations and considerations exist. The reviewed studies identified several limitations, such as determining appropriate training periods and switching from training to testing mode. Factors like distracting noises, smells, or weather conditions can affect accuracy, and a participant’s disease status can change between the dog test and the reference RT-PCR or RAG test. Addressing these limitations requires further research and protocol standardization. Moreover, deploying scent dogs for routine in-person screening demands rapid training, cost-effectiveness analysis, handler awareness of allergies and personal preferences, close dog-handler relationships, and the development of infrastructure for certification and deployment.

Innovations in Diagnostic Instrumentation and Sensors:

Beyond its application in COVID-19 screening, scent dog research can contribute to the development of diagnostic instrumentation and sensors. Scent dogs exhibit extraordinary olfactory capabilities, surpassing the limits of current available instruments by three orders of magnitude.

Exploring volatile organic compounds (VOCs) specific to SARS-CoV-2 infection and assessing their persistence can aid in the development of miniaturized electronic devices called ENoses. These devices mimic the olfactory systems of dogs or humans and utilize artificial neural networks for VOC analysis. Utilizing dogs to train ENoses holds potential for wearable medical sensors capable of detecting diseases and physiological indicators.

Conclusion:

The comprehensive review demonstrates a significant increase in COVID-19 scent dog research over the past two years, highlighting the potential of scent dogs in screening and testing for the virus. Trained scent dogs can effectively and accurately screen and test individuals for COVID-19, providing quick results in public settings.

Their efficacy is comparable to or even superior to traditional testing methods such as RT-PCR and RAG tests. Furthermore, scent dog research contributes to the advancement of medical science and public acceptance of scent dogs as valuable contributors to global disease-fighting efforts. While some limitations and considerations exist, continued research and standardization can overcome these challenges, paving the way for the widespread use of scent dogs in public health screening.


in deep……

Disease- or metabolism-derived volatile organic compounds
Infectious and non-infectious diseases can produce metabolic alterations that may be associated with the release of volatile organic compounds (VOCs) from the body (6–10). In this way, specific volatile biochemical fingerprints may be detected and function as biomarkers for corresponding diseases and their clinical course, provided that appropriate sensory means are available (18, 19). The detective olfactory potential of dogs and other animals has been researched in the medical field concerning various infectious viral, bacterial, and parasitic as well as non-infectious diseases and disorders like epilepsy, diabetes, and cancer (5, 11, 20, 21).

Horvath et al. demonstrated that dogs can differentiate between normal and neoplastic tissue as well as non-neoplastic disease processes such as inflammation, necrosis or emergence of metabolic products (22). For example, Ehmann et al. reported that detection dogs were able to differentiate lung cancers from chronic obstructive pulmonary disease (COPD) by sniffing the breath (23). The occurrence of specific disease-associated VOC-profiles using chemical analytical methods and technical sensory devices was shown in ovarian (24) and breast cancer (25) or in various respiratory diseases (26) and other infections (27).

By applying quantitative analytical methods in animal or in vitro models, interesting questions about the temporal and quantitative dynamics of VOC-production across infection states and progress can be addressed. Traxler et al. (28) detected VOC-changes in the breath of pigs after influenza A infection versus control animals. Interestingly, none of the animals in the study displayed clinical signs, indicating that changes in VOCs still remain despite a lack of significant host immune responses (28). Another study measured VOCs produced by B lymphoblastoid cells following infection with specific avian and human influenza strains in vitro. VOCs did change depending on infection status, which coincided with the many cellular processes that occur when an organism becomes infected (29).

Gould et al. summarized that, in various viral infections, glycolysis in host cells is elevated due to the necessary energy supply for replication, accompanied with increased production of fatty acids, alkanes and related products (30). SARS-CoV-2-infections were shown to lead to characteristic immune and metabolic dysregulation in proteins and lipids in blood serum (31). SARS-CoV-2-specific biochemical processes, such as those associated with modes of entry and replication in cells, combined with induction of humoral and cellular immunologic reactions as well as the dynamic cytokine release might play an important role in COVID-19-specific VOC-expression (32).

