Science Page: Sow Farm PRRS status classification 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 survey from the MSHMP team on the different protocols used to classify PRRS status.

Key points

  • The majority of veterinarians consider it important to classify sow herd PRRS status.Our survey showed that 8/21 follow AASV guidelines, with the others using alternative criteria.
  • Half of the surveyed veterinarians use processing fluids as part of their testing protocol for determining sow herd PRRS status.
  • Most of the respondents mentioned that AASV PRRS classification guidelines should be re-visited.

Twenty-one veterinarians from 12 participant systems and 1 non-participant group completed the questionnaire accounting approximately for 1.5 million sows.

When asked how important it was to classify sow farm PRRS status, 12/21 (57%) answered very important, 8/21 (38%) answered important. Among the most important reasons requiring PRRS status were:

  • Commingling of pigs downstream,
  • Timing the Depopulation/Re-population of growing sites with continuous flow, and
  • Defining gilt acclimation and introduction procedures.

The testing protocol to classify a farm as stable varied across and within systems. However, the most frequent sample collected was due-to-wean blood sampling. Other samples are shown in the figure below.

PRRS classification survey


Science Page: Assessment of PRRS area spread for sow herd outbreaks in US swine dense regions

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 project from Dr. Andreia Arruda in collaboration with the MSHMP team regarding Porcine Reproductive and Respiratory Syndrome virus (PRRSV) area spread for sow herd outbreaks in US swine dense regions.

Dr. Arruda has also been investigating PRRS seasonality in the US and how topography surrounding a farm influences outbreak risk.

Key points

  • Strong evidence of area spread was not found after evaluating three farm clusters located in two swine dense regions.
  • All barns of a nursery/finishing site should be sampled to define status.
  • Sick pen might not be the best target when sampling for PRRSV in grower pig sites

Background and Objectives

Area spread refers to the transmission of a pathogen (here PRRSV) through small particles in the air as well as through fomites on which the pathogen would have deposited on.

The objective of the study was to determine if the virus detected in a recently infected sow farm was similar to the one detected in neighboring farms (in other words: was local spread a likely source of infection?)

Methods and Results

35 farms were monitored for PRRSV. As soon as a farm broke, all of the neighboring farms were sampled for PRRSV independently of the type of production on site. If a sick pen was present on the farm, effort was made to include it in the sampling. Positive samples were then sequenced to compare to the original virus from the outbreak.

PRRS area spread arruda
Graphical representation of the results of one specific region.

For two of the three area spread assessments performed, no similar sequence to the one obtained from the farm under investigation was found. Also it was not always possible to detect PRRSV in sick pens of the growing pig sites sampled in our study.

Best of Leman 2017 series #6: A. Arruda – New insights into PRRS seasonality across US regions

We launched a new series on the blog in October. Once a month, we are sharing with you a presentation given at the 2017 Allen D. Leman swine conference, on topics that the swine group found interesting, innovative or that lead to great discussions.

Our sixth presentation is by Dr. Andreia Arruda from the Ohio State University sharing the work she did in collaboration with Dr. Morrison regarding PRRS seasonality as well as the environmental factors that are protective against a PRRS outbreak.

For more information regarding PRRS summer outbreaks, you may take a look at this report by Dr. Sanhueza from the MSHMP team.

To listen to this talk, please click on the image below.

Leman Arruda PRRS seasonality

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.


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

Science Page: Investigating the role of the environment and the lactating sow in PRRSV infections during an outbreak (Part 1)

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. Carles Vilalta and Dr. Juan Sanhueza in collaboration with Dr. Montse Torremorell discuss the sensitivity and specificity of sampling the farrowing environment and lactating sows at processing to detect PRRSV in an infected farm.

Key Points:

  • Lactating sows and the farrowing environment can be sources of PRRS virus
  • Sampling the farrowing environment and the udder skin of lactating sows can be used to monitor for PRRSV although the sensitivity is lower than that of serum samples.
  • The farrowing environment and the lactating sow may serve as a source of infection for PRRSV.

Sampling started 2 weeks after a PRRSV outbreak was reported in a sow farm. Sampling was conducted from 10 litters every 3 weeks for a total of 24 weeks. Samples were collected at processing (~ 3 days of age) and included: surface wipes of farrowing crates, surface wipes of the udder skin of lactating sows, blood samples from all piglets within the selected litters.

PRRS sampling in the environment and on the sows.gif
Scatter plot of the individual RT-PCR Ct values in serum (all piglets) compared with those from surfaces (A) and udder skin (B).

PRRSV was detected in the farrowing crate environment and on the skin of the lactating sow at processing. The surface and udder skin wipes were less sensitive at detecting PRRSV than serum PCR at processing. However, in this study all pigs in the litter were bled which is not the standard practice in the field.

The results show that the environment and the lactating sow may serve as a source of
infection for PRRSV, indicating a need to further understand their roles to establish herd level stability.

Science Page: Why are we not making more progress to decrease PRRS incidence?

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. Clayton Johnson from Carthage Veterinary Services on PRRSV incidence and why it has not been decreasing as expected at the past few years.

Key points

  • Enhancing biosecurity increases the chances to prevent PRRS.
  • We have learnt to deal better with the disease and that is reflected by the reduction of the economic impact of PRRS
  • Choose the level of biosecurity that economically better fits to your risk.

In his report, Dr. Johnson identifies 3 main causes that PRRSV incidence is not decreasing.

  1. We can’t Prevent PRRS Infections
  2. PRRS Cost is Decreasing: Tools and Technologies for PRRS Infection Management are Improving
  3. PRRS Prevention Strategies aren’t Cost Effective

To learn more you can read the full report or take a look at Dr. Johnson’s presentation on this very same topic during the 2017 Leman conference: