By Cesar A. Corzo, Juan Sanhueza and Carles Vilalta, University of Minnesota Morrison Swine Health Monitoring Project
It is well documented that when herds have a high health status they will perform at an optimum level as it has been measured through classical key performance indicators such as reproductive performance, mortality rate, average daily gain and feed conversion which is all translated into a stronger financial balance. Breeding herds that plan to eliminate a specific pathogen have a variety of options as elimination has become popular in the last two decades as a result of a better understanding of the epidemiology of diseases.
An orchestrated set of steps considering herd immunity, pig flow and management measures focused on preventing within-herd transmission are required to achieve elimination without depopulation. As veterinarians and producers embark into these projects, they are aware that there is a probability of both success and failure. Their persistence and progressive attitude has allowed the industry to increase the probability of success. Perhaps the pathogen that is first on the list when it relates to elimination is the porcine reproductive and respiratory syndrome virus due to its costly nature.
At the University of Minnesota, and through the Morrison Swine Health Monitoring Project, a project was designed by Juan Sanhueza, Andreia Arruda and Carles Vilalta to understand whether PRRSV-infected breeding herds needed the same time to eliminate the virus or if there was variability at the system and herd level. A group of MSHMP participating production systems that had a similar PRRSV control and elimination philosophy and who used a similar testing and herd classification criteria were selected for the project. A dataset voluntarily provided by the production systems containing PRRSV outbreaks between 2011 and 2017 was used for analysis.
Statistical analyses were performed to understand variability on the time required to eliminate PRRSV from a breeding herd measured by the consistent production of PRRSV-negative weaned pigs which is commonly known as time-to-stability. Additionally, there was an assessment of factors that could potentially increase or decrease the window of time between the outbreak and elimination.
Overall, the median time between the outbreak to the last diagnostic test that confirmed a successful elimination was 41.5 weeks. A significant difference was detected when comparing the time to eliminate the virus across systems which speaks about the within system peculiarities. At the system level, an important variability was also seen in that each system had herds that would eliminate the virus between 30 and 50 weeks; however, there would be farms that would require twice as much time to reach the goal. The database contained herds that had experienced more than one outbreak, therefore, the within-herd variability was assessed. Interestingly, variability was also detected at the herd level indicating that the time to eliminate the virus differed between outbreaks. The mean raw difference between outbreaks across all herds was 20 weeks with a standard deviation of 12 weeks.
Understanding such variability is key for planning and budgeting, but also to continue to increase the odds of success. The assessment of factors related to the time required to eliminate the virus included season when the outbreak occurred, viral strain and immunity. The dataset showed clearly that herds that had an outbreak during spring and summer required a longer time to eliminate compared to herds that broke during the fall and winter. The mechanism by which this occurs is not well understood and requires further research. Viral strain also played a significant role in that herds infected with a specific strain, also known as 1-7-4, required more time to eliminate the virus compared to other viruses which may relate to the virulence characteristic of this virus.
Previous immunity was also associated with the time required to eliminate the virus. However, after accounting for these factors, the within-herd variability could not be explained from a statistical standpoint meaning that there are factors within the farm that are driving such variability which may potentially explain whether the program may have a higher or lower probability of success.
Understanding within-herd dynamics is a challenge the industry continues to face. The better we understand the interaction between these pathogens, our management systems and the role of farm personnel the higher the probability of drawing conclusions for successful interventions.