Comparison of a novel rapid sampling method to serum and tonsil scraping to detect PRRSV in acutely infected sows.

Few practical methods are available to monitor the PRRSV status of the sows. Common sampling methods for sows like serum sampling, and tonsil scraping involve restraining individual sows and are labor-intensive, time-consuming, relatively invasive, and therefore, have limited use in large-scale production settings. Thus, a practical and rapid method of sampling large numbers of sows is needed. This study aimed to develop a new sampling method, named tonsil-oral scraping (TOSc) and compare TOSc to serum and tonsil scraping in terms of PRRSV qPCR detection rate and Ct values in thirty matched sows, thirty days after PRRSV outbreak. TOSc recovered a mixture of oral fluids and tonsil exudates from the sow oral cavity within seconds without restraining the animals. Results showed that, numerically, the TOSc samples had higher PRRSV qPCR detection rate (100 %) compared to serum (16.8 %) and tonsil scraping (73.1 %). Moreover, TOSc samples had lower average Ct values (29.7) than tonsil scraping (30.7) and serum (35.2). There was no significant difference in the detection rate between TOSc and tonsil scraping (Tukey test, p = 0.992), while there was a significant difference between serum and tonsil scraping (Tukey test, p < 0.001), as well as between serum and TOSc (Tukey test, p < 0.001). In terms of Ct values, there was no statistically significant difference between TOSc and tonsil scrapings (Dunn Test, p > 0.05), while there was a significant difference between tonsil scraping with serum (Dunn Test, p < 0.01), and TOSc with serum (Dunn Test, p < 0.01). Our results suggest great potential of the TOSc as a novel, practical, and rapid tool for PRRSV RNA detection in sows to assess sow herd status.

Assessment of temperature and time on the survivability of porcine reproductive and respiratory syndrome virus (PRRSV) and porcine epidemic diarrhea virus (PEDV) on experimentally contaminated surfaces.

Fomites might be responsible for virus introduction in swine farms, highlighting the importance of implementing practices to minimize the probability of virus introduction. The study's objective was to assess the efficacy of different combinations of temperatures and holding-times on detecting live PRRSV and PEDV on surfaces commonly found in supply entry rooms in swine farms. Two PRRSV isolates (MN 184 and 1-4-4 L1C variant) and one PEDV isolate (NC 49469/2013) were inoculated on cardboard and aluminum. An experimental study tested combinations of four temperatures (20°C, 30°C, 40°C, and 50°C) and six holding-times (15 minutes, 60 minutes, 6 hours, 12 hours, 24 hours, and 36 hours) for the presence of the viruses on each surface type. After virus titration, virus presence was assessed by assessing the cytopathic effects and immunofluorescence staining. The titers were expressed as log10 TCID50/ml, and regression models; half-lives equations were calculated to assess differences between treatments and time to not detect the live virus. The results suggest that the minimum time that surfaces should be held to not detect the virus at 30°C was 24 hours, 40°C required 12 hours, and 50°C required 6 hours; aluminum surfaces took longer to reach the desired temperature compared to cardboard. The results suggest that PRRSV 1-4-4 L1C variant had higher half-lives at higher temperatures than PRRSV MN 184. In conclusion, time and temperature combinations effectively decrease the concentration of PRRSV and PEDV on different surfaces found in supply entry rooms in swine farms.

A cross-sectional assessment of PRRSV nucleic acid detection by RT-qPCR in serum, ear-vein blood swabs, nasal swabs, and oral swabs from weaning-age pigs under field conditions.

