Translating big data into smart data for veterinary epidemiology: the MSHMP perspective

Big data can be defined as the daunting accumulation of abundant and diverse information. While recording data is the first step to measure progress or quickly identify an issue, the large amount of information collected can make it difficult to analyze.

At the University of Minnesota, one of the main projects using big data is the Morrison’s Swine Health Monitoring Program. This ongoing project collects veterinary reports and diagnostic results from numerous swine producers on a daily basis. The compiled information is then analyzed, interpreted and reported back as smart data to the participants every week. Smart data is commonly defined as a piece of information useful enough to make educated decisions.


Data pipeline utilized by the Morrison Swine Health Monitoring Project.jpg
Data pipeline used by the Morrison Swine Health Monitoring project for generating near real-time insight about the incidence of PRRSV


The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing “big” data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having “big data” to create “smart data,” with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

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Several influenza A genotypes detected in the same farm, sub-population, and pig

In this collaborative open-access research article from the University of Minnesota, five commercial sow farms were sampled regularly over a year. Sows, gilts, and piglets was sampled with nasal swabs. A little less than 5% of the samples were PCR positive for influenza A. The strains were classified in 7 groups based on their hemagglutinin (a surface protein of the virus) sequences. One additional group was created based on another gene segment.

Complete genome sequencing influenza A Diaz 2017

Several viral groups were detected in the sub-populations of all of the 5 farms, as shown in the figure below. Influenza strains combined segments from several viral groups were detected in three farms. Additionally, several strains were detected in individual animals showing the potential for reassortment and creation of new influenza strains.

Complete genome sequencing influenza A Diaz 2017 group
Influenza viral groups (VG) detected in each farm sub-populations over time (PG:piglets, GL: gilts, NG: new gilts)   *: month during which sampling started.


Influenza A viruses (IAVs) are endemic in swine and represent a public health risk. However, there is limited information on the genetic diversity of swine IAVs within farrow-to-wean farms, which is where most pigs are born. In this longitudinal study, we sampled 5 farrow-to-wean farms during a year and collected 4,190 individual nasal swabs from three distinct pig subpopulations. 207 (4.9%) samples tested PCR positive for IAV, and 124 IAVs were isolated. We sequenced the complete genome of 123 IAV isolates, and found 31 H1N1, 26 H1N2, 63 H3N2 and 3 mixed IAVs. Based on the IAV hemagglutinin seven different influenza A viral groups (VGs) were identified. Most of the remaining IAV gene segments allowed us to differentiate the same VGs although an additional viral group was identified for gene segment 3 (PA). Moreover, the co-detection of more than one IAV VG was documented at different levels (farm, subpopulation, and individual pigs) highlighting the environment for potential IAV reassortment. Additionally, three out of 5 farms contained IAV isolates (n=5) with gene segments from more than one VG, and 79% of all IAVs sequenced contained a signature mutation (S31N) in the matrix gene that has been associated with resistance to the antiviral amantadine. Within farms, some IAVs were only detected once while others were detected for 283 days. Our results illustrate the maintenance and subsidence of different IAVs within swine farrow-to-wean farms over time, demonstrating that pig subpopulation dynamics is important to better understand the diversity and epidemiology of swine IAVs.

IMPORTANCE At the global scale swine are one of the main reservoir species for influenza A viruses (IAVs), and play a key role on the transmission of IAVs between species. Additionally, the 2009 IAV pandemics highlighted the role of pigs in the emergence of IAVs with pandemic potential. However, limited information is available regarding the diversity and distribution of swine IAVs in farrow-to-wean farms where novel IAVs can emerge. In this study we studied 5 swine farrow-to-wean farms during a year and characterized the genetic diversity of IAVs among three different pig subpopulations commonly housed in this type of farms. Using next generation sequencing technologies, we demonstrated the complex distribution and diversity of IAVs among the pig subpopulations studied. Our results demonstrated the dynamic evolution of IAVs within farrow-to-wean farms, which is crucial to improve health interventions to reduce the risk of transmission between pigs and from pigs to people.

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Infection dynamics and genetic variability of Mycoplasma hyopneumoniae in self-replacement gilts

This is a new research paper from the MycoLab under Dr. Maria Pieters’ supervision. In this study, the group looked at the infection dynamics and genetic variability of Mycoplasma hyopneumoniae in self-replacement gilts, in 3 positive herds. Serum samples were taken from the gilts at 150 days of age onward and laryngeal swabs were collected from the gilts and their progeny.

Highlights of this project

  • Genetic variability of M. hyopneumoniae was evaluated using MLVA typing.
  • The highest M. hyopneumoniae prevalence in gilts was detected at 150 days of age.
  • Detection patterns for M.hyopneumoniae were different among farms.
  • Genetic variability was identified within and among farms.


Pieters 2017 infection dynamics Mhyop


The aim of this study was to assess the longitudinal pattern of M. hyopneumoniae detection in self-replacement gilts at various farms and to characterize the genetic diversity among samples. A total of 298 gilts from three M. hyopneumoniae positive farms were selected at 150 days of age (doa). Gilts were tested for M. hyopneumoniae antibodies by ELISA, once in serum at 150 doa and for M. hyopneumoniae detection in laryngeal swabs by real time PCR two or three times. Also, 425 piglets were tested for M. hyopneumoniae detection in laryngeal swabs. A total of 103 samples were characterized by Multiple Locus Variable-number tandem repeats Analysis. Multiple comparison tests were performed and adjusted using Bonferroni correction to compare prevalence of positive gilts by ELISA and real time PCR. Moderate to high prevalence of M. hyopneumoniae in gilts was detected at 150 doa, which decreased over time, and different detection patterns were observed among farms. Dam-to-piglet transmission of M. hyopneumoniae was not detected. The characterization of M. hyopneumoniae showed 17 different variants in all farms, with two identical variants detected in two of the farms. ELISA testing showed high prevalence of seropositive gilts at 150 doa in all farms. Results of this study showed that circulation of M. hyopneumoniae in self-replacement gilts varied among farms, even under similar production and management conditions. In addition, the molecular variability of M. hyopneumoniae detected within farms suggests that in cases of minimal replacement gilt introduction bacterial diversity maybe farm specific.

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Survival of porcine coronaviruses in feed ingredients and impact of feed additives

A lot of research has been done at the University of Minnesota regarding the survival of porcine coronaviruses in the feed and how to impact their survival. We are presenting today two papers published this spring looking at this important topic. First, Trudeau et al. showed that the feed ingredient which lead to the longest porcine coronaviruses’ survivability was soybean meal. Then, Cottingim et al. showed that some feed additives could inactivate PDCoV.

Importance of porcine coronaviruses and their relationship to swine feed

Porcine coronaviruses of importance in the swine industry nowadays are Porcine Epidemic Diarrhea virus (PEDV), Transmissible Gastroentiritis virus (TGEV), and Porcine Delta Coronavirus (PDCoV). All cause enteric issues in swine and some can lead to up to 100% mortality in nursing piglets. The role of feed ingredients in spreading PEDV and causing outbreaks in Northern America in 2013 has been questioned since then.

Survival of PEDV, TGEV, and PDCoV in complete feed and feed ingredients

The first research project evaluated the persistence of PEDV, TGEV, and PDCoV in porcine feed and feed ingredients. To do so, complete feed and major feed ingredients samples (spray dried porcine plasma, meat meal, meat and bone meal, blood meal, corn,
soybean meal, and corn dried distillers grains with solubles) where inoculated with PEDV, TGEV, or PDCoV and kept for up to 56 days. Aliquots were tested 11 times between the inoculation day and the end of the trial. Time necessary to reduce the viral concentration by 1 log was recorded.

Soybean meal took the longest time to attain the reduction in concentration for all of the coronaviruses, reaching 7.5 days for PEDV, and 42 days for both PDCoV and TGEV. This study also demonstrated that there was a modest positive correlation between moisture content and persistence of TGEV and PDCoV. On the other end, there was a moderate negative correlation between ether extract content and TGEV survival, not observed with the other two viruses.

