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

Abstract

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.

Review the full article

Science Page: Mycoplasma hyopneumoniae detection in nylon flocked and rayon bud swabs

This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.

Sterile swabs are used to collect clinical samples from the pig’s respiratory tract. Research studies have shown that the sensitivity of respiratory pathogens detection can vary depending on the type of swab used for sample collection.

The objective of this study was to compare two types of commercial swabs for M. hyopneumoniae detection by real-time PCR.

nylon versus rayon swabs mycoplasma hyopneumoniae 2017.gif
Mycoplasma hyopneumoniae detection by real-time PCR. Results shown are Ct values.

Keypoints:

  • Absorption and detection of M. hyopneumoniae in nylon flocked swabs was significantly higher than rayon bud swabs.
  • Nylon flocked swabs could be suggested to use in chronic infections where the bacterial load could be low.

See the full report for more information on the absorption levels of the two different types of swabs.

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.

Abstract

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.

Link to the full open-access article

Science Page: Antibiotic susceptibility in Pasturella multocida and Streptococcus suis isolated at the Minnesota VDL

This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.

Antimicrobial resistance has been a preoccupying topic for the past few years. We talked before about what the definition of antibiotic resistance is and how it can be interpreted in two different manners. This week, Dr. Alvarez from the STEMMA lab is reporting the trends in antimicrobial susceptibility observed in strains of Streptococcus suis and Pasteurella multocida isolated at the Minnesota Veterinary Diagnostic Laboratory over the past 10 years. S. suis and P. multocida are common swine pathogens that can cause severe economic losses. Knowing which antibiotics are more likely to be efficient against those bacteria can help in tackling the disease faster.

Key Points:

  • MN-VDL data was analyzed to study antibiotic susceptibility in clinical isolates of Pasteurella multocida and Streptococcus suis from 2006 to 2016.
  • Isolates were highly susceptible to Ampicillin, Ceftiofur, Enrofloxacin and Florfenicol throughout the study period.
  • There were no changes in antibiotic susceptibility against the antibiotics tested routinely across the study period.

The full report can be read here.

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

Abstract:

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.

Access to the full version of the paper

Science Page: Are the farms that broke with PED the same?

This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.

This week, we are proud to introduce a new chart in the Morrison’s Swine Health Monitoring Project. This new addition will be able to answer a common question regarding PEDV outbreaks:

Are the farms currently breaking with PEDV the same than the ones which broke in the past?

To interpret the figure, follows these steps.

  • Horizontal axis represents all the farms that borke with PEDV during the season 2016/2017, with each tick representing an individual farm
  • Vertical axis shows the previous seasons with 2016-2017 on top and 2012-2013 at the very bottom.
  • The color of the cell (year : farm) represents the number of outbreaks experienced; darker blue meaning more outbreaks.

Here is the example of this chart presented this week:

MSHMP PEDV chart
Outbreak history of farms that broke during the 2016-2017 season.

Key points:

The farms that break with PEDV do not appear to have a history of PEDV infections in the prior season.

Of the farms that broke during the 2016/17 season, only 5 (6.5%) of them had outbreaks during the previous season and 43 (56.6%) of them had broken at some point since 2013.

Only one farm has had an outbreak every year since the beginning of the epidemic in the US (season 2013/14).

The full report is available.

Science Page: Detecting influenza virus with a portable device

This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.

We are presenting today the work done in Dr. Cheeran’s lab on the detection of influenza virus in farms. The objective of their research project is to develop a portable diagnostic platform that is capable of performing on-site testing of influenza viruses in swine with minimum sample handling and laboratory skill requirements.

The device is using giant magnetoresistance (GMR) technology. In a nutshell, if influenza viruses are present in the sample, they will bind to sensors, cause a disruption in resistance, and create an electric signal in the device that will be able to wirelessly transmit the result to a smartphone or computer.

Key points from this week edition:

  • Portable, hand held device for detection of influenza A virus (IAV) based on giant magnetoresistance (GMR) biosensor has been developed.
  • Although in its developmental stage, if successful this test has the potential for rapid on-site testing of influenza viruses in swine.

The first sensitivity tests of the device look very promising!