Progress 05/01/24 to 04/30/25

Outputs
Target Audience:Sharing the findings of this study enables swine veterinarians to utilize and benchmark information on endemic swine pathogens and rapidly respond to possible animal threats occurring in the field. The developed and implementedBLAST platform, updated and published online, supports the audience in making the epidemiological link by comparing their PRRSV ORF5 sequence with what has been detected in the six veterinary diagnostic laboratories participating in the project. Additionalinclusion of the PRRSV ORF5 variant classificationprovides more granular epidemiological PRRSV information. This information will support decision-making and enhance understanding of detection trends for swine pathogens. Additionally, our findings and ongoing monthly PDF reports on pathogen detection and PRRSV ORF5 sequence will provide valuable information to other researchers for follow-up studies or the possibility of utilizing the publicly available information in the published material and online platforms within their research programs. In addition, the dashboard for data geographical representativeness supports producers, veterinarians, and veterinarian authorities in understanding the rate of PCR testing for each pathogenby U.S. states. Finally,two manuscripts were published during this year and targeted the scientific community with applied similar methodology of aggregated diagnostic data to generate ongoing information for the livestock industry. Metrics: The online page of the PRRSV BLAST tool had thevisit of 536 distinct IPs throughout this reporting year, showing the importance of the tool's usageamong veterinarians, producers, researchers, and stakeholders from the swine industry. Also, the PDF, audio, and video report numbers continued to increase, reaching a global audience. The PDF report has 533 receivers from 17 countries. 89.2% of these receivers are from the United States. The report had over 3,000 downloads on the audio format, and the video platform shared on YouTube (https://www.youtube.com/@swinediseasereportingsyste2986) and LinkedIn (https://www.linkedin.com/in/field-epidemiology-46814a194/) had over 50,000 views. On the analytics of LinkedIn, which shares information regarding the top 3 positions that watched your video report, veterinarians and the pharmaceutical industry were the two main listeners, followed by University faculty and researchers. Therefore, these numbers support the evidence that a broader audience has seen the report in different formats, demonstrating the impact of the project for the swine industry. Changes/Problems:Develop and implement a monitoring co-agent detection at the overall and state levels. The proposal considered "A multivariate spatial-temporal model to effectively aggregate different data sources (agents) will be implemented to describe and monitor the pattern of co-agent detection across states", which is still under development. The different patterns among diseases and states increase the complexity of the model, which had to undergo several comparisons to find the ideal model (BFastmonitor). BFastmonitor with trend and harmonic seasonal model showed the lowest detection delay and missed change-point rate. However, the co-detection adjustments must be made considering that different pathogens have different detection patterns and vary among states. Therefore, a causal model is being design based on the online change-point analysis, which can calculate the definition of outbreak for each state and disease (how much the deviation of the positivity has to occur to consider an outbreak). Then, it will measure the impact of these outbreaks in an increased number of co-detections. PRRSV and Influenza are still the primary co-detections we are analyzing as a pilot, but the model will be adjusted for each pathogen. We believe that by December 2025, the co-detection algorithm will be ready and running for the project, similarly to the representativeness dashboard created to evaluate ongoing changes in the co-detection scenario. In summary, the new adjustment to the model will include incorporating network models to flag co-detection spread between states. Also, it can explore the correlation between viruses using the online change-point detection models. Another adjustment and changes were made to the teaching component. The PI Trevisan teaches a graduate course, "VDPAM-560 Ecology of Infectious Diseases," at Iowa State University every other year. Since the course was tough in 2025, there was an adjustment to already include four-hour class sections covering subjects on monitoring, surveillance, usage of individual and population-based samples, utility, and limitations of using aggregated diagnostic data for monitoring and surveillance, and an overview of resources currently available nationally and internationally to gather disease activity information. What opportunities for training and professional development has the project provided?Graduate Students: 6 graduate students are currently under training from