FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Transbound Emerg Dis / Investigation of cross-regional spread and evolution of equi...
Transboundary and emerging diseases2022; 69(5); e1734-e1748; doi: 10.1111/tbed.14509

Investigation of cross-regional spread and evolution of equine influenza H3N8 at US and global scales using Bayesian phylogeography based on balanced subsampling.

Abstract: Equine influenza virus (EIV) is a highly contagious pathogen of equids, and a well-known burden in global equine health. EIV H3N8 variants seasonally emerged and resulted in EIV outbreaks in the United States and worldwide. The present study evaluated the pattern of cross-regional EIV H3N8 spread and evolutionary characteristics at US and global scales using Bayesian phylogeography with balanced subsampling based on regional horse population size. A total of 297 haemagglutinin (HA) sequences of global EIV H3N8 were collected from 1963 to 2019 and subsampled to global subset (n = 67), raw US sequences (n = 100) and US subset (n = 44) datasets. Discrete trait phylogeography analysis was used to estimate the transmission history of EIV using four global and US genome datasets. The North American lineage was the major source of globally dominant EIV variants and spread to other global regions. The US EIV strains generally spread from the southern and midwestern regions to other regions. The EIV H3N8 accumulated approximately three nucleotide substitutions per year in the HA gene under heterogeneous local positive selection. Our findings will guide better decision making of target intervention strategies of EIV H3N8 infection and provide the better scheme of genomic surveillance in the United States and global equine health.
© 2022 Wiley-VCH GmbH.
Get Full Text
Publication Date: 2022-03-16 PubMed ID: 35263501DOI: 10.1111/tbed.14509Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research article investigates the pattern of spread and evolution of equine influenza virus H3N8 on global and US scales using Bayesian phylogeography based on balanced subsampling.

Study Background and Purpose

  • The article revolves around the analysis of Equine Influenza Virus (EIV), a highly contagious pathogen that affects horses and other equids.
  • The pathogen often leads to outbreaks in the United States and globally, with variations of the H3N8 strain particularly noted.
  • The purpose of the study was to understand the pattern of distribution and evolution of this strain on a regional, national (US), and global scale.
  • This knowledge is hoped to inform better decision making for intervention strategies and improve genomic surveillance in global equine health.

Methods Used in the Study

  • The researchers used Bayesian phylogeography, a method that uses mathematical models and statistical inference to trace the geographic spread and genetic variation of diseases over time.
  • The study required balanced subsampling based on regional horse population size, which refers to selecting sample sizes from various regions proportionate to the size of the local equine population.
  • The study collected and subsampled 297 hemagglutinin (HA) sequences of global EIV H3N8 from 1963 to 2019.
  • The collected sequences were divided into a global subset, raw US sequences, and a subset of US sequences.
  • A method known as discrete trait phylogeography analysis was used to estimate the transmission history of EIV using these datasets. This method can trace back the paths of evolution and spread of a certain disease.

Findings of the Study

  • The study discovered that the North American lineage was the main source of globally dominant EIV variants and was responsible for the spread to other global regions.
  • EIV strains in the US generally spread from southern and midwestern regions to other areas.
  • The EIV H3N8 strain accumulated approximately three nucleotide substitutions per year in the HA gene, suggesting a state of ongoing evolution under the influence of local positive selection.
  • These findings are important for shaping interventions to control EIV H3N8 infection and for improving genomic surveillance strategies for both the United States and the global equine health sectors.

Cite This Article

APA
Lee K, Pusterla N, Barnum SM, Lee DH, Martínez-López B. (2022). Investigation of cross-regional spread and evolution of equine influenza H3N8 at US and global scales using Bayesian phylogeography based on balanced subsampling. Transbound Emerg Dis, 69(5), e1734-e1748. https://doi.org/10.1111/tbed.14509

Publication

Transboundary and emerging diseases
ISSN: 1865-1682
NlmUniqueID: 101319538
Country: Germany
Language: English
Volume: 69
Issue: 5
Pages: e1734-e1748

Researcher Affiliations

Lee, Kyuyoung
  • Department of Medicine & Epidemiology, Center for Animal Disease Modeling and Surveillance (CADMS), School of Veterinary Medicine, University of California, Davis, California.
Pusterla, Nicola
  • Department of Medicine & Epidemiology, School Veterinary Medicine, University of California, Davis, California.
Barnum, Samantha M
  • Department of Medicine & Epidemiology, School Veterinary Medicine, University of California, Davis, California.
Lee, Dong-Hun
  • College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea.
Martínez-López, Beatriz
  • Department of Medicine & Epidemiology, Center for Animal Disease Modeling and Surveillance (CADMS), School of Veterinary Medicine, University of California, Davis, California.

