Science Page: PRRS EWMA analysis for years 2009 – 2018

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 sharing a report by the MSHMP team regarding the EMWA analysis for years 2009-2018.

Key points:

  • The  EWMA chart is a smoothed chart of the percentage of farms that are breaking.
  • Newly added farms to MSHMP increase the denominator therefore diluting the estimate which affects the EWMA chart giving the impression that PRRS season has changed.

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.


MSHMP report chart 4 depicts: 1)the number of new cases (green dots – secondary Y axis) during a specific week and 2)the percentage of farms that broke during that week of the total in the MSHMP project in a smoothed way (blue line/Y axis). The red horizontal line indicates the threshold (upper confidence limit  – UCL). This UCL is calculated based on the average of cases during the lowest PRRS months in the year, June, July and August and is recalculated every two years.
When  there are more cases than expected, the blue line crosses the threshold (red line) indicating there is an epidemic.

The formula used in the EWMA chart is the following:

EMVA formula
where E is the smoothed % of infected herds, lambda the constant smoothing the curve, I the % of infected herds during that week and Et-1 is the smoothed % of  infected herds during the previous week.

If different smoothing factors are applied to the MSHMP data this would generate different trends and then we would place the threshold based on the sensitivity
that we consider that signals an epidemic.

EMVA graph with different parameters

Has the incidence of PRRS changed?

One possible reason the EWMA % of cases decreasing might be that the number of farms that are breaking expressed as a percentage is less. This can be due to the fact that the total number of farms sharing PRRS status has been increasing and these new farms might have a lower underlying incidence.


Influenza epidemiology in breed-to-wean farms and infection dynamics in nursery pigs

Fabian Chamba portrait photoEarlier this year, Dr. Fabian Chamba Pardo successfully defended his PhD under the supervision of Drs. Montse Torremorell and Marie Culhane. The focus of his thesis is influenza epidemiology with an emphasis on sow farms and nurseries. We share with you today a summary of his work.


Influenza is an economically important disease in pigs and a public health threat. Breed-to-wean (BTW) farms play a central role in influenza epidemiology and control because piglets maintain and disseminate influenza A virus (IAV) to other farms. Despite the importance of piglets in influenza epidemiology, there is limited information on IAV infection parameters in piglets, risk factors that impact IAV prevalence in piglets at weaning, and how strategies that are implemented in BTW farms affect IAV infections in weaned pigs.


In this thesis, my goal was to address some of the questions that are central to the transmission and control of influenza in BTW farms, especially infection in piglets ready to wean. The questions addressed are also critical to guide control strategies to mitigate IAV infections in the post weaning period. More specifically, I aimed to: 1) estimate herd-level prevalence and seasonality of influenza in BTW farms, 2) evaluate farm factors associated with IAV infection in piglets at weaning, 3) assess transmission patterns and parameters of influenza in nursery pigs based on IAV prevalence at weaning, and 4) evaluate the impact of maternally-derived antibodies (MDA) at weaning on IAV infection parameters in nursery pigs.

Research Chapter 1

Influenza herd-level prevalence and seasonality in breed-to-wean pig farms in the Midwestern United States

Article published in Frontiers in Veterinary Science:

Results showed that IAV herd-level prevalence in piglets at weaning from Midwestern BTW farms is seasonal with higher infection rates in winter (December) and spring (May) than those in summer and fall. Additionally, influenza seasonality was partially explained by the seasonal variations of outdoor air absolute humidity and temperature. Finally, there was significant genetic diversity of influenza strains circulating in those farms and that, co-circulation of more than one genetically distinct clade over time was very common in the studied farms. This is critical knowledge that may help to identify high risk periods where influenza control measures can be placed. It may also help to create research opportunities on absolute humidity and influenza transmission in pigs and finally, it supports other studies that have shown that genetic diversity and circulation is wide and common and that new vaccines and vaccination strategies should take that into consideration.

Chamba herd level influenza prevalence in the Midwest
Influenza A virus herd-level prevalence in Midwestern US breed-to-wean pig farms.

