Macroepidemiological trends of Influenza A virus reverse transcription real-time polymerase chain reaction (RT-rtPCR)detection in porcine samples in the United States over 20 years

Daniel C. A. Moraes ¹ Guilherme Arruda Cezar ¹ Edison Magalhaes ¹ Rafael R Nicolino ¹ Kinath Rupasinghe ¹ Srijita Chandra ¹ Gustavo S Silva ¹ Marcelo Nunes Almeida ¹ Bret Crim ¹ Eric R Burrough ¹ Phillip C. Gauger ¹ Darin Madson ¹ Joseph Thomas ¹ Michael A. Zeller ¹ Rodger Main ¹ Mary Thurn ² Paulo Lages ² Cesar A Corzo ² Matthew Sturos ² Hemant Naikare ² Rob McGaughey ³ Franco Matias Ferreyra ³ Jamie Retallick ³ Jordan Gebhardt ³ Sara McReynolds ⁴ Jon Greseth ⁵ Darren Kersey ⁵ Travis Clement ⁵ Angela Pillatzki ⁵ Jane Christopher-Hennings ⁵ Beth S. Thompson ⁶ Melanie Prarat ⁷ Dennis Summers ⁷ Craig Bowen ⁸ Joseph Boyle ⁸ Kenitra Hendrix ⁸ James Lyons ⁸ Kelli Werling ⁹ Andreia G. Arruda ¹⁰ Mark Schwartz ^11,2 Paul Yeske ¹² Deborah Murray ¹³ Brigitte Mason ¹⁴ Peter Schneider ¹⁵ Samuel Copeland ¹⁶ Luc Dufresne ¹⁷ Daniel Boykin ¹⁸ Corrine Fruge ¹⁹ William Hollis ²⁰ Rebecca C Robbins ²¹ Thomas Petznick ²² Kurt Kuecker ²³ Lauren Glowzenski ²⁴ Megan Niederwerder ²⁵ Daniel C L Linhares ¹ Giovani Trevisan ^1*

• ¹ Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
• ² Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
• ³ Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, United States
• ⁴ Kansas Department of Agriculture, Division of Animal Health, Manhattan, KS, United States
• ⁵ Veterinary & Biomedical Sciences Department, South Dakota State University, Brookings, SD, United States
• ⁶ South Dakota Animal Industry Board, Pierre, SD, United States
• ⁷ Ohio Animal Disease and Diagnostic Laboratory, Reynoldsburg, OH, United States
• ⁸ College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
• ⁹ Indiana State Board of Animal Health, Indianapolis, IN, United States
• ¹⁰ Department of Veterinary Preventive Medicine, College of Veterinary Medicine, The Ohio State University, Columbus, OH, United States
• ¹¹ Schwartz Farms Inc., Sleepy Eye, MN, United States
• ¹² Swine Vet Center, St. Peter, Minnesota, United States
• ¹³ New Fashion Pork, Jackson, MN, United States
• ¹⁴ Country View Family Farms, Middletown, PA, United States
• ¹⁵ Innovative Agriculture Solutions, LLC, Waterloo, IA, United States
• ¹⁶ Prestage Farms, Clinton, NC, United States
• ¹⁷ Swine Veterinary Partners, Quebec, Canada
• ¹⁸ Smithfield Foods, Smithfield, VA, United States
• ¹⁹ The Maschhoffs LLC, Carlyle, IL, United States
• ²⁰ Carthage Veterinary Service LTD, Carthage, IL, United States
• ²¹ Pig Improvement Company, Hendersonville, TN, United States
• ²² ArkCare, Omaha, NE, United States
• ²³ The Hanor Company, Enid, OK, United States
• ²⁴ Pipestone Veterinary Services, Pipestone, MN, United States
• ²⁵ Swine Health Information Center, Ames, IA, United States

Influenza A virus (IAV) in swine is a significant respiratory pathogen globally. This study aimed to characterize the macroepidemiological aspects of IAV reverse transcription real-time polymerase chain reaction (RT-rtPCR) and IAV subtypes detection by RT-rtPCR assays in samples submitted from January 2004 until December 2024 to veterinary diagnostic laboratories (VDLs) participating in the Swine Disease Reporting System (SDRS). A secondary aim was to implement an IAVmonitoring capability to inform stakeholders of weekly changes in IAV detection patterns. Of the 372,659 samples submitted, 31% tested positive for IAV RNA via RT-rtPCR. The most frequent sample types were oral fluids (44.1%) and lung tissue (38.7%). Submissions from wean-to-market samples had higher positivity (34.4%) than submissions from the adult/sow farm age category (26.9%). IAV detection followed a seasonal pattern of detection by RT-rtPCR with peaks during spring and fall seasons, with lower positivity in summer. From a total of 118,490 samples tested for IAV subtyping RT-rtPCR, the most common IAV subtypes detected were H1N1 (33.1%), H3N2 (25.5%), H1N2 (24.3%), H3N1 (0.2%), mixed detection (5.4%), and partial subtype detection (11.5%). Mixed IAV subtypes were detected in individual samples, such as lung samples, nasal swabs, and bronchoalveolar lavage, indicating infection of individual animals with two or more IAV viruses. For IAV forecasting, a combination model between a dynamic regression and a neural network model exhibited superior performance in 2023, achieving the lowest root mean square error (RMSE) and improving the overall skill score compared to the individual models. This study highlights the importance of using laboratory submission data for IAV surveillance and assessing macroepidemiological aspects. The findings provide important insights into IAV dynamics and support the need for VDLs' standardized monitoring systems to enhance IAV understating in swine populations in the United States.