The smell of COVID-19
Various studies exist, which give striking insights into SARS-CoV-2-VOC-profiles with differing identifiable VOCs mainly via gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS), time-of-flight-mass spectrometry (TOF-MS) or related techniques (33–38). In principle, spectrometric techniques enable the identification and quantification of VOCs in breath samples, preceded by gas chromatographic separation if needed. Prior studies have reported quantifiable differences in about two dozen VOCs between individuals with COVID-19 versus healthy individuals as well as individuals with other respiratory diseases.

Particularly striking here are COVID-19-associated elevated concentrations of certain alcohols such as butanol and propanol or derivatives (33, 35, 37, 38), aldehydes such as heptanal, octanal, and nonanal (33, 34, 36), as well as ketones such as acetone and butanone or derivatives (33, 38). Other substances with reported increased concentrations are various alkanes, alkenes, further aldehydes, aromatic substances, and their derivatives (33, 34, 36–38). Decreased VOC-concentrations in COVID-19-breath were shown for methanol (33) and – in contrast to Ruszkiewicz et al. (33) – acetone (35).

In addition, Feuerherd et al. showed by headspace air sampling of virus-infected cell cultures that specific differences in 2-butanone, nonane, and pentanal concentrations represent robust discriminatory features between SARS-CoV- 2-, human coronavirus NL63-, and influenza A virus subtype H1N1-infections (39). Similarly, Steppert et al. were able to discriminate between individuals infected with influenza A virus or SARS-CoV-2 analyzing breath samples via IMS coupled with a multicapillary column (40). In a study from ten Hagen et al. dogs were able to discriminate supernatants of SARS-CoV-2-infected human cell cultures from 15 other viruses including coronaviridae, orthomyxoviridae, paramyxoviridae, pneumoviridae, adenovirus, and rhinovirus among others (41).

The use of electronic noses (eNoses) has also been explored by some studies for the detection of COVID-19. Sensors and nanotechnology allow to detect differences in the chemical composition of air samples by means of chemical reactions with sensor arrays consisting of specific coatings of certain metal oxides, organic polymers, nanoparticles, etc. (42, 43). The emerging differences in resistance and conductivity produce corresponding “volatile finger-” or “breathprints” via artificial neural networks (44). eNoses were able to discriminate breath samples between individuals with symptomatic COVID-19 versus healthy individuals (45–47) or other respiratory diseases (48), Post-COVID-19 condition (49), and non-symptomatic COVID-19 (47, 50). Two recent studies provided evidence that also dogs can detect Post-COVID-19 conditions (51, 52).

Detection of disease-related volatile organic compounds by devices versus dogs
Despite good discriminatory potential within individual studies, the comparison of the described chemical analytical or sensor methods between studies nevertheless highlights some drawbacks of these techniques, which may create challenges for their use in an open screening process. In the following paragraphs, certain features of the canine and technical methods are critically discussed.

First, it is not ensured that all relevant VOCs are reliably detected via MS or sensor methods. Differences in databases and small number of metabolites available as standards complicate interpretations of MS analyses (53). Small ions, molecules or molecular fragments cannot be easily detected and make it difficult to interpret and draw conclusions about originally contained compounds. For example, small hydrocarbon-based molecules occur abundantly in exhaled breath, making their detection complicated due to overlap with molecules of similar spectra (38).

In addition, certain measurable VOCs are non-specifically altered across diseases making disease discrimination prone to errors. For example, elevated propanol in breath is associated with infectious and non-infectious respiratory diseases other than COVID-19 (35, 54–57). Analogously, a certain “roughness” of detection is also given with eNoses, since the selective and susceptible coatings of the sensors might lead to physical limitations in qualitative and quantitative resolution (42, 58, 59). These aspects become impactful, especially when considering that VOCs in exhaled breath are numerous and most of the VOC-compositions have wide inter-individual variations (60). Similarly, some uncertainties exist in canine detection, as well, since research in perception and processing of certain olfactory cues in dogs is not yet very advanced. Thus, the definition of the target odor, especially in the medical field, remains one of the main challenges in canine scent detection.

