Global trends in infectious diseases of swine

Dr. Kim VanderWaal and Dr. John Deen from the University of Minnesota co-authored a new publication available now in the Proceedings of the National Academy of Sciences of the United States of America.

The objectives of this study were to identify priority swine pathogens, characterize temporal and geographic trends in research priorities.

57,471 publications covering 40 swine pathogens, compiled from 3 major database searches and dating from 1966 to 2016 were included in this analysis.

The top 10 pathogens published on were:

  • Salmonella spp.
  • Escherichia coli
  • Influenza
  • Pseudorabies
  • Foot and Mouth Disease
  • Porcine Reproductive and Respiratory Syndrome
  • Classical Swine Fever
  • Actinobacillus pleuropneumoniae
  • Trichinella spp.
  • African Swine Fever

The number of publications on swine infectious diseases increased over time as the hog production intensified. However, 8 pathogens increased faster than expected, particularly in the past 15 years: hepatitis E virus, Nipah virus, influenza, Streptococcus suisLawsonia intracellularis, porcine circovirus 2, PRRS, and PED.

On the contrary, some diseases had a slower growth in number of publications than expected. These included pseudorabies, Pasteurella multocida, Actinobacillus pleuropneumoniae, Brachyspira hyodysenteriae, and transmissible gastroenteritis virus. All of these pathogens were production diseases whose importance to the industry had declined in recent decades due to better control or even regional eradication.

Differences among world regions were identified except for influenza virus which appeared in the top 5 in most regions of the world. Southern regions where extensive hog production may still be the norm, tended to focus more on parasitic infections compared to Northern areas. Western Europe centered more on pathogens related to zoonotic and foodborne concerns compared to Northern America.

Read more about the evolution of publications on swine infectious diseases around the world.


Pork accounts for more than one-third of meat produced worldwide and is an important component of global food security, agricultural economies, and trade. Infectious diseases are among the primary constraints to swine production, and the globalization of the swine industry has contributed to the emergence and spread of pathogens. Despite the importance of infectious diseases to animal health and the stability and productivity of the global swine industry, pathogens of swine have never been reviewed at a global scale. Here, we build a holistic global picture of research on swine pathogens to enhance preparedness and understand patterns of emergence and spread. By conducting a scoping review of more than 57,000 publications across 50 years, we identify priority pathogens globally and regionally, and characterize geographic and temporal trends in research priorities. Of the 40 identified pathogens, publication rates for eight pathogens increased faster than overall trends, suggesting that these pathogens may be emerging or constitute an increasing threat. We also compared regional patterns of pathogen prioritization in the context of policy differences, history of outbreaks, and differing swine health challenges faced in regions where swine production has become more industrialized. We documented a general increasing trend in importance of zoonotic pathogens and show that structural changes in the industry related to intensive swine production shift pathogen prioritization. Multinational collaboration networks were strongly shaped by region, colonial ties, and pig trade networks. This review represents the most comprehensive overview of research on swine infectious diseases to date.

Breed-to-wean farm factors associated with influenza A virus infection in piglets at weaning

A scientific article written by Dr. Fabian Chamba Pardo when he was doing his PhD in the Torremorell lab was recently published on the journal of Preventive Veterinary Medicine. The study presented aimed to look at the various factors influencing the influenza infection status of piglets at weaning.


  • Sow vaccination decreased influenza infections in piglets at weaning.
  • Influenza positive gilts at entry were associated with positive piglets at weaning.
  • More work is needed to assess herd closure, gilt isolation and gilt vaccination.

83 farms from 2 different pig production companies and located in Iowa, Minnesota and South Dakota were enrolled in this study. Samples were collected at weaning on a monthly basic for a little less than 6 years as part of routine surveillance programs. The majority of farms submitted 4 oral fluid samples per month but some collected nasal swabs or oro-pharyngeal swabs.

23% of the samples tested positive for influenza allowing the collection of 173 hemagglutinin sequences. In the H1 hemagglutinin subtype, isolates were 93.8% to 99% similar between each other and 94.3% to 97.4% similar to the vaccine strains. The largest discrepancy was found in the delta 1 clade. In the H3 hemagglutinin subtype, isolates were 95.9 to 99.7% similar among each other and 997.3% to 97.5% similar to the vaccine strains.

influenza factors for piglet positive at weaning

The influenza status of the piglets at weaning was influenced by several factors.

