Science page: How farm structure and demography impact disease detection

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’s edition reports the latest research on modeling the spread of swine vesicular diseases based on farm structure and number of sites. The model was then used to establish an expected time to detection. Two virus strains (high versus low virulence) were evaluated with the model to assess how the strain would influence the time to detection in a farm.

Key points from this week edition:

  • The models showed that the virus persisted longer in farms with a farrowing unit.
  • It is more difficult to diagnose FMD when the strains cause low mortality or no mortality.

Click on the link to see the details about disease spread models.

 

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.

Click on the banner below to access the full article in open access.

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.

Click on the banner below to access the full article in open access.

Cottingim feed additives survival PDCoV coronavirus swine

 

Science page: Comparing EWMAs

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.

But first, we would like to congratulate our 4th-year student Hunter Baldry for receiving the ZinPro scholarship in recognition of her accomplishments as a food-animal student at the University of Minnesota. Keep up the good work, Hunter!

This week, the Science Page answers one of your questions: Is the trend of PRRSV outbreaks recorded for the original 13 participants still related to the PRRSV outbreaks evolution monitored for all the MSHMP participants?

Key points from this week edition:

  • The EWMA of the original 13 participating systems is still a good representation of the overall EWMA.
  • Questions from participants are always welcome!

Reminder: What is the EWMA?

The Exponential Weighted Moving Average (EMWA) is a statistical method that averages data over time, continually decreasing the weight of data as it moves further back in time.  An EWMA chart is particularly good at monitoring processes that drift over time and is used to detect small shifts in a trend.

In our project, EWMA is used to follow the evolution of the % of farms at risk that broke with PRRSV every week. EWMA incorporates all the weekly percentages recorded since the beginning of the project and gives less and less weight to the results as they are more removed in time. Therefore, the % of farms at risk that broke with PRRSV last week will have much more influence on the EMWA than the % of farms at risk that broke with PRRSV during the same week last year.

Take a look at the original 13 and overall EMWAs.

 

 

 

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
Abstract

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.

Link to the entire article

What does antimicrobial-resistant bacteria really mean?

Antimicrobial resistance is an expression that everyone in swine production has heard at least once but what does it really mean?  How are you as a producer or veterinarian affected?

Villalta NHF antimicrobial resistance 2017.gif

In this column for the National Hog Farmer, Dr. Carles Vilalta explains that beyond the definition of a bacterium that is not affected by an antimicrobial, there are two different approaches to think about resistance:

  • One is determined by the Minimal Inhibitory Concentration or MIC, which records the minimum medicine concentration required to stop the growth of the bacteria.
  • The other focuses on the presence of genes enabling the bacterium to counteract the effect of the antimicrobial.

These genes are usually present in a sub-population of bacteria called mutants. The video below created by Harvard Medical School shows how these mutants can develop, adapt, and survive the highest antimicrobial concentrations. (video length < 2min)

 

 

Science page: Creating really strong passwords

This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project.

Last week, we explained why we took the decision to change the name of the project to honor Bob and his dedication to the swine industry. The project continues, carrying his legacy.

Key points from this week edition:

  • Computer processing power keeps increasing at an alarming rate, allowing hackers to greatly increase their password cracking capabilities.
  • Hackers’ password cracking tools can crack weak passwords in no more than a couple of hours of execution. The same tools will take millions of years to crack a strong password.
  • Whenever password cracking is mentioned in this article, it should be assumed that the password is encrypted using a strong cryptographic hash algorithm such as scrypt: http://www.tarsnap.com/scrypt.html

So what makes a strong password in the end? Read our full paper on the topic.

Science Page: Bob Morrison’s legacy

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

This week, the Science Page honors Dr. Robert Morrison, the founder and leader of the Swine Health Monitoring Project.

Bob’s unique talent for creating relationships that advanced the swine industry culminated in the creation of the Swine Health Monitoring Project (SHMP), one of the initiatives that Bob carried with pride. […] As it evolved, the SHMP changed names several times but many in the industry simply refer to it as “Bob’s project”. For that reason, and to give the just recognition he deserves, we have decided to renam the project to “Dr. Bob Morrison’s SHMP” (MSHMP).