Research Chapter 2

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

In this chapter, there were 24 farm factors evaluated for their association with influenza at weaning and among those, only IAV sow vaccination and the IAV-negative status of replacement breeding females (gilts) at entry to the herd were significantly associated with less IAV infected piglets at weaning. This is critical information that veterinarians and producers may use to manage IAV levels at weaning. In addition, there was also a lack of significant association with factors such as air filtration and farm density which may be indicative that endemic influenza infections are more important than airborne lateral transmissions between farms. Finally, disease control strategies such as herd closure, early weaning, batch farrowing, gilt isolation and gilt influenza vaccination were not fully evaluated in this study. Hence, more work is needed to further understand how to use these strategies to decrease influenza infections in pigs.

sow vac protocol - Copy
Influenza A virus (IAV) positive mean predicted probabilities over time for breed-to-wean farms with different sow vaccination protocols.

 Research Chapter 3

Influenza A virus transmission patterns and parameters in growing pigs

Results indicate that groups of piglets with different prevalence at weaning had different transmission patterns and parameters after weaning and these patterns were characterized by 1, 2 or no peaks of infection after weaning. Piglets with low prevalence at weaning had less influenza infections in the nursery. This information may help producers and veterinarians to make informed decisions when it comes to use control strategies such as sow vaccination aimed to reduce influenza infections in the nursery.

Figure 1

Research Chapter 4

Effect of maternally-derived antibodies on influenza A virus infection in growing pigs

In my last chapter, I reported that if pigs had high levels of strain-specific maternally-derived antibodies at weaning, IAV infection occurred later and it was of shorter duration after weaning. Piglets with hemagglutination inhibition (HI) titers of 1:40 or higher were less likely to test IAV positive at weaning and during the nursery. These results indicate that strain-specific maternally-derived antibodies generated with sow vaccination pre-farrow significantly reduce influenza infections at weaning and in the nursery.

Figure 1 (1)


Knowledge of influenza seasonality and what factors are significantly associated with influenza in breed-to-wean farms can help producers and veterinarians to better use and allocate influenza control strategies such as sow vaccination. In addition, lower prevalence of influenza at weaning due to high strain-specific maternally-derived antibodies levels may help decrease influenza spread from wean-to-finish farms. Reducing the burden of influenza in growing pigs should decrease influenza-associated economic losses and the generation of novel strains, including strains with pandemic potential. More studies are needed to further elucidate control strategies to limit influenza infections and spread in pigs.

Swine microbiome studies: Why, how and where are we going?

There is no Science Page this week; we will return to our normal schedule next week. In the meantime,  you may read our previous publications on our website.

Today, we will be talking about swine microbiome studies. Dr. Andres Gomez, expert in microbiome, who joined the University as part of the new AGREETT positions wrote an article for the National Hog Farmer about research on swine microbiome.

What does microbiome mean?

Microbiome refers to all of the microbes present in an area. For example, gut microbiome is the entire population of microorganisms (most of the time bacteria) present in the intestinal tract.

Microbes have been traditionally viewed through a lens of distrust, as pathogens affecting health. However, molecular and computational breakthroughs to study microbial diversity and function by sorting DNA sequences have presented a novel concept of an animal “flora” that acts as a friend as opposed to a foe.

Characterizing the microbiome to improve nutrition

Characterizing the specific microbes that increase or decrease in abundance upon pharmaceutical or dietary interventions is critical to determine precise dose-response relationships and to potentially reduce feed costs while achieving desired improvements in pig health and productivity.

Defining “healthy” microbiomes to identify poor-doing pigs

Regular “microbiome snapshots” along the most critical stages of pig growth (e.g., pre- and post-weaning), can be used to predict health and potential pathogen threats for disease by early identification of bacteria in slow-growing pigs or those that are at most risk of infection. This would allow producers to make early decisions on therapeutic or dietary interventions to enhance performance and health.

swine gut microbiome
 1) nutrients and feed additives modulate gut microbiomes to impact health and performance, 2) microbiomes across the pig anatomy are accurate biomarkers of stress such as diseases, early weaning, and heat, and 3) microbiomes in manure can be modulated to mitigate harmful gases.