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Trudeau coronavirus feed swine survival PED

Feed additives and PDCoV survival

In this second project, the survival of PDCoV was evaluated after being put in contact with nursery feed samples containing one of six different commercial feed acids (UltraAcid P, Activate DA, KEMGEST, Acid Booster, Luprosil, and Amasil), salt, or sugar. Acids were added following the recommended concentrations in the first part of the experiment and then, were double-dosed. Feed samples were inoculated with PDCoV and kept for up to 35 days. Like in the previous article, days to achieve a reduction of virus concentration by 1 log were recorded.

At recommended values, there was no difference between viral load reduction in feed samples with or without additives. When acids were added to the feed at a double concentration, the time period to attain the reduction in viral load was decreased to 0.28 days or less for all acids except for Amasil which increased it to 4.95 days (control: 0.35 days). The difference between acidifiers may be explained by the active ingredients used in the products. Furthermore, the addition of salt decreased PDCoV survival whereas sugar increased it.

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Cottingim feed additives survival PDCoV coronavirus swine


Detection of Mycoplasma hyopneumoniae in naturally infected gilts over time

A longitudinal study to assess Mycoplasma hyopneumoniae natural infection in gilts

This study was conducted by Dr. Karine Takeuti under the supervision of Dr. Maria Pieters from the University of Minnesota, College of Veterinary Medicine. The objective was to sample replacement gilts from 20 days of age until the day before weaning to detect Mycoplasma hyopneumoniae . Laryngeal swabs, tested by PCR, were taken every 30 days at a Mycoplasma positive sow farm. Therefore, the animals were naturally infected.

Gilts were found positive at 110 days, no detection in piglets

11.4% of the gilts were found positive at 110 days whereas all the previous samples came back negative. Positive results peaked at 140 days when 36.4% of the samples were positive for Mycoplasma hyopneumoniae. 27.3% of the gilts got positive results twice or more during the sampling period but 18.2% of the animals remained negative for the duration of the study.  All of the 220 piglets samples were also negative.

Takeuti longitudinal gilt mycoplasma hyopneumoniae 2017

Mycoplasma hyopneumoniae causes a chronic respiratory infection in pigs and its transmission occurs mainly by direct contact and by vertical transmission (sow-to-piglet). The objective of this study was to assess the detection dynamics and persistence of M. hyopneumoniae natural infection in replacement gilts. Forty-four twenty-day-old gilts were selected from a M. hyopneumoniae positive farm and followed up to one day prior to their first weaning. Laryngeal swabs were collected every 30 days, starting at day 20, for M. hyopneumoniae detection by real-time PCR, resulting in 12 samplings. Piglets born to selected females were sampled via laryngeal swabs one day prior to weaning to evaluate sow-to-piglet transmission. The M. hyopneumoniae prevalence was estimated at each one of the 12 samplings in gilts and a multiple comparison test and Bonferroni correction were performed. Bacterial detection in gilts started at 110 days of age (doa) and a significant increase (p < 0.05) occurred at 140 doa. The M. hyopneumoniae prevalence remained above 20% from 140 to 230 doa, decreasing thereafter. However, it did not reach 0% at any sampling after 110 doa. In this study, M. hyopneumoniae was not detected in piglets sampled prior to weaning. The M. hyopneumoniae detection pattern showed that in natural infections, gilts were positive for M. hyopneumoniae for one to three months, but occasionally long-term detection may occur. Moreover, the lack of M. hyopneumoniae detection throughout the study in 18.2% of gilts indicated the existence of negative subpopulations in positive herds.

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Mycoplasma hyorhinis prevalence varies based on pigs’ age


  • Mycoplasma hyorhinis can cause polyserositis and arthritis in post-weaning pigs.
  • To study M.hyorhinis‘ prevalence based on age, nasal swabs were taken from pigs at 1, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70 and 77 days as well as from sows, in 3 different Minnesotan herds (A, B, and C).
  • 8.8% of the sows were positive for M.hyorhinis in herds A and B whereas 3.3% of the sows were positive in herd C.
  • The percentage of positive piglets (<21 days of age) was low: between 0 and 10% depending on the herds.
  • At 28 days of age, the prevalence of M.hyorhinis in pigs increased dramatically to around 50% in herd A and 100% in herd B. After 42 days of age, the prevalence in those herds stayed above 95%.
  • The prevalence in herd C stayed close to 0% until the pigs reached the age of 77 days, time at which the prevalence increased to 100%.

Did you see our Science page on Mycoplasma hyorhinis and swine conjunctivitis?

Mhyorhinis prevalence baed on age Rovira 2017


Mycoplasma hyorhinis is one of the causative agents of polyserositis and arthritis in postweaning pigs. Knowledge regarding colonization frequency and age distribution in modern pig production is lacking. The objective of this study was to estimate the prevalence of M hyorhinis colonization in different age groups across three commercial pig populations. Nasal swabs were collected from sows, piglets and nursery pigs of different ages. Oral fluids were collected from nursery pigs. Necropsies were performed to assess the presence of M hyorhinis-associated disease. M hyorhinis was detected in 5/60 sows in herd A, 3/60 in herd B and none in herd C. In herd A and B, the prevalence was low in preweaning piglets (∼8 per cent) and high in postweaning pigs (∼98 per cent). A total of 7/8 oral fluids tested PCR positive in herds A and B, while 1/8 tested positive in herd C. In herd C, the preweaning and postweaning prevalence was low. In herds A and B, necropsied pigs had polyserositis lesions where M hyorhinis was detected by PCR. This study showed that prevalence of M hyorhinis colonization varies with pig age and across farms. Information generated will aid in the design and implementation of control and prevention strategies.

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Detecting Senecavirus A in tissues: development of a new diagnostic test at the University of Minnesota


In Canada and the USA alike, Senecavirus A is a challenge for producers and veterinarians because of its clinical similarity to Food and Mouth Disease (FMD). Indeed, Senecavirus A, is a causative agent of swine vesicular disease with lesions developing on the snout, around the mouth and on the coronary band of the feet. Therefore, being able to differentiate Senecavirus A infections from FMD rapidly is of utmost importance to be able to take the appropriate measures.

In the past months, several diagnostic tests have been developed at the University of Minnesota to detect antibodies against Senecavirus A. The difference between those tests and the in situ hybridization (ISH) described here is that ISH targets the genetic material included in the viral particle and marks it as a red spot as can be seen on the figure below. This advantage of this method is to be able to locate the virus and gives additional information to researcher wanting to study the behavior of Senecavirus A in the body of the pig.

in situ hybridization senecavirus A pigs
Red dots and clusters represent the presence of SVV mRNA within an erosive lesion on the tongue of a pig © 2017 Resende et al.


Seneca Valley virus (SVV) is the causative agent of an emerging vesicular disease in swine, which is clinically indistinguishable from other vesicular diseases such as foot-and-mouth disease. In addition, SVV has been associated with neonatal mortality in piglets. While a commercial SVV qRT-PCR is available, commercial antibodies are lacking to diagnose SVV infections by immunohistochemistry (IHC). Thus, a novel in situ hybridization technique—RNAscope (ISH) was developed to detect SVVRNA in infected tissues. From a total of 78 samples evaluated, 30 were positive by qRT-PCR and ISH-RNA, including vesicular lesions of affected sows, ulcerative lesions in the tongue of piglets and various other tissues with no evidence of histological lesions. Nineteen samples were negative for SVV by qRT-PCR and ISH-RNA. The Ct values of the qRT-PCR from ISH-RNA positive tissues varied from 12.0 to 32.6 (5.12 x 106 to 5.31 RNA copies/g, respectively). The ISH-RNA technique is an important tool in diagnosing and investigating the pathogenesis of SVV and other emerging pathogens.

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