Introduction: The porcine reproductive and respiratory syndrome virus (PRRSV) continues to challenge swine production in the US and most parts of the world. Effective PRRSV surveillance in swine herds can be challenging, especially because the virus can persist and sustain a very low prevalence. Although weaning-age pigs are a strategic subpopulation in the surveillance of PRRSV in breeding herds, very few sample types have been validated and characterized for surveillance of this subpopulation. The objectives of this study, therefore, were to compare PRRSV RNA detection rates in serum, oral swabs (OS), nasal swabs (NS), ear-vein blood swabs (ES), and family oral fluids (FOF) obtained from weaning-age pigs and to assess the effect of litter-level pooling on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of PRRSV RNA. Methods: Three eligible PRRSV-positive herds in the Midwestern USA were selected for this study. 666 pigs across 55 litters were sampled for serum, NS, ES, OS, and FOF. RT-qPCR tests were done on these samples individually and on the litter-level pools of the swabs. Litter-level pools of each swab sample type were made by combining equal volumes of each swab taken from the pigs within a litter. Results: Ninety-six piglets distributed across 22 litters were positive by PRRSV RT-qPCR on serum, 80 piglets distributed across 15 litters were positive on ES, 80 piglets distributed across 17 litters were positive on OS, and 72 piglets distributed across 14 litters were positive on NS. Cohen's kappa analyses showed near-perfect agreement between all paired ES, OS, NS, and serum comparisons (). The serum RT-qPCR cycle threshold values (Ct) strongly predicted PRRSV detection in swab samples. There was a ≥ 95% probability of PRRSV detection in ES-, OS-, and NS pools when the proportion of positive swab samples was ≥ 23%, ≥ 27%, and ≥ 26%, respectively. Discussion: ES, NS, and OS can be used as surveillance samples for detecting PRRSV RNA by RT-qPCR in weaning-age pigs. The minimum number of piglets to be sampled by serum, ES, OS, and NS to be 95% confident of detecting ≥ 1 infected piglet when PRRSV prevalence is ≥ 10% is 30, 36, 36, and 40, respectively.

In-silico characterization of the relationship between the Porcine reproductive and respiratory syndrome virus prevalence at the piglet and litter levels in a farrowing room.

BACKGROUND: Family oral fluids (FOF) sampling has been described as a sampling technique where a rope is exposed to sows and respective suckling litters and thereafter wrung to obtain fluids. PCR-based testing of FOF reveals presence of PRRS virus RNA only at the litter level, as opposed to conventional individual-animal-based sampling methods that demonstrate PRRSV RNA at the piglet level. The relationship between the PRRSV prevalence at the individual piglet level and at the litter level in a farrowing room has not been previously characterized. Using Monte Carlo simulations and data from a previous study, the relationship between the proportion of PRRSV-positive (viremic) pigs in the farrowing room, the proportion of litters in the farrowing room with at least one viremic pig, and the likely proportion of litters to be positive by a FOF RT-rtPCR test in a farrowing room was characterized, taking into account the spatial distribution (homogeneity) of viremic pigs within farrowing rooms. RESULTS: There was a linear relationship between piglet-level- and litter-level prevalence, where the latter was always larger than the former. When the piglet-level prevalence was 1%, 5%, 10%, 20%, and 50%, the true-litter level prevalence was 5.36%, 8.93%, 14.29%, 23.21%, and 53.57%, respectively. The corresponding apparent-litter prevalence by FOF was 2.06%, 6.48%, 11.25%, 21.60%, and 51.56%, respectively. CONCLUSION: This study provides matching prevalence estimates to help guide sample size calculations. It also provides a framework to estimate the likely proportion of viremic pigs, given the PRRSV RT-rtPCR positivity rate of FOF samples submitted from a farrowing room.

Evaluating oral swab samples for PRRSV surveillance in weaning-age pigs under field conditions.

