Publications

The Pestivirus genus comprises species that affect animal health and productivity worldwide. Members of the Suidae family are hosts for classical swine fever virus (CSFV), an important pathogen tracked by the World Organization for Animal Health (OIE). However, swine are also susceptible to other pestivirus species that can result in disease or compromise CSFV detection. We searched for pestivirus infection in swine sera collected from 320 backyard pig herds in southern Brazil. We used reverse-transcription PCR primers for Bungowannah virus; atypical porcine pestivirus (APPV); and a panpestivirus pair that detects bovine viral diarrhea virus (BVDV)-1, -2, and HoBi-like pestivirus (HoBiPeV), border disease virus (BDV), and CSFV. Two samples were positive using the panpestivirus primer pair and were classified as BVDV-1d and -2a, respectively. Serum samples were tested for virus neutralization against BVDV-1a, -1b, and -2 strains, resulting in 28 (4.4%) positive samples. Of those, 16 samples had the highest titers against BVDV-1a (2), BVDV-1b (5), and BVDV-2 (9). Our results indicate that Bungowannah virus, APPV, CSFV, BDV, and HoBiPeV have not been circulating in these specific backyard swine populations. However, ruminant pestiviruses were detected and must be considered in future pestivirus control programs conducted in Brazil.

The performance of five forecasting models was investigated for predicting nursery mortality using the master table built for 3242 groups of pigs (~13 million animals) and 42 variables, which concerned the pre-weaning phase of production and conditions at placement in growing sites. After training and testing each model's performance through cross-validation, the model with the best overall prediction results was the Support Vector Machine model in terms of Root Mean Squared Error (RMSE = 0.406), Mean Absolute Error (MAE = 0.284), and Coefficient of Determination (R2 = 0.731). Subsequently, the forecasting performance of the SVM model was tested on a new dataset containing 72 new groups, simulating ongoing and near real-time forecasting analysis. Despite a decrease in R2 values on the new dataset (R2 = 0.554), the model demonstrated high accuracy (77.78%) for predicting groups with high (>5%) or low (<5%) nursery mortality. This study demonstrated the capability of forecasting models to predict the nursery mortality of commercial groups of pigs using pre-weaning information and stocking condition variables collected post-placement in nursery sites.

ABSTRACT Human seasonal H3 3C3a clade influenza A viruses (IAV) were detected in four U.S. pigs from commercial swine farms in Michigan, Illinois, and Virginia in 2019. To evaluate the relative risk of this spillover to the pig population, whole genome sequencing and phylogenetic characterization was conducted and revealed all eight viral gene segments were closely related to 2018-2019 H3N2 human seasonal IAV. Next, a series of in vitro viral kinetics, receptor binding, and antigenic characterization studies were performed using a representative A/swine/Virginia/A02478738/2018(H3N2) (SW/VA/19) isolate. Viral replication kinetic studies of SW/VA/19 demonstrated less efficient replication curves than all ten swine H3N2 viruses tested, but higher than three human H3N2 strains. Serial passaging experiments of SW/VA/19 in swine cells did not increase virus replication, but changes at HA amino acid positions 9 and 159 occurred. In swine transmission studies, wild type SW/VA/19 was shed in nasal secretions and transmitted to all indirect contact pigs, whereas the human seasonal strain A/Switzerland/9715293/2013(H3N2) from the same 3C3a clade failed to transmit. SW/VA/19 induced minimal macroscopic and microscopic lung lesions. Collectively these findings demonstrate that these human seasonal H3N2 3C3a-like viruses did not require reassortment with endemic swine IAV gene segments, impacting virus shedding and transmission in pigs. Limited detections in the U.S. pig population in the subsequent period of time suggests a yet unknown restriction factor likely limiting the spread of these viruses in the U.S. pig population. IMPORTANCE Interspecies human-to-swine IAV transmission occurs globally and contributes to increased IAV diversity in pig populations. We present data that a swine isolate from a 2018-2019 human-to-swine transmission event was shed for multiple days in challenged and contact pigs. By characterizing this introduction through bioinformatic, molecular, and animal experimental approaches, these findings better inform animal health practices and in vaccine decision-making. Since wholly human seasonal H3N2 viruses in the U.S. were not previously identified as being transmissible in pigs (i.e. reverse zoonosis), these findings reveal the interspecies barriers for transmission to pigs may not require significant changes to all human seasonal H3N2.

