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.

OptisampleTM: Open web-based application to optimize sampling strategies for active surveillance activities at the herd level illustrated using PRRS

This past Saturday during the 49th AASV annual meeting, Dr. Rovira presented OptisampleTM, an online open-access tool to determine sample strategies for disease surveillance.

Did you miss this presentation? Click here to see the schedule of our talks during the 2018 AASV meeting!

Dr. Ana Alba who created this tool published an open-access article on how to use Optisample for PRRS active surveillance.

Several inputs are needed to use this web-based application: herd size, frequency of testing, minimum prevalence to detect…

3 different herd examples are then shown to test for PRRSV surveillance. The input and outputs of those examples are show in the figure below:

If you want to try out OptisampleTM, click here.


Porcine reproductive and respiratory syndrome virus (PRRSv) infection causes a devastating economic impact to the swine industry. Active surveillance is routinely conducted in many swine herds to demonstrate freedom from PRRSv infection. The design of efficient active surveillance sampling schemes is challenging because optimum surveillance strategies may differ depending on infection status, herd structure, management, or resources for conducting sampling. Here, we present an open web-based application, named ‘OptisampleTM’, designed to optimize herd sampling strategies to substantiate freedom of infection considering also costs of testing. In addition to herd size, expected prevalence, test sensitivity, and desired level of confidence, the model takes into account the presumed risk of pathogen introduction between samples, the structure of the herd, and the process to select the samples over time. We illustrate the functionality and capacity of ‘OptisampleTM’ through its application to active surveillance of PRRSv in hypothetical swine herds under disparate epidemiological situations. Diverse sampling schemes were simulated and compared for each herd to identify effective strategies at low costs. The model results show that to demonstrate freedom from disease, it is important to consider both the epidemiological situation of the herd and the sample selected. The approach illustrated here for PRRSv may be easily extended to other animal disease surveillance systems using the web-based application available at

Swine Global Surveillance Project Issues First Reports

cahfs_primary_graphicThe University of Minnesota Swine Group and the Center for Animal Health and Food Safety (CAHFS) have partnered with the Swine Health Information Center (SHIC) to develop and implement a system for near real time global surveillance of swine diseases. The output of the system is the identification of hazards that are subsequently scored using a step-wise procedure of screening, to identify increments in hazards that, potentially, may represent a risk for the US.

The first version of the system is now live, with the first three reports available, including data from November 5, 2017 to January 14, 2018.

Beginning in early March the tool will be available for spontaneous reporting by stakeholders, such as producers and practitioners both overseas and in the United States. During the first year of the project, the system will be developed and beta-tested for USDA-classified tier 1 reportable foreign animal swine diseases (ASF, CSF, FMD), but in the future more diseases will be tracked.

“As we have learned in recent years, we need to pay attention to external health threats as part of our overall risk management. Keeping tabs on global trends is a prudent investment,” said Dr. Jerry Torrison, Director of the University of Minnesota Veterinary Diagnostic Laboratory.

From the most recent report, December 18, 2017 – January 14, 2018:

The current concern continues to focus on African swine fever in Poland and surrounding countries. Infected wild boars continue to be identified in the vicinity surrounding Warsaw, and the possibility of spread of the disease to the pig intensive area of eastern Poland continues to be a concern. Countries in the region are using a combination of increased hunting of wild boar along with boar proof fencing along borders to attempt to control the spread of the disease.

Visit to access the reports, and coming soon, to use the tool to provide spontaneous reporting.

Sample types and diagnostic methods for early detection of Mycoplasma hyopneumoniae

In lieu of the Science Page today, we are bringing you our most popular articles on the blog this past year: a publication by Dr. Maria Pieters, head of the MycoLab called Sample and diagnostic types for early detection of Mycoplasma hyopneumoniae.


Mycoplasma hyopneumoniae is the causative agent enzootic pneumonia, an economically significant disease in pigs. In this study published by Drs. Pieters and Rovira from the University of Minnesota, pigs experimentally inoculated with M.hyopneumoniae were sampled 0, 2, 5, 9, 14, 21, and 28 post-inoculation.

Different sample types were compared:

  • Nasal swabs
  • Laryngeal swabs
  • Tracheobronchal lavages
  • Oral fluids
  • Serum samples

Using different diagnostic tests:

  • PCR
  • ELISA IgG anti M.hyopneumoniae
  • ELISA Ig M anti M.hyopneumoniae
  • ELISA C-reactive protein

Laryngeal swab samples tested by PCR were highly sensitive for detection of Mycoplasma hyopneumoniae in live pigs. Various commercial ELISA kits for detection of Mycoplasma hyopneumoniae antibodies showed similar sensitivity. Oral fluids showed a low sensitivity for detection of Mycoplasma hyopneumoniae in experimentally infected pigs.