Introduction: The use of serum and family oral fluids for porcine reproductive and respiratory syndrome virus (PRRSV) surveillance in weaning-age pigs has been previously characterized. Characterizing more sample types similarly offers veterinarians and producers additional validated sample options for PRRSV surveillance in this subpopulation of pigs. Oral swab sampling is relatively easy and convenient; however, there is sparse information on how it compares to the reference sample type for PRRSV surveillance under field conditions. Therefore, this study's objective was to compare the PRRSV reverse-transcription real-time polymerase chain reaction (RT-rtPCR) test outcomes of oral swabs (OS) and sera samples obtained from weaning-age pig litters. Method: At an eligible breeding herd, six hundred twenty-three weaning-age piglets from 51 litters were each sampled for serum and OS and tested for PRRSV RNA by RT-rtPCR. Results and Discussion: PRRSV RT-rtPCR positivity rate was higher in serum samples (24 of 51 litters, 83 of 623 pigs, with a mean cycle threshold (Ct) value of RT-rtPCR-positive samples per litter ranging from 18.9 to 32.0) compared to OS samples (15 of 51 litters, 33 of 623 pigs, with a mean Ct of RT-rtPCR positive samples per litter ranging from 28.2 to 36.9); this highlights the importance of interpreting negative RT-rtPCR results from OS samples with caution. Every litter with a positive PRRSV RT-rtPCR OS had at least one viremic piglet, highlighting the authenticity of positive PRRSV RT-rtPCR tests using OS; in other words, there was no evidence of environmental PRRSV RNA being detected in OS. Cohen's kappa analysis (Ck = 0.638) indicated a substantial agreement between both sample types for identifying the true PRRSV status of weaning-age pigs.

Porcine reproductive and respiratory syndrome virus RNA detection in tongue tips from dead animals.

The control of porcine reproductive and respiratory syndrome virus (PRRSV) hinges on monitoring and surveillance. The objective of this study was to assess PRRSV RNA detection by RT-PCR in tongue tips from dead suckling piglets compared to serum samples, processing fluids, and family oral fluids. Tongue tips and serum samples were collected from three PRRSV-positive breeding herd farms (farms A, B, and C) of three different age groups: newborns (<24 h), processing (2 to 7 days of age), and weaning (18 to 22 days of age). Additionally, processing fluids and family oral fluids were collected from 2-7 days of age and weaning age, respectively. In farms A and B, PRRSV RNA was detected in tongue tips from all age groups (100 and 95%, respectively). In addition, PRRSV RNA was detected in pooled serum samples (42 and 27%), processing fluids (100 and 50%), and family oral fluids (11 and 22%). Interestingly, the average Ct value from tongue tips was numerically lower than the average Ct value from serum samples in the newborn age. In farm C, PRRSV RNA was only detected in serum samples (60%) and family oral fluids (43%), both from the weaning age. Further, no PRRSV RNA was detected in tongue tips when pooled serum samples from the same age group tested PRRSV RNA-negative. Taken together, these results demonstrate the potential value of tongue tips for PRRSV monitoring and surveillance.

Effect of pooling family oral fluids on the probability of PRRSV RNA detection by RT-rtPCR.

Family oral fluids (FOFs) are an aggregate sample type shown to be a cost-efficient and convenient option for determining the porcine reproductive and respiratory syndrome virus (PRRSV) status of weaning age pigs. This study investigates the effect of pooling PRRSV-positive FOF samples with PRRSV-negative FOF samples at different levels (1/3, 1/5, 1/10, 1/20) on the probability of PRRSV RNA detection by reverse-transcription real-time polymerase chain reaction (RT-rtPCR). Mathematical models were built to assess how much the probability of RT-rtPCR PRRSV detection changed with increasing proportion of PRRSV-positive samples present within pools and how partially sampling a farrowing room influenced the probability of RT-rtPCR detection of PRRSV RNA in pooled samples at different prevalence scenarios. A general example of a guideline for FOF-based sampling under different prevalence scenarios to detect PRRSV RNA by RT-rtPCR with at least 95 % certainty is presented. At the sample level, the probability of detecting PRRSV RNA by RT-rtPCR decreased from 100 % to 87 %, 68 %, and 26 % when diluting up to 1/20 for PRRSV positive FOF having an initial Cycle threshold (Ct) below 34, between 34 and 36, or above 36, respectively. When PRRSV prevalence is near-zero (1 or 2 litters positive out of 56), the most cost-efficient farrowing room sampling strategy to detect PRRSV RNA with at least 95 % certainty was pooling FOF samples up to 1/10; at higher prevalence (≥ 3 of 56 litters positive), the most cost-efficient strategy was submitting samples in pools of 20. Subsampling a farrowing room for FOF pools was also demonstrated to be a valuable cost-saving strategy. Overall, based on the conditions of this study, pooling FOFs up to 1/20 is a valid option in situations of cost constraint and regardless of pooling level chosen, capturing as many litters as possible improves the probability of PRRSV detection.