different Iowa State University departments, reinforcing the multidisciplinary content of the funded grant. Srijita Chandra (PhD Computer Sciences), Alan Moore (PhD Statistics), Meghana Korada (MS, Electrical and Computer Science Engineering), Elisa De Conti (Ms), Quyen Thuc (Ms) and Guilherme Cezar (PhD) (Veterinary Diagnostic and Production Medicine) are working directly on the research and communication component of the project. One graduate student, Jai Tatineni (MBA, MS, Business Analytics) is concluding his MS in May 2025. Veterinary Students: Five veterinary students continue to participate in the advisory board of the project, interacting with veterinarians, producers, and state veterinarians. The students have been participating in the discussions through the emails shared with the advisory board. They became exposed to the veterinarians and producers' decision-making process based on the shared diagnostic data. Cassidy Cordon (University of Minnesota), Colby Dodson (Kansas State University), Elizabeth Ohl (Ohio State University), Kendall Sattler (Purdue University), and Kristen Cleaver (Iowa State University) continued to be trained in the second year of the project. Producers and veterinarians: A national webinar organized in conjunction with Iowa Pork Industry Center Regional Conferences took place in November of 2024 and present to producers the tools available in the Swine Disease Reporting System, including the new dashboard and platforms developed under the USDA-NIFA grant. The webinar presentation associated with a personalized email explaining all the features included in the report brought 36 producers/veterinarians to the receiver list of the monthly reports, which impacts their access to benchmark information regarding swine pathogens detection. By the way, the number of receivers increased by 55.4 % since the USDA supported this grant; the number of receivers jumped from 341 to 533 in the last reporting year. Most new receivers are veterinarians, pharmaceutical company employees, researchers, and producers. International Faculty Training: The project could train two international faculty members from Brazilian institutions. Dr. Rafael Nicolino (Universidade Federal de Minas Gerais) and Dr. Janice Zanella (Embrapa suínos e aves). Both faculty members had the opportunity to be exposed to the project, understand the principles of aggregating diagnostic data, and inform the industry about disease activity. How have the results been disseminated to communities of interest?The results from year two of the grant were shared at several conferences. Four oral presentations at swine-related conferences were given at the American Association of Swine Veterinarians Annual Meeting (1), Iowa Veterinary Medical Association (1), American Society of Animal Scientist meeting (1), North American PRRSV Symposium (1), and American Association of Veterinary Laboratory Diagnosticians Annual Meeting (1). Two publications in a digital magazine targeting swine producers and veterinarians (National Hog Farmer magazine). In addition, two journal publications, one at Frontiers in Veterinary Science and another in PLOS ONE (Description in products section).The project's received invitations to share an oral presentation at the Work Pork Expo. The IPIC has shared SDRS information at the Iowa regional Iowa Pork Industry seminars during February 2025, and created a webinar series to share SDRS information for producers, contributing with SDRS communication and distribution. SDRS was presented at the Kansas State University Veterinary Seminar in November 2024 and at the Iowa State University Swine Seminar in Spetember 2024. What do you plan to do during the next reporting period to accomplish the goals?Ongoing monitoring of the PRRSV ORF5 sequence with the Ct value associated. The database has been created by this report delivery, with the individual ORF5 sequence with a Ct value associated from its screening PCR. For the following report, we will implement a dashboard to see possible drops in the Ct values from individual PRRSV variants and associate them with their movement or emergence. The movement will be tracked at a state level, monitoring if the sequence was detected elsewhere than its normal detected area. The variant emergence will be associated with an abnormal increase in lineage counts that did not have a variant assigned. An Early Aberration Reporting System (EARS) model will monitor the abnormal count number. Also, the BFastmonitor model will be implemented for PCR detections for co-detections and state spreadness. The new change-point algorithm has been implemented at an individual pathogen, but it will be adapted for the co-detection cases in next year's report. Then the principal investigators can intuitively report this information to the industry in the monthly PDF reports and other media channels (podcasts and videos). Finally, the a new manuscripts is expected to be written in the next year covering thevalidation of the Bfastmonitor and its comparison with other change-point direction algorithms.

