Scent dog identification of SARS-CoV-2 infections in different body fluids.

BACKGROUND: The main strategy to contain the current SARS-CoV-2 pandemic remains to implement a comprehensive testing, tracing and quarantining strategy until vaccination of the population is adequate. Scent dogs could support current testing strategies. METHODS: Ten dogs were trained for 8 days to detect SARS-CoV-2 infections in beta-propiolactone inactivated saliva samples. The subsequent cognitive transfer performance for the recognition of non-inactivated samples were tested on three different body fluids (saliva, urine, and sweat) in a randomised, double-blind controlled study. RESULTS: Dogs were tested on a total of 5242 randomised sample presentations. Dogs detected non-inactivated saliva samples with a diagnostic sensitivity of 84% (95% CI: 62.5-94.44%) and specificity of 95% (95% CI: 93.4-96%). In a subsequent experiment to compare the scent recognition between the three non-inactivated body fluids, diagnostic sensitivity and specificity were 95% (95% CI: 66.67-100%) and 98% (95% CI: 94.87-100%) for urine, 91% (95% CI: 71.43-100%) and 94% (95% CI: 90.91-97.78%) for sweat, 82% (95% CI: 64.29-95.24%), and 96% (95% CI: 94.95-98.9%) for saliva respectively. CONCLUSIONS: The scent cognitive transfer performance between inactivated and non-inactivated samples as well as between different sample materials indicates that global, specific SARS-CoV-2-associated volatile compounds are released across different body secretions, independently from the patient's symptoms. All tested body fluids appear to be similarly suited for reliable detection of SARS-CoV-2 infected individuals.

ß-Propiolactone (BPL)-inactivation of SARS-Co-V-2: In vitro validation with focus on saliva from COVID-19 patients for scent dog training.

ß-Propiolactone (BPL) is an organic compound widely used as an inactivating agent in vaccine development and production, for example for SARS-CoV, SARS-CoV-2 and Influenza viruses. Inactivation of pathogens by BPL is based on an irreversible alkylation of nucleic acids but also on acetylation and cross-linking between proteins, DNA or RNA. However, the protocols for BPL inactivation of viruses vary widely. Handling of infectious, enriched SARS-CoV-2 specimens and diagnostic samples from COVID-19 patients is recommended in biosafety level (BSL)- 3 or BSL-2 laboratories, respectively. We validated BPL inactivation of SARS-CoV-2 in saliva samples with the objective to use saliva from COVID-19 patients for training of scent dogs for the detection of SARS-CoV-2 positive individuals. Therefore, saliva samples and cell culture medium buffered with NaHCO3 (pH 8.3) were comparatively spiked with SARS-CoV-2 and inactivated with 0.1 % BPL for 1 h (h) or 71 h ( ± 1 h) at 2-8 °C, followed by hydrolysis of BPL at 37 °C for 1 or 2 h, converting BPL into non-toxic beta-hydroxy-propionic acid. SARS-CoV-2 inactivation was demonstrated by a titre reduction of up to 10^4 TCID50/ml in the spiked samples for both inactivation periods using virus titration and virus isolation, respectively. The validated method was confirmed by successful inactivation of pathogens in saliva samples from COVID-19 patients. Furthermore, we reviewed the currently available literature on SARS-CoV-2 inactivation by BPL. Accordingly, BPL-inactivated, hydrolysed samples can be handled in a non-laboratory setting. Furthermore, our BPL inactivation protocols can be adapted to validation experiments with other pathogens.

Key feature-cases as virtual patients in education of veterinary neurology.

