The goal of this blog is to register novel indexed papers about PRRS diagnostics, monitoring, control and elimination. This will include: reports of novel or improved diagnostic methods; papers about effictiveness of PRRS vaccines on pig performance, shedding and transmission; important news about PRRS virus structure and applied immunology; and much, much more. Stay tuned and be the first to know!
Department of Animal and Grassland Sciences, Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan; Center for Animal Disease Control, University of Miyazaki, Miyazaki, Japan. Electronic address: email@example.com.
Course of Animal and Grassland Sciences, Graduate School of Agriculture, University of Miyazaki, Miyazaki, Japan.
Feed One Co., Ltd., Kanagawa, Japan.
IDEAS Swine Clinic, Chiba, Japan.
Summit Veterinary Services, Gunma, Japan.
Boehringer Ingelheim Animal Health Japan Co. Ltd., Tokyo, Japan.
It is well known that infectious diseases such as porcine reproductive and respiratory syndrome (PRRS) and porcine epidemic diarrhea (PED) decrease herd productivity and lead to economic loss. It is believed that biosecurity practices are effective for the prevention and control of such infectious diseases. Therefore, the objective of the present study was to investigate whether or not an association between biosecurity level and herd productivity, as well as disease status exists on Japanese commercial swine farms. The present study was conducted on 141 farms. Biosecurity in each farm was assessed by a biosecurity assessment tool named BioAsseT. BioAsseT has a full score of 100 and consists of three sections (external biosecurity, internal biosecurity and diagnostic monitoring). Production data for number of pigs weaned per sow per year (PWSY) and post-weaning mortality per year (PWM) were collected for data analysis. Regarding PRRS status, the farms were categorized into two groups: unknown or unstable and stable or negative. In addition, these farms were categorized based on their PED status, either positive or negative. The total BioAsseT score was associated with herd productivity: as total score increased by 1, PWSY increased by 0.104 pigs and PWM decreased by 0.051 % (P < 0.05). Herd productivity was associated with the score of external and internal biosecurity (P < 0.05), but did not correlate with the score of diagnostic monitoring. Regarding PRRS status, farms with an unknown or unstable status had lower total score than those with stable or negative status (P < 0.05). Similarly, PED positive farms had a lower total score compared to PED negative farms (P < 0.05). In conclusion, the present study provides evidence for the association between high biosecurity levels and increased herd productivity as well as a decreased risk for novel introductions of infectious diseases such as PED.
We isolated and plaque purified IA76950-WT and IA70388-R, 2 porcine reproductive and respiratory syndrome viruses from pigs in the same herd in Iowa, USA, that exhibited coughing and had interstitial pneumonia. Phylogenetic and molecular evolutionary analysis indicated that IA70388-R is a natural recombinant from Fostera PRRSV vaccine and field strain IA76950-WT.
PRRSV; United States; pigs; porcine reproductive and respiratory syndrome virus; recombination; swine; vaccine; viruses; wild type
Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, Iowa, United States of America.
Swine Health Information Center, Ames, Iowa, United States of America.
Veterinary Population Medicine, University of Minnesota, Saint Paul, Minnesota, United States of America.
College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, United States of America.
Veterinary & Biomedical Sciences Department, South Dakota State University, Brookings, South Dakota, United States of America.
This project investigates the macroepidemiological aspects of porcine reproductive and respiratory syndrome virus (PRRSV) RNA detection by veterinary diagnostic laboratories (VDLs) for the period 2007 through 2018. Standardized submission data and PRRSV real-time reverse-transcriptase polymerase chain reaction (RT-qPCR) test results from porcine samples were retrieved from four VDLs representing 95% of all swine samples tested in NAHLN laboratories in the US. Anonymized data were retrieved and organized at the case level using SAS (SAS® Version 9.4, SAS® Institute, Inc., Cary, NC) with the use of PROC DATA, PROC MERGE, and PROC SQL scripts. The final aggregated and anonymized dataset comprised of 547,873 unique cases was uploaded to Power Business Intelligence-Power BI® (Microsoft Corporation, Redmond, Washington) to construct dynamic charts. The number of cases tested for PRRSV doubled from 2010 to 2018, with that increase mainly driven by samples typically used for monitoring purposes rather than diagnosis of disease. Apparent seasonal trends for the frequency of PRRSV detection were consistently observed with a higher percentage of positive cases occurring during fall or winter months and lower during summer months, perhaps due to increased testing associated with well-known seasonal occurrence of swine respiratory disease. PRRSV type 2, also known as North American genotype, accounted for 94.76% of all positive cases and was distributed across the US. PRRSV type 1, also known as European genotype, was geographically restricted and accounted for 2.15% of all positive cases. Co-detection of both strains accounted for 3.09% of the positive cases. Both oral fluid and processing fluid samples, had a rapid increase in the number of submissions soon after they were described in 2008 and 2017, respectively, suggesting rapid adoption of these specimens by the US swine industry for PRRSV monitoring in swine populations. As part of this project, a bio-informatics tool defined as Swine Disease Reporting System (SDRS) was developed. This tool has real-time capability to inform the US swine industry on the macroepidemiological aspects of PRRSV detection, and is easily adaptable for other analytes relevant to the swine industry.