Porcine reproductive and respiratory syndrome virus (PRRSV) is the most important swine pathogen affecting the United States of America (USA), leading to significant economic losses. Despite advances in diagnostic testing, there remains a gap in understanding the genetic evolution of PRRSV, especially in tracking the emergence of novel sequences and their spread across different regions and production stages. This research addresses this gap by developing a systematic methodology for directly collecting and analyzing PRRSV ORF5 sequences from veterinary diagnostic laboratories. The study aimed to identify trends among collected sequences and emerging PRRSV sequences by integrating nucleotide sequence data with metadata, providing critical insights into their geographic distribution, collected specimens, swine age groups, lineages, variants, and restriction fragment length polymorphism (RFLP) patterns. As of December 2024, the database housed 115,643 PRRSV ORF5 sequences. Sublineages 1B, 1A, 1H, and 1C.5 were the major wild-type PRRSV sequences detected over time, whereas vaccine-like strains comprised mostly of sublineages 5A and 8A. A novel sequence detection system was implemented, categorizing sequences based on similarity thresholds, ambiguities, and length criteria, identifying 167 novel sequences for the period between 2010 and 2024, whereas only three had continued detection in the field over time, forming clusters of detection. The analysis of these novel sequences highlighted significant trends, including the dominance of grow-finish animals in sequence origin and the high number of detections of sublineage 5A. Production sites located in states with the largest swine inventory have contributed to the most frequent detection of new PRRSV strains. Additionally, the development of a web-based tool provides end users with the capability to search sequences similar to their query sequence, providing macroepidemiological information and genetic sequence features to support PRRSV management and control. Real-time PRRSV sequencing data analysis informs producers and veterinarians of any upcoming novel sequences and trends of detection. The findings are intended to enhance current surveillance efforts and support more effective strategies for managing PRRSV outbreaks, ultimately safeguarding animal health, economic sustainability in the swine industry, and ultimately contributing to national food production sovereignty through pork-derived products.

Swine nursery mortality is one of the most important key performance indicators (KPIs) for commercial swine production systems and, for the purpose of this study, refers to the number of pigs that died during the first 60 days during the post-weaning phase (approximately 170-day period). Likewise, nursery mortality accounts for almost 50% of the mortality that occurs throughout the post-weaning phase. Despite being a metric concerning the post-weaning phase of production, previous studies have demonstrated that nursery mortality is highly correlated with the previous performance of the piglets in the pre-weaning phase and to stocking conditions at placement in nursery sites. However, there is no evidence of that predictive models are currently routinely utilized in the swine industry to predict the nursery performance of individual groups of pigs based on their previous performance in the pre-weaning phase. One obstacle to building such predictive models is that health and management data as well as production data for the pre and post-weaning phases are collected with separate record-keeping programs and stored in unconnected databases. Thus, the objective of this study was to measure and compare the performance of 5 forecasting models for predicting nursery mortality using a master table containing data collected from a single swine production system for 1,831 groups of pigs. An automated model was built to integrate information for 48 variables included in the master table that was previously disconnected within the production system. After the model and parameter tuning process, the model with the best overall prediction performance was the Support Vector Machine (SVM) in terms of Root Mean Squared Error (RMSE=0.3929), Mean Absolute Error (MAE=0.2956), and coefficient of determination (R2=0.7761). This study demonstrated the ability to use an integrated master table containing whole-herd information until the placement event of nursery groups to predict their downstream nursery mortality through the initial 60 days of the post-weaning phase.

