October

• Top publications | October
• Derald J. Holtkamp, DVM, MS; Montserrat Torremorell, DVM, PhD; Cesar A. Corzo, DVM, MS, PhD; Daniel C. L. Linhares, DVM, MBA, PhD; Marcelo N. Almeida, DVM, MS; Paul Yeske, DVM, MS; Dale D. Polson, DVM, MS, PhD; Lisa Becton, DVM; Harry Snelson, DVM; Tara D

A standardized system for classifying the porcine reproductive and respiratory syndrome virus (PRRSV) status of swine herds is necessary for communication between veterinarians and producers. The 2011 classification system has been widely adopted by producers and veterinarians worldwide. In 2018, a working group met to revisit the system and make recommendations for changes. The most significant modification was to the classification of positive unstable and positive stable breeding herds. Recommended diagnostic protocols for promotion of herds to each status were modified and recommended diagnostic protocols to maintain a status were added. The growing pig classification for PRRSV was also modified.

• Top publications | October
• Yiqun Jiang, Qing Li, Giovani Trevisan, Daniel C. L. Linhares, Cameron MacKenzie

Porcine reproductive and respiratory syndrome (PRRS) is a disease caused by the PRRS virus (PRRSV) that has spread globally in the last 30 years and causes huge economic losses every year. This research aims to 1) investigate the relationship between the PRRSV detection in two age categories (wean-to-market and adult/sow farm), and 2) examine the extent to which the wean-to-market PRRSV positive rate forecasts the adult/sow farm PRRSV positive rate. The data we used are the PRRSV RNA detection results between 2007 and 2019 integrated by the US Swine Disease Reporting System project that represent 95% of all porcine submissions tested in the US National Animal Health Network. We first use statistical tools to investigate to what extent the increase in PRRSV positive submissions in the wean-to-market is related to the PRRSV increase in adult/sow farms. The statistical analysis confirms that an increase in the PRRSV positive rate of wean-to-market precedes the increase in the adult/sow farms to a large extent. Then we create the dynamic exponentially weighted moving average control charts to identify out-of-control points (i.e., signals) in the PRRSV rates for both wean-to-market and adult/sow farms. This control-chart-based analysis finds that 78% of PRRSV signals in the wean-to-market are followed by a PRRSV rate signal in the adult/sow farms within eight weeks. We expect that our findings will help the producers and veterinarians to justify and reinforce the implementation of bio-security and bio-contaminant practices to curb disease spread across farms.

• Top publications | October
• Will A. López, Phillip C. Gauger, Karen M. Harmon, Derald J. Holtkamp, Jean Paul Cano, Nubia Macedo, Min Zhang, Gustavo S. Silva, Jose Angulo, Jeffrey J. Zimmerman, Daniel C.L. Linhares

There has been a tremendous increase in recent years of population-based diagnostic monitoring and surveillance strategies in swine populations. One example is the use of processing fluids (PF) to screen breeding herds for porcine reproductive and respiratory syndrome virus (PRRSV) activity. An important question from practitioners using such methods is on how intensively can the sample be pooled. More specifically, processing fluids of how many litters can be pooled into a single sample for diagnostic testing to preserve a high probability of PRRSV RNA detection at low prevalence situations? The objective of this study was to model the effect of pooling PF samples on the probability of PRRSV RNA detection. For this study, a PRRSV-positive PF field sample with a RT-rtPCR quantification cycle (Cq) value of 28 was selected to represent a litter of 11 pigs with a single viremic piglet. PF samples from a PRRSV-naïve herd were used to perform 6 replications of 8 two-fold serial dilutions of the PRRSV-positive sample, thus modeling the pooling effect (dilution). Each two-fold dilution represented an increase in the number of PRRS-negative pigs in the sample by a factor of 2. Samples were tested for PRRSV RNA by RT-rtPCR and the data was analyzed using linear and probit regression models. There was an average increment of 1.37 points in Ct for each two-fold dilution. The estimated probability of testing positive on RT-rtPCR was 43 %, 80 %, and 95 % when there was a single PRRSv-positive piglet among 784, 492, and 323 PRRSv-negative piglets contributing to the sample respectively. Results from this study support the practice of collecting and aggregating PF samples from multiple litters for PRRSV RNA testing.