To provide students of veterinary medicine with the necessary day 1 competences, e-learning offerings are increasingly used in addition to classical teaching formats such as lectures. For example, virtual patients offer the possibility of case-based, computer-assisted learning. A concept to teach and test clinical decision-making is the key feature (KF) approach. KF questions consist of three to five critical points that are crucial for the case resolution. In the current study usage, learning success, usability and acceptance of KF cases as neurological virtual patients should be determined in comparison to the long cases format. Elective courses were offered in winter term 2019/20 and summer term 2020 and a total of 38 virtual patients with neurological diseases were presented in the KF format. Eight cases were provided with a new clinical decision-making application (Clinical Reasoning Tool) and contrasted with eight other cases without the tool. In addition to the evaluation of the learning analytics (e.g., processing times, success rates), an evaluation took place after course completion. After 229 course participations (168 individual students and additional 61 with repeated participation), 199 evaluation sheets were completed. The average processing time of a long case was 53 min, while that of a KF case 17 min. 78% of the long cases and 73% of KF cases were successfully completed. The average processing time of cases with Clinical Reasoning Tool was 19 min. The success rate was 58.3 vs. 60.3% for cases without the tool. In the survey, the long cases received a ranking (1 = very good, 6 = poor) of 2.4, while KF cases received a grade of 1.6, 134 of the respondents confirmed that the casework made them feel better prepared to secure a diagnosis in a real patient. Flexibility in learning (n = 93) and practical relevance (n = 65) were the most frequently listed positive aspects. Since KF cases are short and highlight only the most important features of a patient, 30% (n = 70) of respondents expressed the desire for more specialist information. KF cases are suitable for presenting a wide range of diseases and for training students' clinical decision-making skills. The Clinical Reasoning Tool can be used for better structuring and visualizing the reasoning process.

Canine real-time detection of SARS-CoV-2 infections in the context of a mass screening event.

INTRODUCTION: Previous research demonstrated that medical scent detection dogs have the ability to distinguish SARS-CoV-2 positive from negative samples with high diagnostic accuracy. To deploy these dogs as a reliable screening method, it is mandatory to examine if canines maintain their high diagnostic accuracy in real-life screening settings. We conducted a study to evaluate the performance of medical scent detection dogs under real-life circumstances. METHODS: Eight dogs were trained to detect SARS-CoV-2 RT-qPCR-positive samples. Four concerts with a total of 2802 participants were held to evaluate canines' performance in screening individuals for SARS-CoV-2 infection. Sweat samples were taken from all participants and presented in a line-up setting. In addition, every participant had been tested with a SARS-CoV-2 specific rapid antigen test and a RT-qPCR and they provided information regarding age, sex, vaccination status and medical disease history. The participants' infection status was unknown at the time of canine testing. Safety measures such as mask wearing and distance keeping were ensured. RESULTS: The SARS-CoV-2 detection dogs achieved a diagnostic specificity of 99.93% (95% CI 99.74% to 99.99%) and a sensitivity of 81.58% (95% CI 66.58% to 90.78%), respectively. The overall rate of concordant results was 99.68%. The majority of the study population was vaccinated with varying vaccines and vaccination schemes, while several participants had chronic diseases and were under chronic medication. This did not influence dogs' decisions. CONCLUSION: Our results demonstrate that SARS-CoV-2 scent detection dogs achieved high diagnostic accuracy in a real-life scenario. The vaccination status, previous SARS-CoV-2 infection, chronic disease and medication of the participants did not influence the performance of the dogs in detecting the acute infection. This indicates that dogs provide a fast and reliable screening option for public events in which high-throughput screening is required.

Detection of Post-COVID-19 Patients Using Medical Scent Detection Dogs-A Pilot Study.

There is a growing number of COVID-19 patients experiencing long-term symptoms months after their acute SARS-CoV-2 infection. Previous research proved dogs' ability to detect acute SARS-CoV-2 infections, but has not yet shown if dogs also indicate samples of patients with post-COVID-19 condition (Long COVID). Nine dogs, previously trained to detect samples of acute COVID-19 patients, were confronted with samples of Long COVID patients in two testing scenarios. In test scenario I (samples of acute COVID-19 vs. Long COVID) dogs achieved a mean sensitivity (for acute COVID-19) of 86.7% (95%CI: 75.4-98.0%) and a specificity of 95.8% (95%CI: 92.5-99.0%). When dogs were confronted with Long COVID and negative control samples in scenario IIa, dogs achieved a mean sensitivity (for Long COVID) of 94.4 (95%CI: 70.5-100.0%) and a specificity of 96.1% (95%CI: 87.6-100.0%). In comparison, when acute SARS-CoV-2 positive samples and negative control samples were comparatively presented (scenario IIb), a mean sensitivity of 86.9 (95%CI: 55.7-100.0%) and a specificity of 88.1% (95%CI: 82.7-93.6%) was attained. This pilot study supports the hypothesis of volatile organic compounds (VOCs) being long-term present after the initial infection in post-COVID-19 patients. Detection dogs, trained with samples of acute COVID-19 patients, also identified samples of Long COVID patients with a high sensitivity when presented next to samples of healthy individuals. This data may be used for further studies evaluating the pathophysiology underlying Long COVID and the composition of specific VOC-patterns released by SARS-CoV-2 infected patients throughout the course of this complex disease.

