Improvement of monitoring and surveillance systems for porcine reproductive and respiratory syndrome virus in the United States swine industry

Abstract

<p>Porcine reproductive and respiratory syndrome (PRRS) is the most economically significant disease affecting swine production in the United States (US). The etiologic agent of PRRS is an RNA virus named as PRRS virus (PRRSV). Substantial economic losses attributed to PRRS are due to reduced reproductive performance in sows and reduced growth rate and increased mortality in growing animals. In the US, PRRSV activity is routinely monitored by production systems and/or veterinary clinics. A group of swine production systems in the US voluntarily share their PRRSV breeding herd incidence to a program that gathers, aggregates, and reports the weekly incidence and prevalence among participants. As of February of 2020, most of the participants are from large production systems that represented 2.8 million sows. Currently, there is no information on PRRSV detection in the broader industry which totals of 6.46 million sows. Additionally, American Association of Swine Veterinarians (AASV) guidelines for PRRSV monitoring (from 2011) was based on the use of serum samples. However, there is a recent description of processing fluid as a population-based sample type to monitor PRRSV herd status more efficiently. The validation of this new sample type raises the need to better understand the practical applications of this sample type to monitor PRRSV. Considering (a) the high economic importance of PRRS to the US swine industry, (b) the current gap of information about PRRSV activity in most breeding herds, and in growing animals, and the (c) gap in knowledge about applications of processing fluids to monitor and surveil PRRSV, there is the critical need to develop additional tools for improvement in the monitoring and surveillance systems for PRRSV in the US swine industry. Therefore, the overall objectives of this dissertation were: a) to develop a capability to reliably and consistently track PRRSV detection over time, age group, geographical space, and specimen in the US swine industry; and b) to develop monitoring and surveillance systems to enable veterinarians to make science-driven decisions to support disease prevention, detection, and control strategies. To that end, a capability to monitor and report the detection of PRRSV RNA by RT-PCR at the four major US swine-centric veterinary diagnostic laboratories was built. A procedure to receive data, a process to compile to the same format, aggregate, report, and a capability for continuous automated updates was developed. This information was used to describe the macroepidemiological aspects of PRRSV RNA detection by RT-PCR in the US (Chapter 2). An algorithm based on a cyclic regression model was incorporated to scan the database, forecast the weekly results for the upcoming year, and monitor the expected vs. the actual detection (Chapter 3). A field longitudinal study investigated the practical application of processing fluid to monitor breeding herds undergoing virus elimination (Chapter 4). A strategy to use PRRSV RT-PCR testing results from processing fluid samples was developed to classify weekly batches of newborns piglets, 2 to 5 days old, according to PRRSV exposure status. Moreover, the association of the PRRSV exposure status with the subsequent nursery mortality was investigated in a field longitudinal study (Chapter 5). In summary, the described macroepidemiological aspects of PRRSV detection in Chapter 2 documented: a) an increased number of submissions tested for PRRSV over time; b) detected the rise and increased usage of processing fluid samples for PRRSV testing; c) restricted US geographical distribution of PRRSV-1 when compared with PRRSV-2; and d) an apparent cyclic pattern of PRRSV detection in the US. The algorithm described under Chapter 3 was able to scan the PRRSV detection in the US, forecast the expected percentage of positive results for the upcoming year, and monitor the observed detection, with an added ability to issue an alert signal for abnormal detection. Chapter 4 described the usage of processing fluid as a practical sample type to be used as a tool to screen breeding herds undergoing virus elimination. Chapter 5 presents a useful way to classify weekly batches of newborn piglets according to the PRRSV exposure status and demonstrated the association of subsequent nursery mortality. The highest observed downstream mortality difference was for groups classified as PRRSV exposure group "low Cq" (Cq < 27) vs. "medium Cq", high Cq", and or negative PCR." Altogether this dissertation presents science-driven solutions to improve the monitoring and surveillance systems of PRRSV in the US swine industry. Findings are directly applicable to monitor PRRSV virus detection at the macroepidemiological/national level by using aggregated testing results from VDLs. PRRSV detection data can be scanned by an algorithm to inform US swine stakeholders on observed abnormalities in rates of PRRSV detection. The use of processing fluids to monitor herds undergoing virus elimination and to classify weekly batches of newborn piglets according to PRRSV status can assist veterinarians in making informed decisions for prevention, detection, and management of PRRS to reduce the losses caused by the PRRSV and secondary bacterial infections.</p>