Morrison Swine Health Monitoring Project 2018 Summary

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, Dr Cesar Corzo shares the summary of the year 2018 for the Morrison Swine Health Monitoring Project.

During 2018 the MSHMP continued to make progress in different areas related to our main objective of developing the capacity to support the industry respond to emerging pathogens.

1) Database – Database has been structured to be able to capture a larger volume of data. This is a major step forward as we continue to work towards building the capacity of adding more sites and disease entities if needed.

2) Prospective PRRS sequence monitoring – The process of capturing diagnostic data continues, although not yet automated it is still adding sequences to the database. The database currently has 23,414 PRRS sequences from 20 systems and 21 states. Analyses of the database have begun with a subset but ultimately, we will be exploring trends and seasonal relationships involving spatialͲtemporal approaches. The database continues to provide a resource for MSHMP participants when conducting outbreak investigations.

3) Transport data capture and analysis – After a challenging year with our transport App we have decided to go back to basics and try a new approach to capturing transport data. The new approach which involves technology already validated in the trucking industry is currently being tested; we will follow up on this objective later this year.

4) Expansion – MSHMP continues to grow through three different ways:

  • 1) Current MSHMP participants continue to add new established farms,
  • 2) New participants have joined the project, two new production systems are already reporting and 2 more are in the process of providing data and
  • 3) Growing herd data inclusion into MSHMP has begun and is in the early stages as we learn how to link it with the breeding herd.

We have also continued our commitment with creating value to our producers through specific research projects that have been shared through conferences, MSHMP participant meeting during AASV and Leman Conference.

Peer Reviewed Publications

1. Vilalta C, Sanhueza J, Alvarez J, Murray D, Torremorell M, Corzo C, Morrison R. Use of processing fluids to determine porcine reproductive and respiratory syndrome virus infection status in pig litters. Vet Microbiol. 2018. 225:149Ͳ156. DOI: 10.1016/j.vetmic.2018.09.006

2. Machado, G., C. Vilalta, A.M. Corzo, C., Torremorrell, M., Perez, K. VanderWaal. Predicting outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods. Nature Scientific Reports. Accepted.

3. Kinsley, A.C., A. Perez, M.E. Craft, K. VanderWaal. Characterization of swine movements in the United States and implications for disease control. Preventive Veterinary Medicine. Submitted.

4. Sanhueza JM, Vilalta C, Corzo C, Arruda AG. Factors affecting Porcine Reproductive and Respiratory Syndrome virus time-to-stability in breeding herds in the Midwestern United States. Transbound Emerg Dis. 2018. Dec 6. Doi: 10.11111/tbed.13091.

5. Arruda AG, Sanhueza J, Corzo C, Vilalta C. Assessment of area spread of porcine reproductive and respiratory syndrome (PRRS) virus in three clusters of swine farms. Transbound Emerg Dis. 2018. DOI: 10.1111/tbed.12875.

6. Arruda AG, Vilalta C, Puig P, Perez A, Alba A. Time-series analysis for porcine reproductive and respiratory syndrome in the United States. PLoS One. 2018. 13(4):e0195282. DOI: 10.1371/journal.pone.0195282. eCollection.

7. VanderWaal, K, Perez A, Torremorrell A, Morrison R, Craft M. Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus. Epidemics. 2018. 24:67-75. DOI: 10.1016/j.epidemic.2018.04.001.

Acknowledgements

We would like to acknowledge the strong team of faculty members, post-docs, students and staff that make this project possible. Additionally, this project would not be possible without the commitment of participants and practitioners and funding from the Swine Health Information Center.

Faculty: B. Morrison, C. Corzo, A. Perez, M. Torremorell, K. VanderWaal, J. Torrison and D. Linhares (ISU), D. Holtkamp (ISU), A. Arruda (OSU), and G. Machado (NCSU)

Post-Docs and Students: Carles Vilalta (Data visualization, PRRS testing), Juan Sanhueza (TTS, spatialͲtemporal analysis), Mariana Kikuti (PRRS sequence trends), Paulo Fioravante (IT Director), Emily Geary (Data manager), Kaushi Kanankege (Spatial analysis), Igor Paploski (Regional PRRS sequence analysis), Belinda Befort (Diagnostic trends)

Project Invitation: Assessing within-herd PRRS variability and its impact on production parameters

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, Dr. Arruda and her numerous collaborators invite you to participate in a project.

We know that PRRS virus mutates and evolves quickly. We know there can be co-circulation of PRRS variants in a herd, and even within a single animal. We don’t know whether that can impact health and production. We don’t know how that affects the way we are currently sampling and assessing virus similarity within herds over time.