Interpretable machine learning applied to on-farm biosecurity and porcine reproductive and respiratory syndrome virus.

Effective biosecurity practices in swine production are key in preventing the introduction and dissemination of infectious pathogens. Ideally, on-farm biosecurity practices should be chosen by their impact on bio-containment and bio-exclusion; however, quantitative supporting evidence is often unavailable. Therefore, the development of methodologies capable of quantifying and ranking biosecurity practices according to their efficacy in reducing disease risk has the potential to facilitate better-informed choices of biosecurity practices. Using survey data on biosecurity practices, farm demographics, and previous outbreaks from 139 herds, a set of machine learning algorithms were trained to classify farms by porcine reproductive and respiratory syndrome virus status, depending on their biosecurity practices and farm demographics, to produce a predicted outbreak risk. A novel interpretable machine learning toolkit, MrIML-biosecurity, was developed to benchmark farms and production systems by predicted risk and quantify the impact of biosecurity practices on disease risk at individual farms. By quantifying the variable impact on predicted risk, 50% of 42 variables were associated with fomite spread while 31% were associated with local transmission. Results from machine learning interpretations identified similar results, finding substantial contribution to predicted outbreak risk from biosecurity practices relating to the turnover and number of employees, the surrounding density of swine premises and pigs, the sharing of haul trailers, distance from the public road and farm production type. In addition, the development of individualized biosecurity assessments provides the opportunity to better guide biosecurity implementation on a case-by-case basis. Finally, the flexibility of the MrIML-biosecurity toolkit gives it the potential to be applied to wider areas of biosecurity benchmarking, to address biosecurity weaknesses in other livestock systems and industry-relevant diseases.

Household and animal factors associated with sheeppox and goatpox sero-prevalence and identification of high-risk areas in selected States of northern Nigeria.

Sheeppox and goatpox (SGP) are transboundary, highly contagious diseases affecting sheep and goats with characteristic clinical signs. SGP affect populations of small ruminants in Africa, Asia and the Middle East and, as a result, threaten farmers' livelihoods. Despite their importance, studies looking at factors that increase the risk of sheeppox-virus (SPPV) and goatpox-virus (GTPV) exposure and infection are limited. A cross-sectional study was conducted in three states of Northern Nigeria (Bauchi, Kaduna and Plateau) to determine the sero-prevalence and spatial patterns of SGP, and identify risk factors for SPPV/GTPV exposure at animal and household level. Sera samples were collected from 1,800 small ruminants from 300 households. Data on putative risk factors were collected using a standardised questionnaire. Twenty-nine small ruminants were sero-positive to SGP - apparent weighted sero-prevalence 2.0 %; 95 % C.I. 1.1-.3.0 %. Sero-positive animals came from 19 (6.3 %) households. Analysis of the questionnaire showed that a fifth (20.3 %) of farmers claimed to have experienced SGP outbreaks previously in their flocks, with 33 (1.8 %) of the individual animals sampled in this study reported to have had clinical signs. At animal level, the odds of being sero-positive were higher in older animals (>24months; OR = 8.0, p = 0.008 vs ≤24 months) and small ruminants with a history of clinical SGP (OR = 16.9, p = 0.01). Bringing new small ruminants into the household and having a history of SGP in the flock were the main factors identified at household level. Households were less likely to be sero-positive if the time between bringing animals into the household and sampling was over a year (PR = 0.31, p = 0.05), while households with a history of SGP were more likely to be sero-positive regardless of the timeframe. Important spatial heterogeneity was found. The Bayes smooth rate ranged from 0.06 to 4.10 % across local government areas (LGA), with LGA in the north-east or north-west of the study area identified as hot-spots for SGP exposure. Results from this study shed new light on the understanding of SGP epidemiology and provide key inputs to design risk-based surveillance and intervention programmes in the area.