Impacts
What was accomplished under these goals? Early detection of emerging animal health threats through the usage of genetic sequences. The new Blast tool algorithm was updated and now includes a new ORF5 lineage classification for PRRSV-1. Therefore, now the Blast can compare PRRSV-2 and PRRSV-1, increasing the possibilities for veterinarians who use the tool. Also, a new column was added to display inBlast results PRRSV-2 ORF5 basedvariant classification. The new variant classification developed by VanderWaal et al. 2024 helps better understand the epidemiological link among the sequences, and it is easier to understand scenarios like an undergoing PRRSV-2 clonal expansion reported in the SDRS report #76 of June 4, 2024. SDRS-developed algorithms can support theidentification ofnew sequences entering in the databasebased on level of nucleotide similarity. In addition to the PRRSV BLAST tool, a new PRRSV ORF5 page was designed and included in the SDRS monthly reports, SDRS report #78of August 6, 2024. The page is composed offour charts that aid the industry in understanding the trends about new variants detected and their distribution among U.S. states. Therefore, the ongoing monitoring algorithm developed in year 1 is now implemented and able to detect and inform the industry rapidly, either in the monthly reports or through email chains. Finally, a manuscript was published in the Frontiers in Veterinary Science journal as described in the product section, closing this research aim (https://doi.org/10.3389/fvets.2025.1571020) Moreover, adatabase update and remanufacturing was done, and a pilot dashboard has been created that associated the information of Ct values from the sequences detected by qPCR and the abnormal number of sequences detected based on the Early Aberration Report System (EARS) model. The database is fully integrated with the Ct values, which required a different data collation to associate the PCR and sequence databases. Further, the EARS model C1 was applied for the count of every lineage detected in the U.S. using seven datapoints as a baseline to detect anomalies if the count is three standard deviations above the expected number. Assess a regional representativeness matrix of the data. The developed analytical model created in the previous year was updated, creating an interactive dashboard that displays data from USDA hog count reports merged with the total number of porcine cases tested at the six participant VDLs. Nowadays, the dashboard needs to be manual updated once a year toincludethe hog inventory and a set of SAS codes to update the ratio of PCR testing per pathogen and statistical model. Therefore, at a state level, the algorithms calculated the testing representativeness regarding the proportion of the number of PCR cases tested per 100,000 hog population. With an implementedautomatization, the model can be easily updated and reveal differences in testing over the years. For example, from 2022 to 2024, Ohio became the second state with a larger number of tests per 100,000 heads of pigs in their inventory achieving 468 PCR tests per 100,000 population, losing only to Oklahoma, which became the first state in a number of tests since 2020, achieving 716 PCR tests per 100,000 population. Also, it is important to highlight the decline of South Dakota, which was the number 1 state in testing per 100,000 pigs with 482 tests in 2014, and has now become the fourth one with 356 tests. In addition, differences were identified when breaking down the data by categories, such as the testing in sow farms in Iowa. Since 2020, the amount of Iowa testing per 100,000 sows has increased, achieving 2,005 tests performed (including all the pathogens). The majority of these cases are driven by PRRSV testing. On the other hand, in the wean-to-market improvements have to be made. According to our database, only 102 tests are performed on 100,000 growing pigs in Iowa. Therefore, with the new dashboard, this information can be accessed easily throughout the years, becoming a good platform for analyzing the testing strategies by state and identifying potential states underrepresented in the database, such as North Carolina, as was reported in the previous USDA reports. Finally, based on the state-level algorithms, insights related to data modeling based on change-point detection were analyzed to identify significant changes in the detection scenario per state. A manuscript has been written including the comparison of these different models performance and it will be submitted to the Journal of Preventive Veterinary Medicine. An MS graduated in May 2025 and wrote a dissertation on implementing and leveraging state-level monitoring. Develop and implement a monitoring co-agent detection at the overall and state levels. A new methodology had to be developed for this analysis. In order to understand the abnormal value of codetection, various online change-point detection methods were compared, including BFastmonitor, Strucchange, Weighted CUSUM, and BEAST. These methods were tested on simulated data generated using TBATS models fitted to historical data. The simulation involves inserting "outbreak patterns" using an SIR model to mimic real outbreaks. For this study, an outbreak was considered a high increase in the percentage of positive submissions validated with inputs from field veterinarians. Then,Monte Carlo simulations were conducted to compare change-point methods to estimate thresholds for each technique to achieve a given average run length (ARL). Detection delay and missed change-point rate are compared across methods using simulated outbreak data. BFastmonitor with trend and harmonic seasonal model showed the lowest detection delay and missed change-point rate across various settings. However, it is essential to highlight that this test was performed for PRRSV and PEDV separately. After the validation for a single pathogen, now the method will be tested for co-detections to identify early abnormalities in detection and check if one disease "outbreak" could induce more co-detection cases, e.g., does increased positivity of PRRSV in Minnesota led to more PRRSV + Influenza cases in Iowa?The new timeline and changes performed are described in the section "changes/problems". A manuscript has been written including the comparison of these different models' performance, and it will be submitted to the Journal of Preventive Veterinary Medicine, closing the loop on this research aim. Advisory board. The Advisory Board was established in the first year 1 of the report, including field practitioners, producers, and state veterinarians, and has remained very active during the year, with in-person and virtual meetings, and providing feedback on the current trends in the field's perceptions of different pathogen detections. A significant acquisition for the advisory board was the addition of Dr. Christopher Rademacher, associate director of the Iowa Pork Industry Center. Dr. Rademacher has been communicating the findings of this project in regional meetings in Iowa and the U.S., aiding the dissemination of information regarding the findings of the SDRS reports.