Project main goal:

This project aims to examine within-herd PRRSV variability over time for sow and growing pig sites under different PRRS immunity strategies (vaccinated, negative and positive herds), and investigate the association between within-herd PRRS variability and health and production parameters of interest to swine producers. We partnered up collaborators with a wide range of expertise to use whole genome sequencing (WGS) to provide insights on the likelihood of PRRS outbreaks

Objective 1:

Describe PRRSV quasispecies within farms using a sample of farms of different demographic types and PRRS management strategies over a one-year time span; and investigate whether PRRSV variability has an impact on health and production outcomes.

Objective 2:

Investigate and compare the use of WGS and different ORFs to determine the best predictor to identify and relate viruses within swine herds.

Objective 3:

Correlate PRRSV variants with production and disease metrics being due to “normal” within-herd virus evolution, vs. new PRRS introductions. And we will also look into the effect of PRRSv variants in production

Request:

We are looking to enroll 6 farms for this project, that has a duration of 1 year:

3 breeding herds (farrow-wean):

  • 1 “naïve” herd (no PRRS for at least last 2 years) that just had an outbreak (farm will be enrolled as a new outbreak happens)
  • 1 “vaccinated” herd (a herd that had a PRRS outbreak and has been vaccinated since then at least twice a year with a MLV)
  • 1 “naturally exposed” herd (a herd that had an outbreak in the past year but is no longer exposing or vaccinating animals (herd will be still eligible if gilts are exposed off site and brought in after testing negative)

3 growing pig herds (finisher or wean-finish):

  • 1 “naïve” herd (no PRRS for at least last 2 years) that just had an outbreak (farm will be enrolled as a new outbreak happens)
  • 1 “vaccinated” herd (a herd that vaccinates each batch of animals using a MLV)
  • 1 “positive” herd (a herd that had an outbreak in the past and is regularly exposed to live virus or a herd that is receiving known positive pigs from a positive source.

We would work with your veterinarian and your team to coordinate the submission of ~16 samples total in a monthly basis for 1 year (12 samplings). These samples will include a combination of processing fluids, oral fluids, and tonsil scrapings. All samples will be sent to the University of Minnesota monthly. Diagnostics is paid. Also, sharing production data will be a requirement.

African Swine Fever: economics versus pathology

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, Dr. John Deen compares the consequences of African Swine Fever based on its pathogenicity and its economic impact on the swine industry.

Keypoints

  • The disease appears to be relatively easy to identify, control and eradicate in the US
  • Introduction of African Swine Fever (ASF) would result but relatively few infected pigs
  • The immediate loss of export markets would nonetheless result in catastrophic economic losses

The establishment of ASF in pig populations in Eastern Europe and China has significantly increased the likelihood of the introduction into the US pig population. Its ability to survive for long times in a variety of materials, including pork products, makes it a real threat to travel the distance and infect US pigs. Indeed, with the trillions of ASF viral particle already produced, it is not hard to imagine that one or more of them has already found its way to North America, but subsequently did not find its way into a pig.

The multiple effects of Emerging Infectious Diseases (EID’s), especially hemorrhagic diseases such as ASF, have been mostly studied in human populations, but many of the generalities are appropriate in our preparations.Over the past 9 years the University of Minnesota’s College of Veterinary Medicine has led efforts in capacity building in USAID’s Emerging Pandemic Threats program of USAID. This, in turn, was part of the a broader set of efforts called the Global Health Security Agenda, which expends billions of dollars annually to control and prevent diseases such as MERS, Ebola and SARS.

In negotiating, planning and implementing strategies I came to a number of realizations, but a few came up repeatedly.The first is that population or public health is in short supply in many parts of the world. It is a central part of our swine medicine, but those thought processes are often not evident in human medicine, outside agencies such as the CDC.Many countries lack the luxury of such capabilities, both for human and veterinary medicine. Many countries are dependent on international collaboration, and such veterinary collaborations are underfunded.

The other major lesson is that people rarely act rationally in the face of potential epidemics. The combination of fear, rumors, misinformation and ignorance results in damage that goes far beyond the costs of the disease and its control. Economies are often severely affected, with fear driving a restriction in commerce, tourism and even basic policing.The resultant or exacerbated poverty can result in as much of an insult on health as the infectious disease of concern.

A challenge with the introduction of ASF, or any novel reportable disease, into the US swine herd is that we have a good idea on the behavior of the disease. Frankly, there are many diseases in our pigs that are more difficult to control. ASF moves relatively slowly and can be putatively recognized through its and excellent capabilities to isolate, trace and eradicate the disease. We lack, mostly, the major risk factors of feeding food products and backyard herds. The one concern is our extensive feral pig population, but concerted methods to reduce that exposure are available.