Seasons and vaccination status of the sows against influenza influenced piglet infection status at weaning. Indeed, sow influenza vaccination was significantly associated  with a decreased probability of piglets testing influenza positive at weaning. Both whole-herd and pre-farrow vaccination protocols were better compared to no vaccination and there were no differences between both protocols. Additionally, having influenza positive gilts at entry increased the probability of detecting positive piglets at weaning.

Among all the factors evaluated, sow influenza vaccination and gilt influenza status at entry were the only factors associated with influenza in piglets at weaning in Midwestern breed-to-wean farms.


Breed-to-wean pig farms play an important role in spreading influenza A virus (IAV) because suckling piglets maintain, diversify and transmit IAV at weaning to other farms. Understanding the nature and extent of which farm factors drive IAV infection in piglets is a prerequisite to reduce the burden of influenza in swine. We evaluated the association between IAV infection in piglets at weaning and farm factors including farm features, herd management practices and gilt- and piglet-specific management procedures performed at the farm. Voluntarily enrolled breed-to-wean farms (n = 83) agreed to share IAV diagnostic testing and farm data from July 2011 through March 2017 including data obtained via the administration of a survey. There were 23% IAV RT-PCR positive samples of the 12,814 samples submitted for IAV testing within 2989 diagnostic submissions with 30% positive submissions. Among all the factors evaluated (n = 24), and considering the season-adjusted multivariable analysis, only sow IAV vaccination and gilt IAV status at entry significantly reduced (p-value<0.05) IAV infections in piglets at weaning. Results from this study indicate that veterinarians and producers could manage these identified factors to reduce the burden of influenza in piglets prior to wean and perhaps, reduce the spread of IAV to other farms and people.

Read the entire publication on the journal website.


Use of processing fluids and serum samples to characterize PRRSv dynamics in 3 day-old pigs

This new publication in Veterinary Microbiology describes the best methodology to monitor 3-day-old piglets for PRRS, using both serum and processing fluid samples. The first author of the publication is Dr. Carles Vilalta, member of the Morrison Swine Health Monitoring Program (MSHMP) team.

Key points

  • Processing fluids (PF) constitute a useful sample to detect PRRSV infections at processing.
  • PRRSV can circulate in the farm at a low prevalence, increasing the chances of a re-break.
  • Young parity female litters should be targeted for PRRSV detection.
  • Current practice to bleed 30 pigs could be underestimating PRRSV prevalence in the herd.
  • The decrease in sensitivity at the litter level can be compensated by sampling more litters to detect PRRSV at the herd level.


The study was conducted in a 6,000 sow farm with a PRRS stable status. Every 3 weeks, serum samples and processing fluids were collected from all piglets in 10 randomly chosen litters. This process was then repeated 8 times, meaning that the farm was monitored for a total of 24 weeks. All samples were tested via PCR. 3 samples with the lowest Ct value were tested by virus isolation and sequencing of the ORF5 gene was performed.


10.6% of the piglets tested positive for PRRSv via serum PCR, representing 29.8% of the litters. The same number of litters tested positive via processing fluid PCR testing.

The percentage of processing fluid positive samples was significantly higher is parity 1 and 2 sows compared to parity 3 and older sows. Additionally, a significant association between parity and probability of detecting a positive pig was observed.

A significant higher proportion of positive serum samples was observed in males compared to females. A similar trend was obtained when comparing positive Ct values by gender with values from males being lower (i.e., higher viral load) than those from females.

ct value processing fluids versus serum samples PRRS
Cycle threshold (Ct) positive (≤35) and suspect (between >35 and 40) value distribution for serum (S, triangle) and processing fluid (P, circle) samples overtime (2, 5, 8, 11, 14, 17, 20 and 23 weeks post outbreak). Horizontal black lines indicate the mean Ct values for each week and sample type

Using a Ct value of 37, processing fluid samples had a Se and Sp of 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%), respectively when compared with litter RT-PCR results obtained from individual serum samples. The total agreement between both tests was 92.2% and the positive and negative predictive values were 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%), respectively. False negative processing fluids were identified in litters having 2 or less PRRSV positive piglets

The agreement between the PF and serum results was kappa = 0.81 (95% CI: 0.59–1.00). The difference in the proportion of positive samples between both types of sample was not statistically significant (McNemar test, p = 1).