Publications

• Type: Peer Reviewed Journal Articles Status: Published Year Published: 2025 Citation: Chandra S, Cezar G, Rupasinghe K, Magalh�es E, Silva GS, Almeida M, Crim B, Burrough E, Gauger P, Madson D, Thomas J, Zeller M, Zhang J, Main R, Rovira A, Thurn M, Lages P, Corzo C, Sturos M, VanderWaal K, Naikare H, Matias-Ferreyra F, McGaughey R, Retallick J, McReynolds S, Gebhardt J, Pillatzki A, Greseth J, Kersey D, Clement T, Christopher-Hennings J, Thompson B, Perkins J, Prarat M, Summers D, Bowen C, Boyle J, Hendrix K, Lyons J, Werling K, Arruda AG, Schwartz M, Yeske P, Murray D, Mason B, Schneider P, Copeland S, Dufresne L, Boykin D, Fruge C, Hollis W, Robbins R, Petznick T, Kuecker K, Glowzenski L, Niederwerder M, Huang X, Linhares DCL and Trevisan G. Harnessing sequencing data for porcine reproductive and respiratory Syndrome virus (PRRSV): tracking genetic evolution dynamics and emerging sequences in US swine industry. 2025 Front. Vet. Sci. 12:1571020. doi: 10.3389/fvets.2025.1571020 https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2025.1571020/full
• Type: Peer Reviewed Journal Articles Status: Published Year Published: 2024 Citation: Cezar G, Magalh�es E, Rupasinghe K, Chandra S, Silva G, Almeida M, Crim B, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Fano E, Pi�eyro P, Main R, Thurn M, Lages P, Corzo C, Rovira A, Naikare N, McGaughey R, Matias-Ferreyra F, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A, Summers D, Bowen C, Boyle J, Hendrix K, Arruda AG, Linhares D, Trevisan G. Using diagnostic data from veterinary diagnostic laboratories to unravel macroepidemiological aspects of porcine circoviruses 2 and 3 in the United States from 20022023. 2024. PLOS ONE, 19(12), e0311807 (2024). https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0311807

Progress 05/01/23 to 04/30/24

Outputs
Target Audience:Swine producers/veterinarians: sharing the findings of this study enables swine veterinarians to utilize and benchmark information on endemic swine pathogens and rapidly respond to possible animal threats occurring in the field. A developed and implemented BLAST platform, published online, also supports the audience in making the epidemiological link, comparing their PRRSV ORF5 sequence with what has been detected in the six veterinary diagnostic laboratories present in the project. The information generated will support decision-making and enhance understanding of the detection trends for swine pathogens. Swine researchers: our findings and ongoing analysis regarding pathogens detection and PRRSV ORF5 sequence will provide information to other researchers for follow-up studies or the possibility of utilizing the publicly available information in the published material and online platforms (dashboards and BLAST) within their research programs. There is also the opportunity to stimulate other researchers to conduct similar studies under different field conditions. Changes/Problems:The proposal considered creating quarterly meetings with the advisory board to collect input about the disease activity and the development of the SDRS project. However, at the 2024 American Association of Swine Veterinarians (AASV) annual meeting, an in-person meeting with the advisory board discussed the idea with the veterinarians and producers. The advisory board requested a change in the proposal for an in-person yearly meeting (at AASV) and an online winter preparedness call to occur in October to discuss the possible upcoming animal threats in the winter when the activity of endemic swine pathogens is high. This call will be organized and will take advantage of a Zoom meeting with all the advisory members. Besides the two meetings, the advisory will continue to discuss the major findings of pathogen detection monthly through email. In addition, emergency meetings might occur if the activity of a specific pathogen is alarming, and a discussion with the advisory board can be requested. What opportunities for training and professional development has the project provided?Graduate Students: 5 graduate students are currently under training from different Iowa State University departments, reinforcing the multidisciplinary content of the funded grant. Srijita Chandra (MS Computer Sciences), Alan Moore (PhD Statistics), Jai Tatineni (MBA, MS, Business Analytics), Elisa De Conti (Ms), and Guilherme Cezar (PhD) (Veterinary Diagnostic and Production Medicine) are working directly on the research and communication component of the project. One graduate student, Guilherme Acezar (Veterinary Diagnostic and Production Medicine), concluded his MS at the end of 2023. Veterinary Students: Currently, five veterinary students participate in the advisory board of the project, interacting with veterinarians, producers, and state veterinarians, contributing to the student formation. Also, the students are exposed to the usage of diagnostic data