Second, differences in the detection of COVID-19-VOCs across studies with MS-detection might emerge due to the choice of different detection and analytical techniques, different patient recruitment procedures and the environment (33, 37). Snitz et al. and Rodriguez-Aguilar et al., who conducted cross-sectional trials in a real-life scenario with eNoses, showed the significant impact of differing sample acquisition methods and environmental factors on the results (45, 50). Although disease discrimination was possible, certain environment-associated deterioration in eNose performance could not be excluded (50).

Therefore, it is probable that the chemical analytical and sensor detection methods are susceptible to “olfactory noise” for COVID-19-detection. While these devices might feed intrinsic and extrinsic VOCs to the analyzer in an unfiltered, noisy, and “one-dimensional” manner, living biosensors such as dogs may perceive the learned sensations that are evoked due to a certain key composition, or “network,” of complex and low-concentration VOCs. Dogs are therefore possibly more capable of searching specifically for the “needle in the haystack” than current technical solutions, provided that training samples are correctly and meticulously defined according to the target condition. However, olfactory noise and other distractors may play an important role for canine detection, as well, especially when using detection dogs in the open environmental space. Further research is needed to increase control of these confounding factors.

Third, chemical analytical instruments are often stationary devices. They are mainly used offline and are coupled with software for evaluative steps. eNoses are mobile and online analysis is possible, but they require further software and deep-learning approaches in order to “learn” and analyze specific VOC-patterns. For example, the sensors must be able to detect the correct compounds and in the correct ratio and at low concentrations.

The software then has to interpret the signals correctly, and environmental factors can cause difficulties, as described above. Each specific application needs considerable method development work in advance and is cost-intensive which is a drawback in rapid pandemic dynamics of emerging pathogens. Marder et al. stated that “data processing is a major bottleneck of metabolomics” (38). Furthermore, sensors often have a short life and their sensitivity deteriorates in presence of humidity (42, 48, 50).

The analysis time for chemical analytical devices or sensors used for COVID-19-detection in the aforementioned studies (see section “The smell of COVID-19”) revealed a range of one to 16 min per sample. Dogs, on the other hand, are mobile and can identify COVID-19-samples within a few seconds, i.e., in real-time. This requires preceding specific canine training for high discriminating performance of approximately 4 weeks with a range of 2–15 weeks regardless of the chosen training method (when studies with dogs that had previous COVID-19-scent experience were excluded) (4). However, a variety of factors can have a large influence on learning efficiency, e.g., number of sample exposures, environmental factors, the success of odor generalization, etc. Furthermore, personality traits of dogs and emerging fatigue during work (see also section “Considerations regarding Dog Selection”) are impacting factors, which represent a disadvantage compared to well established artificial devices.

Finally, the lower limit of detection in dogs is one part per trillion (ppt), exceeding the range of detection of current available instruments by around three orders of magnitude (61–63). A new study shows that dogs are indeed able to detect even far lower concentrations, in the order of 10–21 (Turunen et al., unpublished). Since it was reported that VOCs from breath are released in the range of parts per billion (ppb) to ppt, dogs might appear more suitable for VOC-detection in comparison to instruments with sensitivities in the ppb range (50, 64). However, the canine range of detection was validated in controlled environments, which could mask an actual lower sensitivity. In addition, sensitivity might also depend on the qualitative characteristics of the target odor.

In hospitals and other health care facilities, chemical analytical and sensory instruments are well suited for sensitive and relatively rapid isolation of patients (33, 37), provided that they are swiftly fed with sufficient data for rapid adaptive purposes (36, 65). For external mass screening, the use of such technical devices for VOC-detection is complex due to sample processing time, limited selectivity, and increased susceptibility to material damage as well as to external olfactory noise in a poorly controllable environment.

Although similar challenges may exist for dogs, their ability to learn and to process information immediately can make them more capable of searching for specific odors in real time, particularly in complex environments. However, the success of canine detection depends significantly on the training methods and the choice of the right training samples, which is one of the main challenges and disadvantages compared to established analytical and sensory methods. Finally, dogs are likely to be complimentary to sensors and analytical methods and more appropriate for certain scenarios.

reference link : https://www.frontiersin.org/articles/10.3389/fmed.2022.1015620/full


reference link: https://www.degruyter.com/document/doi/10.1515/jom-2023-0104/html

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