There is a need to develop cost effective approaches to sample large populations in particular to determine the disease status of pigs prior to weaning. In this study we assessed the presence of the porcine reproductive and respiratory syndrome virus (PRRSV) in the environment (surfaces and air) of farrowing rooms, and udder skin of lactating sows as an indirect measure of piglet PRRSV status. Samples were collected at processing and weaning every three weeks for 23 weeks after a PRRSV outbreak was diagnosed in a swine breeding herd. PRRSV was detected at processing in udder skin wipes, environmental wipes and airborne deposited particle samples up to 14 weeks post outbreak and at weaning in udder skin wipes up to 17 weeks post outbreak. Similar sensitivities were observed for udder skin wipes (43% [95% CI: 23%-66%]) and surface wipes (57% [95% CI: 34%-77%]) when compared to serum at the litter level from piglets at processing. PRRSV was detected in the environment and the udder skin of lactating sows, which indicates that aggregate samples of the environment or lactating sows may be used to evaluate the PRRSV status of the herd in pigs prior to weaning. However, the use of environmental samples to detect PRRSV by RT-PCR should not be used as the single method to assess the PRRSV status at the litter level. Furthermore, our findings also highlight potential sources of PRRSV infection for piglets in breeding herds.
Division for Diagnostics & Scientific Advice-Epidemiology, National Veterinary Institute/Centre for Diagnostics-Technical University of Denmark, Lyngby, Denmark.
Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg C, Denmark.
As our capacity to collect and store health data is increasing, a new challenge of transforming data into meaningful information for disease monitoring and surveillance has arisen. The aim of this study was to explore the potential of using livestock mortality and antibiotic consumption data as a proxy for detecting disease outbreaks at herd level. Changes in the monthly records of mortality and antibiotic consumption were monitored in Danish swine herds that became positive for porcine reproductive and respiratory syndrome (PRRS) and porcine pleuropneumonia. Laboratory serological results were used to identify herds that changed from a negative to a positive status for the diseases. A dynamic linear model with a linear growth component was used to model the data. Alarms about state changes were raised based on forecast errors, changes in the growth component, and the values of the retrospectively smoothed values of the growth component. In all cases, the alarms were defined based on credible intervals and assessed prior and after herds got a positive disease status. The number of herds with alarms based on mortality increased by 3% in the 3 months prior to laboratory confirmation of PRRS-positive herds (Se = 0.47). A 22% rise in the number of weaner herds with alarms based on the consumption of antibiotics for respiratory diseases was found 1 month prior to these herds becoming PRRS-positive (Se = 0.22). For porcine pleuropneumonia-positive herds, a 10% increase in antibiotic consumption for respiratory diseases in sow herds was seen 1 month prior to a positive result (Se = 0.5). Monitoring changes in mortality data and antibiotic consumption showed changes at herd level prior to and in the same month as confirmation from diagnostic tests. These results also show a potential value for using these data streams as part of surveillance strategies.
IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Bellaterra, Spain firstname.lastname@example.org.
IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Bellaterra, Spain.
Departament de Sanitat i Anatomia Animals, Facultat Veterinària, Universitat Autònoma de Barcelona, Bellaterra, Spain.
Sows in breeding herds are often mass vaccinated against porcine reproductive and respiratory syndrome (PRRS) every few months using modified live vaccines (MLV). Field veterinarians repeatedly report that multiple vaccinated sows test negative in ELISA. Obviously, this creates uncertainty when assessing the compliance of vaccination and the status of sows.
In the present study, four commercial ELISAs were used to assess the serological PRRS status in gilts and sows of three farms that were PRRS MLV vaccinated every four months. Animals were tested before vaccination (BV) and postvaccination (PV). Total and neutralising antibodies and cell-mediated responses were also measured in animals that yielded negative results in all ELISAs.
The proportion of seronegative animals BV varied depending on the farm and the ELISA used. When samples were analysed using only one ELISA, a substantial number of negative results obtained BV remained as negative afterwards. Five animals were negative BV and PV with all the examined ELISAs. Those animals also yielded negative results in all the other immunological assays.
Our findings suggest that the use of ELISA for monitoring multiple PRRS MLV vaccinated sows is very limited due to the variability of the humoral responses and the moderate agreement between tests.
Investments in biosecurity practices are made by producers to reduce the likelihood of introducing pathogens such as porcine reproductive and respiratory syndrome virus (PRRSv). The assessment of biosecurity practices in breeding herds is usually done through surveys. The objective of this study was to evaluate the use of machine-learning (ML) algorithms to identify key biosecurity practices and factors associated with breeding herds self-reporting (yes or no) a PRRS outbreak in the past 5 years. In addition, we explored the use of the positive predictive value (PPV) of these models as an indicator of risk for PRRSv introduction by comparing PPV and the frequency of PRRS outbreaks reported by the herds in the last 5 years. Data from a case control study that assessed biosecurity practices and factors using a survey in 84 breeding herds in U.S. from 14 production systems were used. Two methods were developed, method A identified 20 variables and accurately classified farms that had reported a PRRS outbreak in the previous 5 years 76% of the time. Method B identified six variables which 5 of these had already been selected by model A, although model B outperformed the former model with an accuracy of 80%. Selected variables were related to the frequency of risk events in the farm, swine density around the farm, farm characteristics, and operational connections to other farms. The PPVs for methods A and B were highly correlated to the frequency of PRRSv outbreaks reported by the farms in the last 5 years (Pearson r = 0.71 and 0.77, respectively). Our proposed methodology has the potential to facilitate producer’s and veterinarian’s decisions while enhancing biosecurity, benchmarking key biosecurity practices and factors, identifying sites at relatively higher risk of PRRSv introduction to better manage the risk of pathogen introduction.