Enhancing the protective microbiome

The microbiome in the gut or respiratory tract is a protective layer against infectious diseases. Thus, with microbiome research, we can determine how novel feed additives and management interventions work, by either enhancing the abundance of microbes that promote health and/or displacing those that cause disease.

Microbiome beyond pork production

For instance, specialized bacteria and fungi can degrade otherwise underutilized natural resources to maximize pig productivity, while decreasing the environmental footprint. Additionally, specialized microbial communities can also mitigate the production of dangerous gases  produced in manure pits.

Stability of Porcine Epidemic Diarrhea Virus on Fomite Materials at Different Temperatures

Today, we are presenting a paper published by Dr. Maxim Cheeran‘s lab in Veterinary Sciences regarding the stability of PEDV on fomite materials at different temperatures.

The full article is available in open access on the journal’s website.

Porcine Epidemic Diarrhea virus and its transmission

Porcine epidemic diarrhea virus (PEDV) causes highly contagious viral enteritis in swine. In May 2013, a PEDV strain, genetically related to a Chinese strain, was introduced in the US and spread rapidly across the country causing high mortality in piglets. Over eight million pigs were killed during this outbreak, leading to an estimated loss of 1.8 billion US dollars.

Transmission of PEDV primarily occurs by the fecal-oral route, but indirect transmission can occur when an animal comes in contact with inanimate objects (fomites) contaminated with the feces of PEDV-infected animals.


200 μL of virus containing 2.1 × 106 TCID50/mL was applied on various fomite material: Styrofoam, nitrile gloves, cardboard, aluminum foil, Tyvek® coveralls, cloth, metal, rubber, and plastic. The virus-contaminated fomites were then stored at either 4◦C or at room temperature. Samples were then taken at 0,1 2, 5, 10, 15, 20 and 30 days post-contamination to test for virus stability.

PEDV survival on fomites Cheeran et al


Infectious PEDV was recovered from fomite materials for up to 15 days post application at 4◦C; only 1 to 2 logs of virus were inactivated during the first 5 days post application. On the other hand, PEDV survival decreased precipitously at room temperature within 1 to 2-days post application, losing 2 to 4 log titers within 24 h as can be seen on the figure above.

Immunoplaque assay was used to identify positive fomites after 20 days of storage at 4◦C. Immunoplaque assay is much more sensitive than PCR and can detect virus as low concentration as 24 focus forming units/mL. Titers of approximately 1 × 10^3 FFU/mL were observed in eluates from Styrofoam, metal, and plastic, representing a 3-log virus inactivation after 20 days. The surviving virus on Tyvek® coverall and rubber surfaces was moderately above detection limit (24 FFU/mL).


Indirect transmission of porcine epidemic diarrhea virus (PEDV) ensues when susceptible animals contact PEDV-contaminated fomite materials. Although the survival of PEDV under various pHs and temperatures has been studied, virus stability on different fomite surfaces under varying temperature conditions has not been explored. Hence, we evaluated the survival of PEDV on inanimate objects routinely used on swine farms such as styrofoam, rubber, plastic, coveralls, and other equipment. The titer of infectious PEDV at 4 °C decreased by only 1 to 2 log during the first 5 days, and the virus was recoverable for up to 15 days on Styrofoam, aluminum, Tyvek® coverall, cloth, and plastic. However, viral titers decreased precipitously when stored at room temperature; no virus was detectable after one day on all materials tested. A more sensitive immunoplaque assay was able to detect virus from Styrofoam, metal, and plastic at 20 days post application, representing a 3-log loss of input virus on fomite materials. Recovery of infectious PEDV from Tyvek® coverall and rubber was above detection limit at 20 days. Our findings indicate that the type of fomite material and temperatures impact PEDV stability, which is important in understanding the nuances of indirect transmission and epidemiology of PEDV.

Science Page: Geographic distribution and genetic diversity of PCV3 from clinical samples in US swine farms

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 sharing a report by Zhen Yang a DVM/MS candidate at the UMN, regarding the Geographic distribution and genetic diversity of PCV3 from clinical samples in US swine farms.

Key Points:

  • PCV3 is widespread in the U.S.
  • Abortion cases in the study had a high rate of PCV3 positivity.
  • PCV3 found in association with lesions in an abortion case suggesting causality.