Collection of serum samples of pigs at weaning to monitor for porcine reproductive and respiratory syndrome virus (PRRSV) has become a common practice to determine PRRSV herd infection status. Diagnostic sensitivity of this practice is low in herds undergoing PRRSV elimination once prevalence of infection is near zero. Thus, the goal of this study was to characterize the dynamics of PRRSV infection in 3 day-old pigs overtime using serum and serosanguineous fluids obtained as part of castration and tail docking practices (processing fluids (PF)). Secondary goal was to estimate sensitivity and specificity of PF in the 3 day old population. A 6000 breed-to-wean sow herd was monitored every three weeks for 23 weeks after a PRRSV outbreak by collecting both PF and individual serum samples from all pigs in the selected litters. Out of the 77 litters tested, 23 (29.8%) were identified as positive using the PF and the serum samples, with a Cohen’s kappa statistic of 0.81 (95% CI: 0.59–1) between the results obtained in each sample type. The sensitivity and specificity of the PF relative to the results in serum was 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%) respectively. The percentage of PRRSV positive litters decreased over time and litters from gilts were more likely to test positive than those from older sows. Overall, the study demonstrates that PF can be a convenient and reliable specimen to monitor PRRSV infection in breeding herds.

Follow the link to read the entire article.

Pioneering Structural Study of Porcine Coronavirus

Today, we are highlighting the research of a completely different team at the University of Minnesota. The Minnesota Supercomputing Institute provides advanced research computing infrastructure and expertise to advance and accelerate research and foster innovation and discoveries.

MSI PIs Wei Zhang (research associate professor, Diagnostic and Biological Sciences) and Fang Li (associate professor, Veterinary and Biomedical Sciences) have published a new paper that describes some of their continuing research into the structure of coronaviruses. These are a large group of viruses that includes such deadly diseases as SARS and MERS. Coronaviruses have four forms, known as α-, β-, γ-, and δ-coronavirus, which affect different hosts. For example, β-coronaviruses affect only mammals, while the δ form affects both birds and mammals.

The coronavirus structure includes a feature called a “spike protein,” which allows the virus to attach to the host’s cells. The spike proteins of α- and β-coronavirus have been well studied. The spike protein of the δ-coronavirus, however, is described for the first time in this paper. The researchers used cryo-electron microscopy, a fast-developing technology in which protein molecules are studied under ultra-cold temperatures with an electron microscope. This technology was used to determine the structure of the spike protein of porcine δ-coronavirus (PdCoV), a lethal virus infecting pigs, elucidating how PdCoV infects pigs cells and evades the host immune system. This is the first atomic-resolution cryo-electron microscopic study from the state of Minnesota, and is a milestone in the structural biology field at the University of Minnesota.

Zhang Li spike protein porcine deltacoronavirus

Image Description: Overall structure of PdCoV S-e in the prefusion conformation. (A) Schematic drawing of PdCoV S-e (spike ectodomain). S1, receptor-binding subunit. S2, membrane fusion subunit. GCN4-His6, GCN4 trimerization tag followed by His6 tag. S1-NTD, N-terminal domain of S1. S1-CTD, C-terminal domain of S1. CH-N and CH-C, central helices N and C. FP, fusion peptide. HR-N and HR-C, heptad repeats N and C. Residues in shaded regions (N terminus, GCN4 tag, and His6 tag) were not traced in the structure. (B) Cryo-EM maps of PdCoV S-e with atomic model fitted in. The maps have a contour of 6.6 σ. (C) Cryo-EM structure of prefusion PdCoV S-e. Each of the monomeric subunits is colored differently. (D) Structure of a monomeric subunit in the prefusion conformation. The structural elements are colored in the same way as those in panel A. Image and description, J Shang et al., J Virol. 92:e01556-17 (2018). © American Society for Microbiology.

