Tag: PRRS

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)

Cold plasma technology to clean swine barn air

Porcine reproductive and respiratory syndrome virus (PRRSv) costs the US swine industry more than $580 million each year. First described in North Carolina, Iowa, and Minnesota in the late 1980s, the virus rapidly spreads through swine barns and is one of the industry’s biggest game changers. Additionally, pigs infected with virulent strains exhales aerosols containing a large quantity of the virus.

Today, researchers in the Veterinary Diagnostic Lab at the CVM are looking to apply research they are doing on decontaminating foods in collaboration with the University of Minnesota College of Science and Engineering (CSE) to swine barn air filtration in an effort to further promote swine health and safety in the food industry at large.

Plasma, served cold

Plasma is defined as partially or fully ionized gases with neutral net charge. It consists of a cocktail of photons, ions, free radicals, molecules, and atoms—many of which are highly reactive, which allows for many applications, including water decontamination. Plasma sources can also be engineered to produce plasma at close to room temperature—often referred to as cold plasma—enabling the treatment of highly heat-sensitive surfaces, such as some foods.

2D- integrated coaxial micro hollow dielectric barrier plasma discharge array
Plasma (purple) is produced inside the holes of the array, through which air is blown. Pathogens are inactivated when they come into contact with the air coming through the holes in the array.

The United States Department of Agriculture is supporting Sagar Goyal, PhD, professor in the Department of Veterinary Population Medicine at the CVM; Peter Bruggeman, PhD, professor of Mechanical Engineering at the CSE; and their team of researchers in pursuing the use of cold atmospheric gaseous plasma technology for decontaminating food and food-processing surfaces.

The team is seeing success in the lab—bacteria and viruses stand little chance against the cold plasma they are making.

According to Goyal, the laboratory results look extremely promising. “If a surface is contaminated with viruses or bacteria, we can kill them,” says Goyal. “If food is contaminated—as early as during harvest by food handlers—our goal is to use cold plasma to kill the contaminants.”

A pig impact

“Meanwhile,” says Goyal, “swine farmers are already using air filtration systems to mitigate disease. But these are not foolproof, so if we can combine them with this cold plasma, it would be helpful in getting rid of any disease affecting swine that can be transferred by air.” This includes, but is not limited to, PRRSv. So, cold plasma could positively impact the food and agricultural industry in more ways than one.

Follow the link to read more about how cold plasma could be used in swine barns.

The effect of season on PRRS time-to-stability in the Midwestern United States

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.

Key Points

  • Seasonal conditions may effect the time to stability of a farm
  • Understanding seasonal effects on time to stability can help producers and veterinarians plan herd closures

This week, we are sharing a report by the MSHMP team in collaboration with Dr. Andreia Arruda from the Ohio State University regarding the impact of seasons on PRRS time-to-stability.

The time needed between an outbreak and consistently weaning porcine reproductive and respiratory (PRRS) virus PCR negative pigs is referred to as time-to-stability (TTS). In this analysis we describe differences in TTS according to the season when the PRRS outbreak occurred in farms located in the Midwestern United States.

161 PRRS outbreaks in 82 sow farms were classified based on the date of the outbreak:

  • March 21st to June 20th: Spring
  • June 21st to September 20th: Summer
  • September 21st to December 20th: Autumn
  • December 21st to March 20th: Winter

TTS was calculated as the time from the reported PRRS outbreak to the time of the last PRRS PCR negative result in wean-age pigs.

A significant difference was detected in TTS among seasons. The median TTS was higher in spring and summer, compared to autumn and winter.

An explanation for the observed TTS difference among seasons may be found in environmental survivability of the virus as for PRRS outbreaks that occur during spring or summer, the last phase of the stability process coincides with the arrival of winter where the reduced ventilation and decreased temperature within the farm may favor PRRS survival resulting on a lower likelihood of elimination during this time.

PRRS time to stability season

Science Page: Making epidemiological sense out of large datasets of PRRS sequences

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 epidemiological report regarding a large PRRS sequence dataset from Dr. Igor Paploski in the VanderWaal research group.

Key points:

  • Occurrence of PRRS lineages is not equal in different years, systems or production types
  • Occurrence of specific PRRS lineages is associated with movement of animals
  • Continuous surveillance for PRRS occurrence is important in understanding its determinants and might be able to provide insights that can
    help on its prevention

By utilizing a dataset of 1901 PRRS sequences provided by the Morrison Swine Health Monitoring Project (MSHMP) participants over 3 recent years, the spatiotemporal patterns in the occurrence of different lineages of PRRSV was described and the extent to which the network of pig movement between farms determines the occurrence of PRRS from similar lineages was investigated.

PRRS lineages occurred at different frequencies across geographically overlapping production systems. Preliminary analysis showed that the relative frequency in which specific lineages occur increase while others are decrease over time. The rate at which these changes occur appears to be system-specific. Some lineages were also more common in farms of specific production types (i.e. sow farm or nurseries). As expected, farms that were connected via pig movements were more likely to share the same lineages than expected by chance across all years.

These findings suggest that system-specific characteristics partially drive PRRS occurrence over time and across farms of different production types. Our results also
indicate that animal movement between farms is a driver of PRRS occurrence, strengthening this hypothesis of viral transmission.

Additional research is needed to quantify risks and develop mitigation measures related to animal movement.