MeSH Terms

  • Animals
  • Bayes Theorem
  • Hemagglutinins
  • Horse Diseases / epidemiology
  • Horses
  • Humans
  • Influenza A Virus, H3N8 Subtype / genetics
  • Influenza, Human
  • Nucleotides
  • Orthomyxoviridae Infections / epidemiology
  • Orthomyxoviridae Infections / veterinary
  • Phylogeography

Grant Funding

  • Graduate Student Support Program (GSSP) in the School of Veterinary Medicine at UC Davis
  • Graduate group in epidemiology Fellowship at UC Davis
  • Center for Equine Health (CEH) grant award 17-18 at UC Davis
  • #1838207 / US National Science Foundation (NSF)
  • NRF-2018M3A9H4056535 / Bio and Medical Technology Development Program of the National Research Foundation, funded by the Government of South Korea

References

This article includes 79 references
  1. Abdel-Moneim AS, Abdel-Ghany AE, Shany SA. Isolation and characterization of highly pathogenic avian influenza virus subtype H5N1 from donkeys. Journal of Biomedical Science 2010, 17, 25.
  2. Baele G, Lemey P, Bedford T, Rambaut A, Suchard MA, Alekseyenko AV. Improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty. Molecular Biology and Evolution 2012, 29, 2157-2167.
    doi: 10.1093/molbev/mss084google scholar: lookup
  3. Benavides JA, Cross PC, Luikart G, Creel S. Limitations to estimating bacterial cross-species transmission using genetic and genomic markers: Inferences from simulation modeling. Evolutionary Applications 2014, 7, 774-787.
    doi: 10.1111/eva.12173google scholar: lookup
  4. Bielejec F, Rambaut A, Suchard MA, Lemey P. SPREAD: Spatial phylogenetic reconstruction of evolutionary dynamics. Bioinformatics 2011, 27, 2910-2912.
  5. Boots M, Hudson PJ, Sasaki A. Large shifts in pathogen virulence relate to host population structure. Science 2004, 303, 842-844.
  6. Bryant NA, Rash AS, Russell CA, Ross J, Cooke A, Bowman S, MacRae S, Lewis NS, Paillot R, Zanoni R. Antigenic and genetic variations in European and North American equine influenza virus strains (H3N8) isolated from 2006 to 2007. Veterinary Microbiology 2009, 138, 41-52.
  7. Bush RM, Smith CB, Cox NJ, Fitch WM. Effects of passage history and sampling bias on phylogenetic reconstruction of human influenza A evolution. Proceedings of the National Academy of Sciences 2000, 97, 6974-6980.
  8. Charlesworth B. Effective population size and patterns of molecular evolution and variation. Nature Reviews Genetics 2009, 10, 195-205.
  9. Chatham House. Resourcetrade.earth. Chatham House [Online] 2018.
  10. Colizza V, Barrat A, Barthélemy M, Vespignani A. The role of the airline transportation network in the prediction and predictability of global epidemics. Proceedings of the National Academy of Sciences 2006, 103, 2015-2020.
  11. Compans RW, Oldstone MB. Influenza pathogenesis and control, Volume I. Springer 2014.
  12. Cowled B, Ward MP, Hamilton S, Garner G. The equine influenza epidemic in Australia: Spatial and temporal descriptive analyses of a large propagating epidemic. Preventive Veterinary Medicine 2009, 92, 60-70.
  13. Cullinane A, Newton JR. Equine influenza-A global perspective. Veterinary Microbiology 2013, 167, 205-214.
  14. Daly JM, Lai ACK, Binns MM, Chambers TM, Barrandeguy M, Mumford JA. Antigenic and genetic evolution of equine H3N8 influenza A viruses. Journal of General Virology 1996, 77, 661-671.
    doi: 10.1099/0022-1317-77-4-661google scholar: lookup
  15. Diallo AA, Souley MM, Issa Ibrahim A, Alassane A, Issa R, Gagara H, Yaou B, Issiakou A, Diop M, Ba Diouf RO. Transboundary spread of equine influenza viruses (H3N8) in West and Central Africa: Molecular characterization of identified viruses during outbreaks in Niger and Senegal, in 2019. Transboundary and Emerging Diseases 2021, 68, 1253-1262.
  16. Drummond AJ, Rambaut A, Shapiro B, Pybus OG. Bayesian coalescent inference of past population dynamics from molecular sequences. Molecular Biology and Evolution 2005, 22, 1185-1192.
    doi: 10.1093/molbev/msi103google scholar: lookup