Link to the full-article

The emergence and evolution of influenza A (H1α) viruses in swine in Canada and the United States

Today, we are sharing a recent publication on swine influenza in the Journal of General Virology. Dr. Marie Culhane from the University of Minnesota collaborated on this study of the genetic diversity of swine viruses in Canada and how it influences the strains found in the US.

The final data set included:

  • 168 genomes from Canadian swine influenza A viruses,
  • 5 genomes from highly under-represented US states (Alabama, Arkansas, Kentucky, Maryland and Montana),
  • 648 genomes from US and Canadian swine influenza A viruses (GenBank).

In total, these data represented 29 US states and 5 Canadian provinces.

Genetic diversity of influenza A viruses

In Canada, H1α viruses were the most frequently identified H1 viruses. In contrast, H1α viruses died out long ago in US herds, and have only been identified sporadically following new viral introductions from Canada. Notably, the two dominant H1 viruses in the United States, H1γ and H1δ-1, were not observed in any Canadian province during 2009–2016. In contrast to H1, H3 viruses are found in both the United States and Canada, with evidence of frequent cross-border transmission.

Sources of viral diversity

The study shows that the source of influenza viruses is aligned with pig movements. Indeed, Iowa and Minnesota receive around 87% of Manitoba swine exports. Therefore, the patterns of swine influenza viruses in those 2 US states correlate with the ones in Manitoba.

Similarly, viral gene patterns found in Illinois, Michigan, Wisconsin, or Ohio are influenced by the ones found in Ontario. Indeed, it only takes 3 hours to transport pigs from Ontario to Michigan. However, North Carolina and Virginia are the largest source of viruses for this region.


Left: Each region is shaded according to the proportion of total ‘Markov jump’ counts from that particular region into the Heartland: red, high proportion of jumps, important source of viruses; light yellow, low proportion of jumps, not an important source of viruses; black, destination. Right: US states are shaded according to the number of live swine imported from Manitoba in 2015 (per 1000 head)


Swine are a key reservoir host for influenza A viruses (IAVs), with the potential to cause global pandemics in humans. Gaps in surveillance in many of the world’s largest swine populations impede our understanding of how novel viruses emerge and expand their spatial range in pigs. Although US swine are intensively sampled, little is known about IAV diversity in Canada’s population of ~12 million pigs. By sequencing 168 viruses from multiple regions of Canada, our study reveals that IAV diversity has been underestimated in Canadian pigs for many years. Critically, a new H1 clade has emerged in Canada (H1α-3), with a two-amino acid deletion at H1 positions 146–147, that experienced rapid growth in Manitoba’s swine herds during 2014–2015. H1α-3 viruses also exhibit a higher capacity to invade US swine herds, resulting in multiple recent introductions of the virus into the US Heartland following large-scale movements of pigs in this direction. From the Heartland, H1α-3 viruses have disseminated onward to both the east and west coasts of the United States, and may become established in Appalachia. These findings demonstrate how long-distance trading of live pigs facilitates the spread of IAVs, increasing viral genetic diversity and complicating pathogen control. The proliferation of novel H1α-3 viruses also highlights the need for expanded surveillance in a Canadian swine population that has long been overlooked, and may have implications for vaccine design.

Identification of antigenically important sites in Rotavirus B

Happy New Year to all of you readers of this blog! We appreciate your presence here. In 2018, we will bring you even more quality content related to swine health and production.

Our first publication of the year features the work of Frances Shepherd, a PhD student (who recently received an award at the CRWAD meeting) with Drs. Michael Murtaugh and Douglas Marthaler. The paper is in open access in the journal Pathogens and you can read it here.

Shepherd antigenically important sites in rotaviruses B

In this experiment, 174 clinical samples from US and Canadian swine herds and positive for rotavirus B by PCR were used to sequence the gene for the protein VP7.
VP7 is a protein of interest in rotaviruses B because it is structural and can be found on the outer layer of the virus capsid. Along with VP4, they stimulate the creation of neutralizing antibodies in pigs.

Based on those sequences, 169 of the viruses were allocated to 8 defined genotypes: G8, G11, G12, G14, G16, G17, G18, and G20. However, five strains had less than 80% similarity with those genotypes and were assigned to the new genotypes G22, G23 (2 strains), G24, and G25. The G16 genotype was the most prevalent genotype each year. The predominant genotypes clustered geographically, with G12 being predominant on the east coast, G16 in the Midwest, and G20 within the Great Plains states.

Rotaviruses B geographical distribution US
Distribution of Rotavirus B genotypes per state

Investigation of the variability within the VP7 proteins identified 8 variable regions. However, those regions did not align with the sites of high antigenicity detected in the predominant groups. Indeed, surface-exposed antigenic residues underwent negative selection more often than positive selection.


