Canine olfactory detection of SARS-CoV-2-infected humans-a systematic review.

PURPOSE: To complement conventional testing methods for severe acute respiratory syndrome coronavirus type 2 infections, dogs' olfactory capability for true real-time detection has been investigated worldwide. Diseases produce specific scents in affected individuals via volatile organic compounds. This systematic review evaluates the current evidence for canine olfaction as a reliable coronavirus disease 2019 screening tool. METHODS: Two independent study quality assessment tools were used: the QUADAS-2 tool for the evaluation of laboratory tests' diagnostic accuracy, designed for systematic reviews, and a general evaluation tool for canine detection studies, adapted to medical detection. Various study design, sample, dog, and olfactory training features were considered as potential confounding factors. RESULTS: Twenty-seven studies from 15 countries were evaluated. Respectively, four and six studies had a low risk of bias and high quality: the four QUADAS-2 nonbiased studies resulted in ranges of 81%-97% sensitivity and 91%-100% specificity. The six high-quality studies, according to the general evaluation system, revealed ranges of 82%-97% sensitivity and 83%-100% specificity. The other studies contained high bias risks and applicability and/or quality concerns. CONCLUSIONS: Standardization and certification procedures as used for canine explosives detection are needed for medical detection dogs for the optimal and structured usage of their undoubtful potential.

Co-exposure to Anaplasma spp., Coxiella burnetii and tick-borne encephalitis virus in sheep in southern Germany.

The intracellular bacteria Anaplasma spp. and Coxiella burnetii and the tick-borne encephalitis virus (TBEV) are tick-transmitted pathogens circulating in the southern German sheep population. Knowledge of interaction among Anaplasma spp., C. burnetii and TBEV in sheep is lacking, but together they might promote and reinforce disease progression. The current study aimed to identify co-exposure of sheep to Anaplasma spp., C. burnetii and TBEV. For this purpose, 1,406 serum samples from 36 sheep flocks located in both southern German federal states, Baden-Wuerttemberg and Bavaria, were analysed by ELISAs to determine the antibody levels of the three pathogens. Inconclusive and positive results from the TBEV ELISA were additionally confirmed by a serum neutralisation assay. The proportion of sheep with antibodies against Anaplasma spp. (47.2%), C. burnetii (3.7%) and TBEV (4.7%) differed significantly. Significantly more flocks with Anaplasma spp. seropositive sheep (91.7%) were detected than flocks with antibodies against TBEV (58.3%) and C. burnetii (41.7%), but there was no significant difference between the number of flocks which contained TBEV and C. burnetii seropositive sheep. Seropositivity against at least two pathogens was detected in 4.7% of sheep from 20 flocks. Most co-exposed sheep had antibodies against Anaplasma spp./TBEV (n = 36), followed by Anaplasma spp./C. burnetii (n = 27) and Anaplasma spp./C. burnetii/TBEV (n = 2). Only one sheep showed an immune response against C. burnetii and TBEV. Flocks with sheep being positive against more than one pathogen were widely distributed throughout southern Germany. The descriptive analysis revealed no association between the antibody response of the three pathogens at animal level. Taking the flocks as a cluster variable into account, the exposure to TBEV reduced the probability of identifying C. burnetii antibodies in sheep significantly (odds ratio 0.46; 95% confidence interval 0.24-0.85), but the reason for this is unknown. The presence of Anaplasma spp. antibodies did not influence the detection of antibodies against C. burnetii and TBEV. Studies under controlled conditions are necessary to evaluate any possible adverse impact of co-exposure to tick-borne pathogens on sheep health. This can help to clarify rare disease patterns. Research in this field may also support the One Health approach due to the zoonotic potential of Anaplasma spp., C. burnetii and TBEV.

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.

Surveillance of Coxiella burnetii Shedding in Three Naturally Infected Dairy Goat Herds after Vaccination, Focusing on Bulk Tank Milk and Dust Swabs.

Q fever outbreaks on three dairy goat farms (A-C) were monitored after the animals had been vaccinated with an inactivated Coxiella burnetii phase I vaccine. The antibody response was measured before vaccination by serum samples with two C. burnetii phase-specific ELISAs to characterize the disease status. Shedding was determined by vaginal swabs during three kidding seasons and monthly bulk tank milk (BTM) samples. Dust swabs from one windowsill of each barn and from the milking parlors were collected monthly to evaluate the indoor exposure. These samples were analyzed by qPCR. The phase-specific serology revealed an acute Q fever infection in herd A, whereas herds B and C had an ongoing and past infection, respectively. In all three herds, vaginal shedders were present during three kidding seasons. In total, 50%, 69%, and 15% of all collected BTM samples were C. burnetii positive in herds A, B, and C, respectively. Barn dust contained C. burnetii DNA in 71%, 45%, and 50% of examined swabs collected from farms A, B, and C, respectively. The largest number of C. burnetii positive samples was obtained from the milking parlor (A: 91%, B: 72%, C: 73%), indicating a high risk for humans to acquire Q fever during milking activity.