Discrimination of SARS-CoV-2 Infections From Other Viral Respiratory Infections by Scent Detection Dogs.

Background: Testing of possibly infected individuals remains cornerstone of containing the spread of SARS-CoV-2. Detection dogs could contribute to mass screening. Previous research demonstrated canines' ability to detect SARS-CoV-2-infections but has not investigated if dogs can differentiate between COVID-19 and other virus infections. Methods: Twelve dogs were trained to detect SARS-CoV-2 positive samples. Three test scenarios were performed to evaluate their ability to discriminate SARS-CoV-2-infections from viral infections of a different aetiology. Naso- and oropharyngeal swab samples from individuals and samples from cell culture both infected with one of 15 viruses that may cause COVID-19-like symptoms were presented as distractors in a randomised, double-blind study. Dogs were either trained with SARS-CoV-2 positive saliva samples (test scenario I and II) or with supernatant from cell cultures (test scenario III). Results: When using swab samples from individuals infected with viruses other than SARS-CoV-2 as distractors (test scenario I), dogs detected swab samples from SARS-CoV-2-infected individuals with a mean diagnostic sensitivity of 73.8% (95% CI: 66.0-81.7%) and a specificity of 95.1% (95% CI: 92.6-97.7%). In test scenario II and III cell culture supernatant from cells infected with SARS-CoV-2, cells infected with other coronaviruses and non-infected cells were presented. Dogs achieved mean diagnostic sensitivities of 61.2% (95% CI: 50.7-71.6%, test scenario II) and 75.8% (95% CI: 53.0-98.5%, test scenario III), respectively. The diagnostic specificities were 90.9% (95% CI: 87.3-94.6%, test scenario II) and 90.2% (95% CI: 81.1-99.4%, test scenario III), respectively. Conclusion: In all three test scenarios the mean specificities were above 90% which indicates that dogs can distinguish SARS-CoV-2-infections from other viral infections. However, compared to earlier studies our scent dogs achieved lower diagnostic sensitivities. To deploy COVID-19 detection dogs as a reliable screening method it is therefore mandatory to include a variety of samples from different viral respiratory tract infections in dog training to ensure a successful discrimination process.

Scent dog identification of samples from COVID-19 patients - a pilot study.

BACKGROUND: As the COVID-19 pandemic continues to spread, early, ideally real-time, identification of SARS-CoV-2 infected individuals is pivotal in interrupting infection chains. Volatile organic compounds produced during respiratory infections can cause specific scent imprints, which can be detected by trained dogs with a high rate of precision. METHODS: Eight detection dogs were trained for 1 week to detect saliva or tracheobronchial secretions of SARS-CoV-2 infected patients in a randomised, double-blinded and controlled study. RESULTS: The dogs were able to discriminate between samples of infected (positive) and non-infected (negative) individuals with average diagnostic sensitivity of 82.63% (95% confidence interval [CI]: 82.02-83.24%) and specificity of 96.35% (95% CI: 96.31-96.39%). During the presentation of 1012 randomised samples, the dogs achieved an overall average detection rate of 94% (±3.4%) with 157 correct indications of positive, 792 correct rejections of negative, 33 incorrect indications of negative or incorrect rejections of 30 positive sample presentations. CONCLUSIONS: These preliminary findings indicate that trained detection dogs can identify respiratory secretion samples from hospitalised and clinically diseased SARS-CoV-2 infected individuals by discriminating between samples from SARS-CoV-2 infected patients and negative controls. This data may form the basis for the reliable screening method of SARS-CoV-2 infected people.