Large PRRS sequencing dataset

Use of processing fluids and serum samples to characterize PRRSv dynamics in 3 day-old pigs

This new publication in Veterinary Microbiology describes the best methodology to monitor 3-day-old piglets for PRRS, using both serum and processing fluid samples. The first author of the publication is Dr. Carles Vilalta, member of the Morrison Swine Health Monitoring Program (MSHMP) team.

Key points

  • Processing fluids (PF) constitute a useful sample to detect PRRSV infections at processing.
  • PRRSV can circulate in the farm at a low prevalence, increasing the chances of a re-break.
  • Young parity female litters should be targeted for PRRSV detection.
  • Current practice to bleed 30 pigs could be underestimating PRRSV prevalence in the herd.
  • The decrease in sensitivity at the litter level can be compensated by sampling more litters to detect PRRSV at the herd level.

Methods

The study was conducted in a 6,000 sow farm with a PRRS stable status. Every 3 weeks, serum samples and processing fluids were collected from all piglets in 10 randomly chosen litters. This process was then repeated 8 times, meaning that the farm was monitored for a total of 24 weeks. All samples were tested via PCR. 3 samples with the lowest Ct value were tested by virus isolation and sequencing of the ORF5 gene was performed.

Results

10.6% of the piglets tested positive for PRRSv via serum PCR, representing 29.8% of the litters. The same number of litters tested positive via processing fluid PCR testing.

The percentage of processing fluid positive samples was significantly higher is parity 1 and 2 sows compared to parity 3 and older sows. Additionally, a significant association between parity and probability of detecting a positive pig was observed.

A significant higher proportion of positive serum samples was observed in males compared to females. A similar trend was obtained when comparing positive Ct values by gender with values from males being lower (i.e., higher viral load) than those from females.

ct value processing fluids versus serum samples PRRS
Cycle threshold (Ct) positive (≤35) and suspect (between >35 and 40) value distribution for serum (S, triangle) and processing fluid (P, circle) samples overtime (2, 5, 8, 11, 14, 17, 20 and 23 weeks post outbreak). Horizontal black lines indicate the mean Ct values for each week and sample type

Using a Ct value of 37, processing fluid samples had a Se and Sp of 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%), respectively when compared with litter RT-PCR results obtained from individual serum samples. The total agreement between both tests was 92.2% and the positive and negative predictive values were 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%), respectively. False negative processing fluids were identified in litters having 2 or less PRRSV positive piglets

The agreement between the PF and serum results was kappa = 0.81 (95% CI: 0.59–1.00). The difference in the proportion of positive samples between both types of sample was not statistically significant (McNemar test, p = 1).

Abstract:

Collection of serum samples of pigs at weaning to monitor for porcine reproductive and respiratory syndrome virus (PRRSV) has become a common practice to determine PRRSV herd infection status. Diagnostic sensitivity of this practice is low in herds undergoing PRRSV elimination once prevalence of infection is near zero. Thus, the goal of this study was to characterize the dynamics of PRRSV infection in 3 day-old pigs overtime using serum and serosanguineous fluids obtained as part of castration and tail docking practices (processing fluids (PF)). Secondary goal was to estimate sensitivity and specificity of PF in the 3 day old population. A 6000 breed-to-wean sow herd was monitored every three weeks for 23 weeks after a PRRSV outbreak by collecting both PF and individual serum samples from all pigs in the selected litters. Out of the 77 litters tested, 23 (29.8%) were identified as positive using the PF and the serum samples, with a Cohen’s kappa statistic of 0.81 (95% CI: 0.59–1) between the results obtained in each sample type. The sensitivity and specificity of the PF relative to the results in serum was 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%) respectively. The percentage of PRRSV positive litters decreased over time and litters from gilts were more likely to test positive than those from older sows. Overall, the study demonstrates that PF can be a convenient and reliable specimen to monitor PRRSV infection in breeding herds.

Follow the link to read the entire article.

Science Page: Quarterly review of MSHMP reported PRRSv Restriction Fragment Length Polymorphism (RFLP) patterns

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 from the MSHMP team regarding reported PRRS RFLP patterns.

Keypoints:

  •  Recording PRRSv RFLP and sequences will provide better insights into the epidemiology of the disease at local, state and national level.
  • Building a RFLP database will allow us to assess which factors could be involved or related with the emergence of a new RFLP.
  • The predominant pattern RFLP in this quarterly review is the 1-7-4.

In the first quarter of the 2018/2019 incidence year, 20 breaks affecting 12 production systems were reported. Out of these, 4 occurred in July, 13 in August and 3 in September.

Of those 20 farms, three had a break while still being status 1, one was status 2 in the process of eliminating the disease (not using any immunization protocol at that point), 6 were using field virus as the acclimatization protocol (2fvi), 8 were using vaccine (2vx), one was provisionally negative (status 3) and one broke from a status 4 after being almost 4 years completely negative (see figure below).

RFLP patterns with status at break

The distribution of the breaks is wide and affects different states. Thus, we had 6, 1, 4, 1, 4, 2, 1 and 1 break in the states of IA, IN, MN, MO, NC, NE, OK and PA, respectively. The closest 2 farms that broke were 1.2 miles apart, belonged to the same company and had the break a week from each other (no sequences was provided).

Eight out of the 20 breaks reported were accompanied by the associated RFLP. The predominant (4 out of 8) RFLP pattern since July is 1-7-4. Iowa was the state with the highest number of 1-7-4 cases.