for disease surveillance, being introduced through presentations and how the project works, and participating in an in-person meeting at the American Association of Swine Veterinarians in Nashville, Tennessee. Cassidy Cordon (University of Minnesota), Colby Dodson (Kansas State University), Elizabeth Ohl (Ohio State University), Kendall Sattler (Purdue University), and Kristen Cleaver (Iowa State University) were the students trained in this first year of the project. Producers and veterinarians: Four Iowa Pork Industry Center Regional Conferences took place in February of 2024 and present to producers the tools available in the Swine Disease Reporting System, including the new dashboard and platforms developed under the USDA-NIFA grant (new dashboards and PRRSV BLAST tool). The explanation at the conference brought 29 producers/veterinarians to the receiver list of the monthly reports, which impacts their access to benchmark information regarding swine pathogens detection and facilitates the accessibility of dashboards and other tools provided by the project. How have the results been disseminated to communities of interest?The results from year one of the grant were shared with several conferences. Eight oral presentations at swine-related conferences were given at the American Association of Swine Veterinarians Annual Meeting (2), Iowa Veterinary Medical Association (1), Iowa Pork Industry Center Regional Conferences (4), and American Association of Veterinary Laboratory Diagnosticians Annual Meeting (1). One publication in a digital magazine targeting swine producers and veterinarians (National Hog Farmer magazine). Also, the project's findings were presented in a webinar for the Canadian Association of Swine Veterinarians (CASV). The project directors organized a pre-conference entitled "Maximizing the Value of Big Diagnostic Data" in collaboration with the CO-PI, Dr. Daniel Linhares, at the 2024 American Association of Swine Veterinarians Annual Meeting held in Nashville, TN, during February 2024, and had 80 registered attendees. What do you plan to do during the next reporting period to accomplish the goals?Develop an automated monitoring algorithm using the USDA hog report data associated with the SDRS positive rate per pathogen to identify potential anomalies in the number of positive cases based on the swine population of the specific U.S. states. The algorithm is being tested based on the case representativeness matrix created in the first year of the report in time-series models. Ongoing monitoring of the PRRSV ORF5 sequence kept alive to identify daily the potential new PRRSV sequences detected in the U.S. The algorithm identifies new sequences using a threshold of nucleotide similarity implemented by the project. Then, we will generate rapid notifications, reporting to the industry about the new sequences detected and the states they were coming from. A time series algorithm with the weekly data of the PCR testing has been developed based on the representative matrix data. By the next reporting year, the algorithm should be implemented to detect anomalies regarding the number of positive PCR tests detected using the swine population by state as a variable. The new algorithm will detect if the pattern of positive results or testing numbers has increased over time. Then the principal investigators can intuitively report this information to the industry in the monthly PDF reports and other media channels (podcasts and videos)

Impacts
What was accomplished under these goals? Early detection of emerging animal health threats through the usage of genetic sequences. PRRSV ORF5 sequence analysis was developed and validated, and a BLAST tool was implemented in the first year. A class log algorithm was implemented to classify the sequences entered in the SDRS database based on the new lineages according to reference sequences provided by Wannarat et al. 2023. Also, the SDRS-developed algorithms can identify new sequences based on nucleotide similarity. A retrospective analysis using a <95% similarity threshold identified 133 new PRRSV sequences from 2010 to 2023. In contrast, most new variants were detected in samples identified as having been collected in Iowa, followed by Minnesota, Indiana, and Illinois. In addition, the PRRSV BLAST tool is a valuable resource for investigating PRRSV sequences affecting the U.S. swine herd. It offers producers and veterinarians an open platform to compare their own ORF5 sequences with the ones available in the SDRS database (the largest PRRSV-2 ORF5 sequence database in the U.S. from six VDLs). The platform assesses nucleotide similarities between different PRRSVs. This tool can be used to effectively identify active viruses in a region and track their spread to other areas. This epidemiological information equips decision-makers with valuable insights for disease prevention and control strategies, safeguarding