Inasmuch as we understand the behavior of the disease, the behavior of farmers, governments, business and farmers are more difficult to predict. With a loss of 25% of the market (plus any exports in transit being returned), those farmers dependent on public price discovery face the prospect of having no market. The devaluation of inventory and farms will result in decreased ability to finance operations.One or more farms will be affected directly by an ASF infection with rapid depopulation. If more farms are close to the infected farms, they too will be depopulated. However, for some time all farms will be severely affected by the elimination of export markets. Transport, especially between states, will often be stopped. Pigs will back up on the farms, with those that go to slaughter being highly devalued. Money for feed, disease control and other inputs will be hard to secure. Payrolls will not be met and employees will look for more promising jobs in other industries.

Much of our planning has been on disease readiness, and rightly so, as the speed and competence in which the disease is brought under control will determine the speed under which markets will be reacquired. Markets are quick to shut down borders and slow to open them. Most scenarios have regaining of all historic markets measured in years, however.Thus, we not only need disease management but supply management. The economics of pig production are brutal, with oversupply resulting in what can be described as death matches, with the survivors also compromised by the times of low prices and the industry stripped of many of its capabilities.

The industry is now completing many simulations of disease management in the face of the identification of pigs infected by ASF in the US.Depopulation to control disease is readily discussed and modelled to regain markets. Beyond this purpose, depopulation and restriction of production is often ignored, but it may be as important to regain market equilibrium and perhaps even price discovery. For the aggregate industry, there is real benefit to create strategies to combine the benefits of both, actively depopulating all potential contacts, not only through location but also through transportation and management networks.

A term in human health management is the “social determinants of disease”. Of these social determinants, none looms larger than poverty.In the same way, we need to recognize that disease affects economics, but economics also affects disease. Competent and invested care is best delivered on farms that are financially healthy. A rapid restabilization of the industry serves not the owners and employees, but also pigs and the public.

Science Page: To filter or not to filter, that’s not the question anymore!

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, Drs. Torremorell and Janni explain what is new in the world of air filtration.

Key Points

  • There are multiple components that affect the effectiveness of filtration for a particular farm.
  • Virus concentrations, particle size, and prevalence of particle size impact virus concentration within the barn.
  • Filtration type and functionality over season can also affect virus concentration within the barn.

Long gone are the days when we debated whether it’s beneficial to install air filtration in a farm. If you are in a high dense area and you have new breaks often enough that filtration pays off, then filtrate! Whether it is the removal of virus from the air (which is what filters do), or the enhancement and enforcement of basic biosecurity measures which are part of the “filtration package”, air filtration has been shown to reduce the number of PRRSV (porcine reproductive and respiratory syndrome virus) breaks.

However, filtration has not always met farm owner expectations. Retrospective data analysis from the Morrison Swine Health Monitoring Project suggests that PRRSV incidence hasn’t been reduced as much as we had hoped for, although it’s still better than no filtration.

So, what can be going on?

To help producers and veterinarians to contrast and compare filtration options and to help understand the components that affect filtration, we created a model that estimates the theoretical number of airborne viruses that would enter a barn through either filters or through leakage given certain assumptions.

The model takes into account various inputs considered important to affect filtration and provides a look at the interaction between ventilation rate, building leakage, filter particle removal efficiency and particle size distribution where viruses may attach.

We have learned a few things already.

First, and the obvious one, is that filtering ventilation air does decrease virus concentration inside filtered barns. Second, ambient virus concentrations and their size distributions, which are largely unknown, have a large impact on virus concentration inside the barn. Although we have done some measurements of virus distribution based on particle size, the relative distribution is likely affected by various factors such as environmental conditions, type of virus, source of virus aerosol, etc.

In general we can say that if viruses are found mostly in the smallest particles (<1 microns), MERV 14 filters will do quite poorly since their lowest removal efficiency is for particles less than 1 micron (~ 76% removal efficiency). In contrast, if the largest amount of virus is found in medium and large particles (>1 micron), as our studies suggest, then MERV 14 filters should do quite well and the more viruses there are in the largest particles (>3 microns), the better MERV 14 filters do and in this case performance is similar to MERV 16 filters.

However, since virus particle size distribution is likely to change throughout the day and season, the only way to minimize the impact of virus particle size distribution is by using higher MERV rating filters with removal efficiencies above 95 % if not more. But, the overall importance of filter collection efficiencies is uncertain because the ambient virus concentrations and their size distributions are not really known.

The other point that is important to recognize is that there are higher barn virus concentrations with lower mechanical ventilating rates and higher barn leakage rates. In other words, during low ventilation rates (i.e. winter) the number of virus particles per cubic feet per minute is higher than during high ventilation rates (i.e. summer). However, when we consider total amount of virus particles that may enter the barn per minute, then higher ventilation rates result in higher in-barn virus concentration compared to lower ventilation rates. This observation is important also when considering positive ventilated barns since it is not uncommon that in the winter, they operate at higher flow rates than negative ventilated barns resulting in the potential introduction of more viruses through the filter, even though leakage is nearly eliminated.

Lastly, as it is well known reducing barn static pressure drop by increasing filter area helps reduce leakage and virus concentrations in the barn. So, it is not a question whether air filtration helps, but rather knowing which factors to consider when making the best of air filtration. Our model does not measure risk of PRRSV infection into a farm but it shows a fairly complex, not always obvious, interaction between ventilation rate, building leakage, filter particle removal efficiency and viral particle size distribution that knowing it, may be useful to producers and veterinarians when evaluating air filtration systems for sow farms.

For more information about the model, contact Kevin Janni (kjanni-at-umn.edu) or Montse Torremorell (torr0033-at-umn.edu) at the University of Minnesota.

Science Page: Biosecurity screening tool; Benchmarking PRRSv biosecurity vulnerability using a short survey

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 Dr. Linhares’ lab at Iowa State University. In this Science Page are the results of a study looking at biosecurity aspects associated with PRRS frequency.

Key Points

  • New methods allow estimation of the overall PRRS-vulnerability risk score by asking 20 or less questions.
  • This can help producers and veterinarians to (a) measure and benchmark key biosecurity aspects, and (b) toidentify sites at relatively higher (or lower) risk of PRRSv introduction.

Study Summary: This study aimed to identify a small set of biosecurity aspects that, when combined, have a strong association with the frequency of PRRSv introduction into swine breeding herds.

Parameters included in the 2 models (A and B) to predict the number of PRRS outbreaks in farms for the past 5 years.

Preliminary Results: A cross-sectional study assessed biosecurity aspects in 84 breeding herds from 14 production systems in 2017. Models were trained to predict whether a farm had or not reported a PRRS outbreak in the past 5 years, given a set of biosecurity aspects. Two methods were used, and both models were able to classify the herds with a great overall performance based on few biosecurity aspects (See figure). The variables used by both methods were related to the frequency of risk events in the farm, swine density around the farm, farm characteristics/ requirements to visitors, and operational connections to other sites.

Note: The Gini coefficient (or index) is a single number aimed at measuring the degree of inequality in a distribution. (Source: Wikipedia) The higher the number, the less equally distributed the farms will be.

When comparing the predicted positive value obtained by the models, they showed a strong positive correlation (0.7 and 0.76, respectively) with the frequency of past outbreaks.

Enroll on our follow-up study: Study farms will be asked to fill a short survey. Using the methods above, the PRRS-vulnerability risk score will be generated for each farm enrolled. The information will be collected via an Excel file and the name of the farms and production systems will be kept confidential.

To enroll or request additional information please contact: Gustavo Silva (gustavos-at-iastate.edu) or Daniel Linhares (linhares-at-iastate.edu) at Iowa State University.

Science Page: Assessing the relative vulnerability of swine breeding herds to the introduction of PRRS virus

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 Dr. Daniel Linhares’ lab at Iowa State University. The report summarizes the findings of his study regarding the factors making a sow farm vulnerable for PPRS introduction. 

Key Points:

  • A model to quantify and identify biosecurity vulnerability in breeding herds is now available.
  • Events related to swine movements, transmission by air and water, and people movements were the variables most associated with PRRS outbreak.
  • Biosecurity vulnerability scores may help producers/veterinarians prioritize biosecurity investments.

Study Summary:

Herd-specific biosecurity assessments are needed to determine herd-specific risk for PRRS outbreaks. Thus, we developed and validated a biosecurity vulnerability score (BVS) that measures the relative vulnerability of swine breeding herds to PRRSv introduction. The BVS was based on a multi-criteria decision algorithm that ranked risk events associated with outbreaks. A comprehensive biosecurity assessment was used to obtain information of the biosecurity practices from each participating herd. The practices performed in each herd were weighted by the relative importance of each event obtained from an expert opinion panel resulting in a score that identifies the events that should be prioritized. In two independent data sets, the scores consistently revealed that farms with higher scores had a higher frequency of PRRS outbreaks. In addition, results suggest that events related to swine movements,transmission by air and water, and people movements should be prioritized.

Follow-up study:

We are developing a new screening tool to validate the minimum number of questions associated with frequency of PRRS outbreak. Study farms will be asked to fill out a short survey. This can help producers and veterinarians to identify sites at relatively higher risk of PRRSv introduction.

To enroll or to request additional clarification please contact: Gustavo Silva at Iowa State University (gustavos-at-iastate.edu)