PRRS Elimination – Next Steps for the U.S.: A podcast

Podcasts are a perfect way to get caught up with new swine information! We are presenting you the latest episode from “At The Meeting… Honoring Dr. Bob Morrison” in collaboration with SwineCast.

Doing what we know how to do” is the best next step in efforts to eliminate PRRSv from the U.S. herd. The At The Meeting team presents a clear agenda in its continuing conversation with Dr. Scott Dee (Retired Director of Applied Research, Pipestone Veterinary Services) and Dr. Reid Philips (PRRS technical Brand Manager, Boehringer Ingelheim). The group acknowledges that PRRS elimination won’t be easy or immediately profitable, but a patient, persistent and proactive approach will yield success.

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Chart 3 description: PRRS incidence rate by status at break

In this science page we would like to review one of our charts that tends to be more difficult to interpret, yet it conveys a valuable interpretation of the MSHMP data. Chart 3 – PRRSv Incidence rate can be tricky to interpret at first because it reflects the dynamic nature of swine herd health and, consequently, the MSHMP data. Since PRRSv health statuses are not static over time, a farm can experience PRRSv status changes throughout the year. This happens in a variety of ways, such as moving towards a naïve status, introducing vaccine(s), or experiencing a new PRRSv outbreak. The situation becomes more complex by the fact that a farm listed as having recently moved to a PRRSv status 1 can break again with another PRRSv strain. Therefore, we consider each farm is at risk for breaking with PRRSv regardless of its current status.

Chart 3 calculates the PRRS Incidence Rate according to the health status farms had at the beginning of the MSHMP year (Jul 1st). This chart addresses the question: “How frequently do farms that started the MSHMP year in each of the different PRRSv health status break with PRRSv throughout the year?”. Therefore, Chart 3 estimates the number of outbreaks within each status while taking into account the time at risk (i.e. number of weeks in that given status). For instance, if 10 sites started the year as status 2, one breaks with PRRSv within 5 weeks and a second one breaks within 20 weeks, while the rest remain with no PRRSv breaks throughout the year, their time at risk (i.e., time in the original status) is 5 (for the first site), 20 (for the second site), and 52 (for each of the remaining 8 herds) weeks, respectively. The incidence rate would be 2 (total number of breaks) divided by 441 farm-weeks (5+20+(8*52)), or an incidence rate of 0.0045. This means that, on average, the 10 hypothetical sites that started the year in status 2 experience PRRSv breaks at 0.0045 breaks per week. Farm-week is the nomenclature of the standardization of the different contribution times of each site. Similarly, the contribution time can also be standardized to represent years instead of weeks.

Using the Chart 3 example below, the incidence rate for PRRS status 2 farms is 0.0049 cases per farm-week or 0.2537 cases per farm-year. Alternatively, we can multiply those rates by 1,000 and have an incidence rate of 4.9 cases per 1,000 farm-week or 253.7 cases per 1,000 farm-years. In other words, if 1,000 farms are in status 2 in a given week, approximately 5 are expected to experience a PRRSv outbreak (0.0049 x 1,000 farm-weeks). Or annually, if 1,000 farms are in status 2 during the year, then approximately 254 farms are expected to experience a PRRSv outbreak (0.2537 cases x 1,000 farm-years).

Although weekly incidence rate is not visually intuitive, it allows a more nuanced and accurate reflection of the rate in which a site might break with PRRSv given its initial PRRSv status at the beginning of the year. Chart 3 in the MSHMP reports allows us to notice that sites in status 2fvi have an overall higher incidence rate than sites in status 4. Also, it also allows us to quickly notice any drastic change in patterns, such as sudden incidence rate increases in a particular status of interest as it is currently the only swine health monitoring metric that provides an objective measure of disease occurrence since it does have a farm denominator. If you have any comments or questions about the MSHMP PRRSv Chart 3, please do not hesitate to contact Cesar Corzo at

Tools to Fight PRRSv: Too Soon to Admit Defeat: A podcast

Podcasts are a perfect way to get caught up with new swine information! We are presenting you the latest episode from “At The Meeting… Honoring Dr. Bob Morrison” in collaboration with SwineCast.

Decades of hard work have produced a wide assortment of tools to fight the spread of PRRSv. Success and failure and no silver bullets have discouraged many – leaving the impression that the PRRSv cannot be eliminated.

The At The Meeting team documents how far the pig industry has come with two front-line leaders in the PRRSv battle: Dr. Scott Dee (Emeritus Director, Discovery and Innovation, Pipestone Research) and Dr. Reid Philips (PRRS Technical Manager, Boehringer Ingelheim Animal Health Inc USA).

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Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1

Today, we are sharing a new publication from the VanderWaal research lab at the UMN. In this article published in Microbiology Spectrum, Dr. Dennis Makau et al. estimated the likelihood of serum-virus cross-protection between PRRSV-1 viruses and identified important amino acid sites influencing antigenic variability between viruses. Additionally, they investigated how differences in those amino acid sites contributes to the antigenic variability between the viral isolates.

IMPORTANCE Understanding cross-protection between cocirculating PRRSV1 strains is crucial to reducing losses associated with PRRS outbreaks on farms. While experimental studies to determine cross-protection are instrumental, these in vivo studies are not always practical or timely for the many cocirculating and emerging PRRSV strains. In this study, we demonstrate the ability to rapidly estimate potential immunologic cross-reaction between different PRRSV1 strains in silico using sequence data routinely collected by production systems. These models can provide fast turn-around information crucial for improving PRRS management decisions such as selecting vaccines/live virus inoculation to be used on farms and assessing the risk of outbreaks by emerging strains on farms previously exposed to certain PRRSV strains and vaccine development among others.

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Time to a new PRRS outbreak in naïve breeding herds

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.

In today’s Science page, MSHMP researchers Mariana Kikuti, Catalina Picasso-Risso, Claudio Marcello Melini and Cesar Corzo share data regarding the time it takes for naïve breeding herds to break with PRRSV.

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