pork production. An ongoing monitoring algorithm was created that detects new PRRSV sequences rapidly, notifying the project's principal investigators. Based on nucleotide identity, ORF5 sequence length, presence of ambiguities, and arbitrary thresholds, the algorithm detects daily new PRRSV sequences and sends an email with the ID identifiers of these new sequences, facilitating the scanning by the investigators of this project. Assess a regional representativeness matrix of the data. The developed analytical mode uses the USDA hog count reports from 2023, which provides information on the number of the U.S. swine inventory split by age categories (growing pigs and breeding herds). The inventory data was merged with the total number of porcine cases tested at the six participant VDLs. Then, the analysis was divided into two steps: First, access the overall representativeness of a pathogen, which contributed to understanding the pathogen's testing pattern. Then, at a state level, the algorithms calculated the testing representativeness regarding the proportion of the number of PCR cases tested per 100,000 hog population. As an example, from 2012 to 2023, PRRSV was the pathogen most tested in 10 of 11 states monitored in the SDRS project. Kansas was the only exception since 2019. The enteric coronaviruses (PEDV, TGEV, and PDCoV) were the leading pathogens tested in Kansas, with over 80 cases per 100,000 pigs being tested. On absolute numbers, Oklahoma was the state that tested more for PRRSV, with 270 cases per 100,000 pigs. North Carolina had fewer PCR cases per 100,000 pigs for 6 of 8 pathogens monitored by the project (PEDV, PDCoV, TGEV, PRRS, PCV2, and PCV3), varying from 2 to 20 cases per 100,000 pigs. The information was discussed with the SDRS advisory group at the American Association of Swine Veterinarians Annual Meeting in Nashville, TN. The SDRS advisory group made by field veterinarians and producers pointed out that most large swine production systems perform their PCR tests internally, mainly for PRRSV and enteric coronaviruses. Advisory members from these regions provide expert opinions on pathogen activity in these areas. The discussion leads to the idea and a suggestion to pursue future work, pending resources and production company willing to share data, of incorporating diagnostic data from the production systems in-house testing to improve the representativeness of states like NC and report more accurate information for this state. Develop and implement a monitoring co-agent detection at the overall and state level. A detection trend was identified using the Influenza A virus and PRRSV as models. The trend of overall positivity in PCR cases for both viruses was similar, which makes the principal investigators utilize these two pathogens as the first co-detection model for the analysis. A co-detection algorithm using time-series models is still under development at the overall and state levels. Using the count of weekly PCR cases to fit the model. Exponential smooth models, autoregressive integrated moving average model (ARIMA), and Bayesian linear regressions have been tested. For training the models for both the data representativeness and the co-agent detection, expert opinion is been used to identify anomalies in the data, such as outbreaks, changes in testing strategies (i.e., single or multiplex PCR), and outliers to train the models in capturing what would be a "true positive" change in co-detection pattern. Advisory board. The advisory board has been established with 15 members from the swine industry, including veterinarians and producers, who contribute to interpreting the findings. The data representativeness analysis contributed to enhancing the needs of the field experts. Two advisory members are from North Carolina Drs. Daniel Boykin and Samuel Copeland, who work for Smithfield Foods and Prestage Farms, give insights to the project regarding pathogen detection in this region. State veterinarians from IA, MN, SD, KS, IN, and OH were invited to the advisory board, and four members were incorporated: Drs. Dennis Summers (Ohio State Veterinarian), Beth Thompson (South Dakota Animal Industry Board State Veterinarian), Sara McReynolds (Kansas Department of Agriculture Assistant Veterinarian), and Kelli Werling (Indiana State Board of Animal Health Assistant Veterinarian).

Publications

• Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Cezar GA. Invited talk at Canadian Association of Swine Veterinarians (CASV-ACVP) Webinar, Fergus, Ontario. March 21st, 2024. Presentation: Current Porcine Circovirus 3 (PCV3) scenario: What have we learned about this virus?
• Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Cezar GA. Invited talk at IVMA Winter Conference, Altoona, Iowa. February 15th, 2024. Presentation: Swine Disease Reporting System: unraveling the activity of swine endemic pathogens in the U.S.
