The key finding of this study is that the weekly probability of PRRSV PCR positivity at the AHL decreased during the Ontario PCVAD outbreak. Thus, the results of PRRSV PCRs generated through laboratory test requests are an untapped source of swine health data that could be monitored for heightened swine disease outbreak awareness. A large proportion of negative test results do not specifically identify the novel disease or disease pathogen. However, monitoring the trends of such negative results could provide an early indication of disease diagnostic dilemmas occurring in the field. In other words, monitoring the results of such first-order tests could be used as an early indicator of a disease outbreak, a form of syndromic data. This could improve the recognition of a novel outbreak without having to wait the extra time it takes to reach a definitive laboratory diagnosis through the use of follow-up tests. For the Ontario swine industry this could have beneficial implications for the timely detection of swine disease outbreaks and with identifying and utilizing novel data sources for such timely detection
The decrease in the weekly probability of positive PRRSV PCR results during the PCVAD outbreak could be extrapolated to suggest that practicing veterinarians were attempting to diagnose a new disease or syndrome (i.e., the PCVAD outbreak) by initially investigating for the presence of PRRSV through the use of the PRRSV PCR. Hence, monitoring PRRSV PCR requests, and more importantly, the results from these tests, has the potential to represent what veterinarians face in the field with respect to disease diagnosis. The PRRSV PCR used at the AHL did not change until after the PCVAD outbreak was resolved indicating that the changes in test positivity were not a result of changing test accuracy.
The results for the PRRSV ELISA model were not associated with the PCVAD outbreak likely due to data management issues identified in the study. Case submissions were not always clearly identified as to whether they were for monitoring or diagnostic purposes. Consequently, some submissions misclassified as diagnostic submissions were actually associated with routine farm monitoring and not part of a disease investigation. During the initial data management process, case submissions and test requests associated with semen specimens were dropped, as they were felt to represent herd monitoring for PRRSV instead of a disease investigation process. The ELISA, however, uses a serum sample that detects antibody, whereas the PCR, that detects antigen, is routinely performed on semen for boar stud herd PRRSV monitoring. Consequently, when cases associated with semen specimens were excluded, the PRRSV PCR data was likely more representative of true diagnostic cases versus monitoring cases.
The results of the PRRSV ELISA model may have also been influenced by many herd management and demographic changes that occurred in the Ontario swine industry during the study period. The number of total hogs in the province grew and the industry consolidated, with farms becoming larger and more species specialized
. With larger herd size came an increased awareness that disease outbreaks in larger herds have greater potential to create more severe mortality, morbidity, and economic consequences. Hence, management practices changed with respect to an increased understanding of the need for herd monitoring through testing
. For example, many on-farm PRRSV monitoring and eradication strategies were employed with the most common being the “test and removal” and the “herd closure and rollover” techniques
. Both involve frequent PRRSV testing of clinically normal animals.
This study highlights the importance of data quality at the time of collection. Mandatory field requirements on laboratory submission forms, such as those used by Gibbens et al., (2008), could improve upon the classification of monitoring versus diagnostic type cases
. In this study, case submission demographic information associated with the laboratory submissions was incomplete. For example, the age of the pigs being tested was not consistently recorded, and total animals-at-risk for a submission was often omitted. Additionally, the test requests and associated results could not be extracted from the database system together. This created considerable manual manipulation of the data to generate files that contained both the tests requested and associated results. The AHL currently has a new data management system in place with the main objective to improve disease surveillance activities and the utilization of such data.
The AHL is the largest veterinary diagnostic laboratory in Ontario and is the predominant laboratory used for swine diagnostics by practicing veterinarians in the province
. The Ontario Ministry of Agriculture and Rural Affairs (OMAFRA) partially funds food-animal producers/clients for certain testing at the AHL, which acts as an incentive for veterinarians and producers to use the services of the AHL. Consequently, data generated by the results of test requests at the AHL is believed to represent a large proportion of the diagnostic testing for the Ontario swine industry. Extrapolation beyond the Ontario swine industry should bear this in mind when considering inference to other swine populations. Use and interpretation of data from the diagnostic laboratory or laboratories representing the bulk of testing for the swine population under surveillance should be considered. Amalgamation of PRRSV PCR data from multiple diagnostic laboratories would have to ensure that the PRRSV PCRs were validated between laboratories
A bias that presents itself in this study, as well as other studies using laboratory- derived data for disease surveillance purposes, is that the pigs being tested by the AHL represent farms/producers that seek veterinary professional services. While a large proportion of herds in Ontario probably seek the advice of veterinarians
 and the services of the AHL, the exact proportion of producers conducting and not conducting PRRSV testing during the study period was unknown.
Future studies should employ surveillance monitoring and statistical tools to further investigate the usefulness of monitoring counts or clusters of negative test results. The application of cumulative sum-based (CUSUM) methods and other cluster detection techniques, such as the scan statistic, to the count or proportion of tests results should be considered
[8, 24]. The inclusion of such techniques in a disease surveillance system could present the diagnostic laboratory with a unique opportunity to play a central role in communicating disease trends to practitioners. Increased and timely communication of test results to veterinarians and other interested stakeholders might raise awareness of a disease outbreak, stimulate further discussion and dialogue, and pool knowledge and resources regarding potential disease concerns or outbreaks occurring in the field.