Porcine reproductive and respiratory syndrome virus (PRRSV) is a significant cause of economic loss in the swine industry, yet its control remains challenging in wean-to-harvest sites. This prospective observational study followed 95 wean-to-harvest sites across six U.S. states for one production cycle. Sites were required to be PRRSV-negative or vaccinated with a modified live virus (MLV) and free of major coronaviruses. Outbreaks were defined as RT-qPCR-positive in unvaccinated sites or detection of ORF5 sequences distinct from the MLV strain. Biosecurity data were collected through a survey, and oral fluids were tested every four weeks. PRRS outbreaks occurred in 14/42 nurseries (33.3%), 8/12 wean-to-finish (66.7%), and 35/41 finishers (82.4%), with lineage 1C.5 most frequently detected. In univariate models, higher odds of outbreaks were associated with transporting pigs of unknown status (OR 9.80, 1.73–55.37), rendering (OR 6.47, 1.62–25.84), and employee cohabitation (OR 6.15, 1.51–25.09). Protective factors included exclusive pumping equipment (OR 0.07, 0.01–0.43) and overnight downtime for multi-site workers (OR 0.15, 0.04–0.56). In multivariable models, finisher sites (OR 17.47, 2.44–125.19) and greater swine site density within one mile (OR 1.62, 1.09–2.41) significantly increased outbreak odds. These results support targeted biosecurity practices, helping farmers and the swine industry reduce PRRS outbreaks.

Aggregated diagnostic data collected over time from swine production systems is an important data source to investigate swine productivity and health, especially when combined with records concerning the pre-weaning and post-weaning phases of production. The combination of multiple data streams collected over the lifetime of the pigs is the essence of the whole-herd epidemiological investigation. This approach is particularly valuable for investigating the multifaceted and ever-changing factors contributing to wean-to-finish (W2F) swine mortality. The objective of this study was to use a retrospective dataset (“master table”) containing information on 1,742 groups of pigs marketed over time to identify the major risk factors associated with W2F mortality. The master table was built by combining historical breed-to-market performance and health data with disease diagnostic records (Dx Codes) from marketed groups of growing pigs. After building the master table, univariate analyses were conducted to screen for risk factors to be included in the initial multivariable model. After a stepwise backward model selection approach, 5 variables and 2 interactions remained in the final model. Notably, the diagnosis variable significantly associated with W2F mortality was porcine reproductive and respiratory syndrome virus (PRRSV). Closeouts with clinical signs suggestive of Salmonella spp. or Escherichia coli infection were also associated with higher W2F mortality. Source sow farm factors that remained significantly associated with W2F mortality were the sow farm PRRS status, average weaning age, and the average pre-weaning mortality. After testing for the possible interactions in the final model, two interactions were significantly associated with wean-to-finish pig mortality: (1) sow farm PRRS status and a laboratory diagnosis of PRRSV and (2) average weaning age and a laboratory diagnosis of PRRS. Closeouts originating from PRRS epidemic or PRRS negative sow farms, when diagnosed with PRRS in the growing phase, had the highest W2F mortality rates. Likewise, PRRS diagnosis in the growing phase was an important factor in mortality, regardless of the average weaning age of the closeouts. Overall, this study demonstrated the utility of a whole-herd approach when analyzing diagnostic information along with breeding-to-market productivity and health information, to measure the major risk factors associated with W2F mortality in specified time frames and pig populations.

Classical swine fever (CSF) and foot-mouth disease (FMD) are both highly contagious disease and disruptive to commercial trades, but they are examples of foreign animal diseases that biosecurity-based compartmentalization could be used to support trade in free zones in response to an outbreak. This study aimed to evaluate biosecurity compliance to the Federal Normative Instruction #44 from December 4th, 2017 (BRAZIL, 2017) in commercial swine farms located in southern Brazil. A total of 604 swine farms from 10 commercial swine companies were sampled, from which 28.5% were breeding farms, 29.1% nursery, 32.8% finishing, 6.8% multipliers, and 2.8% farrow-to-finish. Cluster analyses revealed that farms with high compliance (n = 303, Cluster 1) performed 71% of the practices, moderate (n = 219, Cluster 2) 47%, and the low (n = 82, Cluster 3) 33%. A spatial logistic regression model estimated that biosecurity compliance was highest in only one of 10 commercial swine companies, and within a company, multipliers (when present) obtained the highest biosecurity compliance (p-value < 0.01). These results suggest that major improvements in biosecurity practices are needed in breeding herds, nursery, and grow-finish farms to be compliant to the Federal Instruction #44. Based on the combination of these analyses, only one commercial swine company was more suitable to establish compartments for CSF and FMD with minimal investments. Still, this study revealed that the majority of commercial swine companies needs to improve biosecurity practice protocols to then target compartmentalization.