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.
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.
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.
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.
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:
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.
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.
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 http://stemma.ahc.umn.edu/optisample.
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.
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.