An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus - evaluating six conditionally dependent tests.

Latent class analysis is a widely used statistical method for evaluating diagnostic tests without any gold standard. It requires the results of at least two tests applied to the same individuals. Based on the resulting response patterns, the method estimates the test accuracy and the unknown disease status for all individuals in the sample. An important assumption is the conditional independence of the tests. If tests with the same biological principle are used, the assumption is not fulfilled, which may lead to biased results. In a recent publication, we developed a method that considers the dependencies in the latent class model and estimates all parameters using frequentist methods. Here, we evaluate the practicability of the method by applying it to the results of six ELISA tests for antibodies against the porcine reproductive and respiratory syndrome (PRRS) virus in pigs that generally follow the same biological principle. First, we present different methods of identifying suitable starting values for the algorithm and apply these to the dataset and a vaccinated subgroup. We present the calculated values of the test accuracies, the estimated proportion of antibody-positive animals and the dependency structure for both datasets. Different starting values led to matching results for the entire dataset. For the vaccinated subgroup, the results were more dependent on the selected starting values. All six ELISA tests are well suited to detect antibodies against PRRS virus, whereas none of the tests had the best values for sensitivity and specificity simultaneously. The results thus show that the method used is able to determine the parameter values of conditionally dependent tests with suitable starting values. The choice of test should be based on the general fit-for-purpose concept and the population under study.

Impact of Coxiella burnetii vaccination on humoral immune response, vaginal shedding, and lamb mortality in naturally pre-infected sheep.

Introduction: Sheep are considered to be one of the main reservoirs for Coxiella burnetii, a gram-negative bacterium with high zoonotic potential. Infected sheep shed tremendous amounts of the pathogen through birth products which caused human Q fever epidemics in several countries. Information about the impact of an inactivated C. burnetii Phase I vaccine on humoral immune response, vaginal shedding, and lamb mortality in naturally pre-infected sheep is scarce. Methods: Two identically managed and naturally C. burnetii-infected sheep flocks were examined for two lambing seasons (2019 and 2020). One flock (VAC) received a primary vaccination against Q fever before mating and the second flock served as control (CTR). In each flock, one cohort of 100 ewes was included in follow-up investigations. Serum samples at eight different sampling dates were analyzed by C. burnetii phase-specific ELISAs to differentiate between the IgG Phase I and II responses. Vaginal swabs were collected within three days after parturition and examined by a C. burnetii real-time PCR (IS1111). Lamb losses were recorded to calculate lamb mortality parameters. Results: After primary vaccination, almost all animals from cohort VAC showed a high IgG Phase I response up until the end of the study period. In cohort CTR, the seropositivity rate varied from 35.1% to 66.3%, and the Phase I and Phase II pattern showed an undulating trend with higher IgG Phase II activity during both lambing seasons. The number of vaginal shedders was significantly reduced in cohort VAC compared to cohort CTR during the lambing season in 2019 (p < 0.0167). There was no significant difference of vaginal shedders in 2020. The total lamb losses were low in both cohorts during the two investigated lambing seasons (VAC 2019: 6.8%, 2020: 3.2%; CTR 2019: 1.4%, 2020: 2.7%). Discussion: Neither the C. burnetii vaccine nor the C. burnetii infection seem to have an impact on lamb mortality. Taken together, the inactivated C. burnetii Phase I vaccine induced a strong IgG Phase I antibody response in naturally pre-infected sheep. It might also reduce vaginal shedding in the short term but seems to have little beneficial impact on lamb mortality.

Seroprevalence and Risk Factors of Anaplasma spp. in German Small Ruminant Flocks.

Knowledge about the distribution of Anaplasma spp. in small ruminants from Germany is limited. Therefore, serum samples were examined from 71 small ruminant flocks (2731 sheep, 447 goats) located in the five German federal states: Schleswig-Holstein (SH), Lower Saxony (LS), North Rhine-Westphalia (NRW), Baden-Wuerttemberg (BW) and Bavaria (BAV). Antibodies to Anaplasma spp. were determined by a cELISA based on the MSP5 antigen. A risk factor analysis at animal and flock level was also performed. Antibodies to Anaplasma spp. were detected in 70/71 flocks without significant difference in the intra-flock prevalence (IFP) between the federal states. The mean antibody levels from sheep were significantly lower in northern Germany (LS, SH) compared to west (NRW) and south Germany (BW, BAV). Sheep had a 2.5-fold higher risk of being seropositive than goats. Females and older animals (>2 years) were more likely to have antibodies to Anaplasma spp. in one third and one quarter of cases, respectively. Flocks used for landscape conservation had a five times higher risk of acquiring an IFP greater than 20%. Cats and dogs on the farms increased the probability for small ruminant flocks to have an IFP of above 20% 10-fold and 166-fold, respectively. Further studies are necessary to assess the impact of Anaplasma species on the health of small ruminants in Germany.

Concept of an Active Surveillance System for Q Fever in German Small Ruminants-Conflicts Between Best Practices and Feasibility.

Q fever is a zoonotic disease caused by the bacterium Coxiella burnetii. Inhalation of contaminated dust particles or aerosols originating from animals (esp. small ruminants) is the main source of human infection. Hence, an active early warning system for Q fever in German small ruminant livestock was conceptualized to prevent human infections. First, we describe the best practice for establishing this system before evaluating its feasibility, as the combination of both evokes conflicts. Vaginal swabs from all husbandry systems with a focus on reproductive females should pooled and investigated by PCR to detect C. burnetii-shedding animals. Multistage risk-based sampling shall be carried out at the flock level and within-flock level. At the flock level, all flocks that are at risk to transmit the pathogen to the public must be sampled. At the within-flock level, all primi- and multiparous females after lambing must be tested in order to increase the probability of identifying a positive herd. Sampling should be performed during the main lambing period and before migration in residential areas. Furthermore, individual animals should be tested before migration or exhibition to ensure a negative status. If a flock tests positive in at least one individual sample, then flock-specific preventive measures should be implemented. This approach implies huge financial costs (sample testing, action/control measures). Hence, taking the step to develop more feasible and affordable preventive measures, e.g., vaccinating small ruminant flocks, should replace testing wherever justifiable.

An Iterative, Frequentist Approach for Latent Class Analysis to Evaluate Conditionally Dependent Diagnostic Tests.

Latent class analysis is a well-established method in human and veterinary medicine for evaluating the accuracy of diagnostic tests without a gold standard. An important assumption of this procedure is the conditional independence of the tests. If tests with the same biological principle are used, this assumption is no longer met. Therefore, the model has to be adapted so that the dependencies between the tests can be considered. Our approach extends the traditional latent class model with a term for the conditional dependency of the tests. This extension increases the number of parameters to be estimated and leads to negative degrees of freedom of the model, meaning that not enough information is contained in the existing data to obtain a unique estimate. As a result, there is no clear solution. Hence, an iterative algorithm was developed to keep the number of parameters to be estimated small. Given adequate starting values, our approach first estimates the conditional dependencies and then regards the resulting values as fixed to recalculate the test accuracies and the prevalence with the same method used for independent tests. Subsequently, the new values of the test accuracy and prevalence are used to recalculate the terms for the conditional dependencies. These two steps are repeated until the model converges. We simulated five application scenarios based on diagnostic tests used in veterinary medicine. The results suggest that our method and the Bayesian approach produce similar precise results. However, while the presented approach is able to calculate more accurate results than the Bayesian approach if the test accuracies are initially misjudged, the estimates of the Bayesian method are more precise when incorrect dependencies are assumed. This finding shows that our approach is a useful addition to the existing Bayesian methods, while it has the advantage of allowing simpler and more objective estimations.

Health scores for farmed animals: Screening pig health with register data from public and private databases.

There are growing demands to ensure animal health and, from a broader perspective, animal welfare, especially for farmed animals. In addition to the newly developed welfare assessment protocols, which provide a harmonised method to measure animal health during farm visits, the question has been raised whether data from existing data collections can be used for an assessment without a prior farm visit. Here, we explore the possibilities of developing animal health scores for fattening pig herds using a) official meat inspection results, b) data on antibiotic usage and c) data from the QS (QS Qualität und Sicherheit GmbH) Salmonella monitoring programme in Germany. The objective is to aggregate and combine these register-like data into animal health scores that allow the comparison and benchmark of participating pig farms according to their health status. As the data combined in the scores have different units of measure and are collected in different abattoirs with possibly varying recording practices, we chose a relative scoring approach using z-transformations of different entrance variables. The final results are aggregated scores in which indicators are combined and weighted based on expert opinion according to their biological significance for animal health. Six scores have been developed to describe different focus areas, such as "Respiratory Health", "External Injuries/ Alterations", "Animal Management", "Antibiotic Usage", "Salmonella Status" and "Mortality". These "focus" area scores are finally combined into an "Overall Score". To test the scoring method, existing routine data from 1,747 pig farm units in Germany are used; these farm units are members of the QS Qualität und Sicherheit GmbH (QS) quality system. In addition, the scores are directly validated for 38 farm units. For these farm units, the farmers and their veterinarians provided their perceptions concerning the actual health status and existing health problems. This process allowed a comparison of the scoring results with actual health information using kappa coefficients as a measure of similarity. The score testing of the focus area scores using real information resulted in normalised data. The results of the validation showed satisfactory agreement between the calculated scores for the project farm units and the actual health information provided by the related farmers and veterinarians. In conclusion, the developed scoring method could become a viable benchmark and risk assessment instrument for animal health on a larger scale under the conditions of the German system.