The paper was published in late 2017 on the website of the Journal of Virology: J Shang, Y Zhang, Y Yang, Q Geng,W Tai, L Du, Y Zhou, W ZhangF Li. 2018. Cryo-Electronic Microscopy Structure of Porcine Deltacoronavirus Spike Protein in the Prefusion StateJournal of Virology 92 (4): e01556-17. doi: 10.1128/JVI.01556-17.

This report comes from the MSI research highlights.


Time-series analysis for porcine reproductive and respiratory syndrome in the United States

Today, we are sharing an open-access publication from Dr. Andreia Arruda, Dr. Ana Alba and members of the MSHMP team in the journal PlosOne.

This study was conducted using data collected from the Morrison Swine Health Monitoring Project. The main objective of this study was to use time-series analysis to investigate whether yearly patterns commonly described for PRRS were in fact conserved across different U.S. states.


The 268 breeding herds enrolled in this project were the ones that participated in the MSHMP from July 2009 to October 2016. PPRS status of each farm was reported weekly following the AASV guidelines. The five states examined included Minnesota (MN), Iowa (IA), North Carolina (NC), Nebraska (NE), and Illinois (IL).


81 MN farms, 72 IA, 45 NC, 30 NE, 40 from IL, were enrolled in the study with a mean number of animals per site of 2,666; 3,543; 2,342; 4,041; and 4,018 respectively.

Graphs showing the prevalence (black line) and upper and lower 95% confidence intervals (grey dotted lines) of PRRS virus positive farms for the five different U.S. states participating in this study: A: Minnesota; B: Iowa; C: Nebraska, D: North Carolina and E: Illinois

The main finding of this study was that PRRS seasonality varies according to geographical region, and the commonly referred “PRRS season” is not necessarily the only time of increase in disease incidence.

Another interesting finding from this study was the presence of an alternating trend for all examined states within of the U.S., except for the state of Iowa, the largest pork producing states in the country (approximately 31.4% of the total US hog and pig inventory), which had an increasing linear trend over the examined years.

In conclusion, PRRS seasonal patterns are not homogeneous across the U.S., with some important pork producing states having biannual PRRS peaks instead of the previously reported winter peak. Findings from this study highlight the importance of coordinating alternative control strategies in different regions considering the prevailing epidemiological patterns, and the need to reinforce strict biosecurity practices beyond the typically described “PRRS season”.

You can also listen to Dr. Arruda present some of these research findings at the 2017 Leman conference.


Industry-driven voluntary disease control programs for swine diseases emerged in North America in the early 2000’s, and, since then, those programs have been used for monitoring diseases of economic importance to swine producers. One example of such initiatives is Dr. Morrison’s Swine Health Monitoring Project, a nation-wide monitoring program for swine diseases including the porcine reproductive and respiratory syndrome (PRRS). PRRS has been extensively reported as a seasonal disease in the U.S., with predictable peaks that start in fall and are extended through the winter season. However, formal time series analysis stratified by geographic region has never been conducted for this important disease across the U.S. The main objective of this study was to use approximately seven years of PRRS incidence data in breeding swine herds to conduct time-series analysis in order to describe the temporal patterns of PRRS outbreaks at the farm level for five major swine-producing states across the U.S. including the states of Minnesota, Iowa, North Carolina, Nebraska and Illinois. Data was aggregated retrospectively at the week level for the number of herds containing animals actively shedding PRRS virus. Basic descriptive statistics were conducted followed by autoregressive integrated moving average (ARIMA) modelling, conducted separately for each of the above-mentioned states. Results showed that there was a difference in the nature of PRRS seasonality among states. Of note, when comparing states, the typical seasonal pattern previously described for PRRS could only be detected for farms located in the states of Minnesota, North Carolina and Nebraska. For the other two states, seasonal peaks every six months were detected within a year. In conclusion, we showed that epidemic patterns are not homogeneous across the U.S, with major peaks of disease occurring through the year. These findings highlight the importance of coordinating alternative control strategies in different regions considering the prevailing epidemiological patterns.