The study looked at 730 cases from the UMN Veterinary Diagnostic Laboratory with a positive sample for PCV3, received between Feb 2016 and Jan 2018.

Yang PCV3 US location genetic diversity

Out of 22 states, 18 states were PCV3 positive. PCV3 was detected in pigs from all ages.

The positive rate among fetus, piglets, nursery and finishing pigs ranged from 15% to 20%. The PCV3 rate in adults was 35%.

PCV3/PCV2 co-infection rate was 5.2%, and PCV3/PRRSV coͲinfection rate was 7.6%.

In our data, we had 67 abortion cases, and 40% of them were PCV3 positive. In one abortion case investigation, histological lesions were observed in lung tissue of aborted fetus and PCV3 in-situ hybridization showed presence of PCV3 in the lesion.

Seven PCV3 whole genome sequences were obtained. Current PCV3 genomes in the U.S shared over 98% nucleotide identities. U.S strains did not cluster together and were grouped with PCV3 sequences obtained in other countries.

AASV 2018: A successful meeting in San Diego

The UMN CVM students did a fantastic job at the 2018 American Association of Swine Veterinarians (AASV) meeting last week. Zhen Yang presented an update on his research regarding PCV3 and got the second place in the student oral competition.
Taylor Homann received a prize for her poster presentation. Marjorie Schleper was awarded one of the 10 student scholarships given by Merck Animal Health. Hunter Baldry was recognized for the most downloaded podcast: her interview of Dr. Clayton Johnson.

Dr. Montse Torremorell shared the initiatives undergoing at the University of Minnesota in the honor of Dr. Bob Morrison.

Lastly, Dr. Juan Sanhueza received one award given by Boehringer Ingelheim to advance the research on swine respiratory pathogens for his project: “Evaluation of parity as a delaying factor to reach PRRSv stability in sow farms”. Dr. Perle Boyer received a research grant from the AASV Foundation to develop Day 1 competencies for swine veterinary graduates.

Congratulations to all!

Science Page: Swine Global Surveillance Project: update and future steps

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 sharing an update on the Swine Global Surveillance Project, lead by the Center for Animal Health and Food Safety in collaboration with the UMN Veterinary Diagnostic Laboratory, the UMN swine group and the Swine Health Information Center (SHIC).

 Key Points:

  • It is a public, private and academic partnership to implement a system for near real time global surveillance of swine diseases.
  • The output of the system is a report of hazards identified and subsequently scored that may represent a risk for the US pork industry.
  • Developing systems to provide situational awareness to stakeholders in near-real time can facilitate the coordination between government agencies and the industry with the ultimate objective of preventing or mitigating the impact of diseases epidemics.
  • The reports are available at:

The system of near real time global surveillance of swine diseases is based on an online application.  Initially focused on three main potential
threats: Classical Swine Fever (CSF), African Swine Fever (ASF), and Foot and Mouth Disease (FMD), it will expand to other exotic swine diseases in the US in the near future. A report, distributed on a monthly basis by SHIC, includes a list of identified hazards that may represent a risk for the US.

Swine global surveillance process steps

Several steps are needed to build the Swine Global Surveillance report as shown in the figure above.

  1. Screening/Filtering phase: Multiple official data sources and soft data sources are systematically screened to build a raw repository. After that, an Include/exclude process is undertaken under a crowdsourcing model.
  2. Scoring phase: A multi-criteria rubric was built based on: credibility, scale and speed of the outbreak, connectedness, local capacity to respond and potential financial impact on the US market. Each event is score independently by a group of experts.
  3. Quality assurance (QA)/building: Its aim being to ensure that the design, operation, and monitoring of processes/systems will comply with the principles of data integrity including control over intentional and unintentional changes to information. The monthly report is put into a PDF document automatically from the app after the scoring process is finalized. At last, assembly of figures and proofreading is done before sending it to SHIC for monthly publication.

Next steps

  • Complete automation of event capture into the database
  • Expansion of the list of diseases in the report
  • Shrinking the gap between Search/Filter phase and Final Publication – (1 week)
  • Expanding scoring experts panel
  • Process documentation – Quality assurance compliance