• Type: Other Status: Other Year Published: 2024 Citation: Chandra S, Cezar G, Rupasinghe K, Linhares DCL, Trevisan, G. New informative tool for swine veterinarians, producers and stakeholders. National Hog Farmer. Mar 13, 2024. Access at: https://www.nationalhogfarmer.com/livestock-management/new-informative-tool-for-swine-veterinarians-producers-and-stakeholders
• Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Chandra S, Cezar G, Rupasinghe K, Zeller M, Main R, Rovira A, Matias-Ferreyra F, Pillatzki A, Prarat M, Bowen C, Linhares DCL, Huai M, Trevisan, G. Have we seen this PRRSV before? Where? When? SDRS PRRSV BLAST: An informative tool to support swine veterinarians and producers. 2024 AASV annual meeting. February 24-27, 2024. Nashville, Tennessee.
• Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Trevisan G, Yeske P. Macro-epidemiological lessons from aggregated veterinary diagnostic laboratory datasets AASV Pre-Conference Seminars 2024 Leading AASV into the Future Maximizing the Value of Big Diagnostic Data, Nashville, February 24, 2024.
• Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Trevisan G. Swine Disease Reporting System  SDRS What is the SDRS? What information is generated from SDRS? Iowa Pork Congress Swine Health Pannel, Des Moines, January 25, 2024.
• Type: Other Status: Other Year Published: 2023 Citation: Trevisan G. Use of Diagnostic Data to Rapidly Detect and Raise Stakeholder Awareness of Emerging, Biological Animal Health and Production Threats Quarterly NAHLN Lab Director's meeting. USA. June 29, 2023 (delivered online).
• Type: Other Status: Other Year Published: 2023 Citation: Trevisan G. Diagnostic Laboratory Epi information: contributions to the US Swine industry NAHLN Laboratory Response Planning. USA. June 23, 2023 (delivered online)
• Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Yeske P, Cezar GA, Linhares DCL, Trevisan G. Macro-epidemiological lessons from aggregated veterinary diagnostic laboratory datasets. AASV Pre-Conference Seminars 2024 Leading AASV into the Future Maximizing the Value of Big Diagnostic Data. AASV Annual Meeting 2024; Feb 24, 2024; Pg. 3-4; Nashville, DOI: https://doi.org/10.54846/am2024/s2-1
• Type: Other Status: Published Year Published: 2024 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A, Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #74" (2024). April 02, 2024
• Type: Other Status: Published Year Published: 2024 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #73" (2024). March 05, 2024
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Cezar GA, Magalh�es E, Chandra S, Silva G, Almeida M, Crim B, Burrough ER, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Corzo C, Rovira A, McGaughey R, Retallick J, Mattias-Ferreyra F, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Hennings J, Prarat M, Johnson A, Summers D, Arruda AG, Pineyro P, Linhares DCL, Trevisan G. Using aggregated diagnostic data from veterinary diagnostic laboratories to monitor porcine circovirus type 2. 66th AAVLD Annual Meeting; Oct 12-18, 2023; Pg. 26; National Harbor, MD
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Cezar GA, Linhares DCL, Magalhaes, E, Main R, Rovira A, Matias-Ferreyra, Pillatzki A, Prarat M, Trevisan G. Monitoring swine pathogen detection using data from veterinary diagnostic laboratories. 2023 ISU James D. McKean Swine Disease Conference; Jun 27-28, 2023; Pg. 39-40; Ames
• Type: Other Status: Published Year Published: 2024 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #72" (2024). February 06, 2024.
• Type: Other Status: Published Year Published: 2024 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #71" (2024). January 02, 2024.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #70" (2023). December 05, 2023.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #69" (2023). November 07, 2023.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #68" (2023). October 03, 2023.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Bowen C, Hendrix K, Boyle J, Arruda A "Swine Disease Reporting System: Report #67" (2023). September 05, 2023.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Arruda A "Swine Disease Reporting System: Report #66" (2023). August 01, 2023.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Arruda A "Swine Disease Reporting System: Report #65" (2023). July 05, 2023.
• Type: Other Status: Published Year Published: 2023 Citation: Cezar GA, Trevisan G, Linhares DCL, Magalhaes E, Chandra S, Silva G, Almeida M, Crim B, Rupasinghe K, Burrough E, Gauger P, Siepker C, Mainenti M, Zeller M, Main R, Thurn M, Lages PTF, Corzo CA, Rovira A, McGaughey R, Matias-Ferreyra, Retallick J, Gebhardt J, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Prarat M, Johnson A; Summers D, Arruda A "Swine Disease Reporting System: Report #64" (2023). June 06, 2023.