Rotavirus B (RVB) is an important swine pathogen, but control and prevention strategies are limited without an available vaccine. To develop a subunit RVB vaccine with maximal effect, we characterized the amino acid sequence variability and predicted antigenicity of RVB viral protein 7 (VP7), a major neutralizing antibody target, from clinically infected pigs in the United States and Canada. We identified genotype-specific antigenic sites that may be antibody neutralization targets. While some antigenic sites had high amino acid functional group diversity, nine antigenic sites were completely conserved. Analysis of nucleotide substitution rates at amino acid sites (dN/dS) suggested that negative selection appeared to be playing a larger role in the evolution of the identified antigenic sites when compared to positive selection, and was identified in six of the nine conserved antigenic sites. These results identified important characteristics of RVB VP7 variability and evolution and suggest antigenic residues on RVB VP7 that are negatively selected and highly conserved may be good candidate regions to include in a subunit vaccine design due to their tendency to remain stable.

US PRRSv surveillance using risk mapping and species distribution modeling

Today, we are sharing a publication from the Preventive Veterinary Medicine journal, by Dr. Andres Perez and the STEMMA laboratory. The goal of the study was to quantify the combined effect of factors such as season and herd size on the spatial range of high-risk areas for PRRSV outbreaks. Using Species Distribution Model, the team extracted associations between hypothesized risk factors and disease occurrence.


  • A species distribution model was used, to predict the spatial risk of PRRSv in swine populations across the U.S.
  • All of the Maxent spatial models identified high-risk areas, with probabilities greater than 0.5.
  • Relative contribution of pig density to PRRSv risk was higher in densely pig populated areas.
  • Relative contribution of climate and land cover to PRRSv risk were important in areas with relative low pig densities.
  • Ecological dynamics of PRRSv are different between swine production region in the U.S.

The largest number of PRRSv outbreaks in the U.S., as reported in the MSHMP, was observed in north central parts of Iowa, followed by south central areas of Minnesota. However, our crude U.S. Maxent model identified eastern North Carolina, southern Minnesota, and northern Iowa as high-risk areas for PRRSv outbreaks. As expected, pig density accounted for most of the PRRSv spatial risk (81.3% relative contribution). Climate (interpreted as the percentage of day-to-night temperature oscillation compared with the summer-to-winter oscillation, and mean temperature of the warmest quarter) accounted for the remaining spatial risk. Overall, the crude Maxent model suggested geographical areas with high pig densities and with a low level of daily temperature variability to the year are mostly suitable for circulation and maintenance of PRRSv.

Factors percent contribution PRRS outbreak Perez 2017
Summary charts of the estimated relative percent contribution of each environmental and demographic variable of the final Maxent model for each swine production region in the U.S.

The model for the South East region indicated that pig density was the most important predictor; followed by precipitation of the wettest month, land cover, and temperature seasonality. The relative contribution of pig density was smaller for this region compared to the Midwest. Specifically, geographical locations with high pig density, precipitation amount between 120 and 200 mm during the wettest months, and that were located within croplands were mostly suitable for PRRSv outbreaks in North Carolina and Northern South Carolina.

Additionally, the spread of PRRSV under certain conditions was more evident for the regions where pig density is relatively low. For example, in Illinois and Indiana and Kansas, Colorado, Oklahoma and Texas, wet weather and temperatures above 0 °C were more important in predicting the spatial risk of PRRSv than pig density.

Click here to read the entire publication on US PRRSv surveillance using risk mapping and species distribution modeling.


PRedicting and mapping PRRSV outbreaks PEREZ 2017.jpg


Porcine reproductive and respiratory syndrome virus (PRRSv) outbreaks cause significant financial losses to the U.S. swine industry, where the pathogen is endemic. Seasonal increases in the number of outbreaks are typically observed using PRRSv epidemic curves. However, the nature and extent to which demographic and environmental factors influence the risk for PRRSv outbreaks in the country remains unclear. The objective of this study was to develop risk maps for PRRSv outbreaks across the United States (U.S.) and compare ecological dynamics of the disease in five of the most important swine production regions of the country. This study integrates spatial information regarding PRRSv surveillance with relevant demographic and environmental factors collected between 2009 and 2016. We used presence-only Maximum Entropy (Maxent), a species distribution modeling approach, to model the spatial risk of PRRSv in swine populations. Data fitted the selected model relatively well when the modeling approach was conducted by region (training and testing AUCs < 0.75). All of the Maxent models selected identified high-risk areas, with probabilities greater than 0.5. The relative contribution of pig density to PRRSv risk was highest in pig-densely populated areas (Minnesota, Iowa and North Carolina), whereas climate and land cover were important in areas with relatively low pig densities (Illinois, Indiana, South Dakota, Nebraska, Kansas, Oklahoma, Colorado, and Texas). Although many previous studies associated the risk of PRRSv with high pig density and climatic factors, the study here quantifies, for the first time in the peer-reviewed literature, the spatial variation and relative contribution of these factors across different swine production regions in the U.S. The results will help in the design and implement of early detection, prevention, and control strategies for one of the most devastating diseases affecting the swine industry in the U.S.