  17. Duffy S, Shackelton LA, Holmes EC. Rates of evolutionary change in viruses: Patterns and determinants. Nature Reviews Genetics 2008, 9, 267.
  18. Edgar RC. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research 2004, 32, 1792-1797.
  19. FAOSTAT R. FAOSTAT database. Food and Agriculture Organization of the United Nations 2017.
  20. Fisher RA. The genetical theory of natural selection. Oxford Clarendon Press 1930.
    doi: 10.5962/bhl.title.27468google scholar: lookup
  21. Gardy JL, Loman NJ. Towards a genomics-informed, real-time, global pathogen surveillance system. Nature Reviews Genetics 2018, 19, 9.
  22. Grenfell BT, Pybus OG, Gog JR, Wood JL, Daly JM, Mumford JA, Holmes EC. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 2004, 303, 327-332.
  23. Grubaugh ND, Ladner JT, Kraemer MU, Dudas G, Tan AL, Gangavarapu K, Wiley MR, White S, Thézé J, Magnani DM. Genomic epidemiology reveals multiple introductions of Zika virus into the United States. Nature 2017, 546, 401.
  24. Guo Y, Wang M, Kawaoka Y, Gorman O, Ito T, Saito T, Webster RG. Characterization of a new avian-like influenza A virus from horses in China. Virology 1992, 188, 245-255.
  25. Hasegawa M, Kishino H, Yano T. Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. Journal of Molecular Evolution 1985, 22, 160-174.
  26. Huelsenbeck JP, Jain S, Frost SW, Pond SLK. A Dirichlet process model for detecting positive selection in protein-coding DNA sequences. Proceedings of the National Academy of Sciences 2006, 103, 6263-6268.
  27. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nature Methods 2017, 14, 587-589.
    doi: 10.1038/nmeth.4285google scholar: lookup
  28. Karamendin K, Kydyrmanov A, Kasymbekov Y, Khan E, Daulbayeva K, Asanova S, Zhumatov K, Seidalina A, Sayatov M, Fereidouni SR. Continuing evolution of equine influenza virus in Central Asia, 2007-2012. Archives of Virology 2014, 159, 2321-2327.
  29. Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: A novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Research 2002, 30, 3059-3066.
  30. Kosakovsky Pond SL, Frost SDW. Not so different after all: A comparison of methods for detecting amino acid sites under selection. Molecular Biology and Evolution 2005, 22, 1208-1222.
    doi: 10.1093/molbev/msi105google scholar: lookup
  31. Kumar S, Stecher G, Tamura K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology and Evolution 2016, 33, 1870-1874.
  32. Lee K, Pusterla N, Barnum SM, Lee D, Martínez-López B. Genome-informed characterization of antigenic drift in the hemagglutinin gene of equine influenza strains circulating in the United States from 2012 to 2017. Transboundary and Emerging Diseases 2022, 69(4), e52-e63.
    doi: 10.1111/tbed.14262google scholar: lookup
  33. Leitner T, Escanilla D, Franzen C, Uhlen M, Albert J. Accurate reconstruction of a known HIV-1 transmission history by phylogenetic tree analysis. Proceedings of the National Academy of Sciences 1996, 93(20), 10864-10869.
    doi: 10.1073/pnas.93.20.10864google scholar: lookup
  34. Lemey P, Rambaut A, Bedford T, Faria N, Bielejec F, Baele G, Russell CA, Smith DJ, Pybus OG, Brockmann D, Suchard MA. Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2. PLoS Pathogens 2014, 10, e1003932.
    doi: 10.1371/journal.ppat.1003932google scholar: lookup
  35. Lemey P, Rambaut A, Drummond AJ, Suchard MA. Bayesian Phylogeography Finds Its Roots. PLoS Computational Biology 2009, 5, e1000520.
    doi: 10.1371/journal.pcbi.1000520google scholar: lookup
  36. Livesay GJ, O'neill T, Hannant D, Yadav MP, Mumford JA. The outbreak of equine influenza (H3N8) in the United Kingdom in 1989: Diagnostic use of an antigen capture ELISA. The Veterinary Record 1993, 133, 515-519.
  37. Magee D, Scotch M. The effects of random taxa sampling schemes in Bayesian virus phylogeography. Infection, Genetics and Evolution 2018, 64, 225-230.
    doi: 10.1016/j.meegid.2018.07.003google scholar: lookup
  38. Mavian C, Pond SK, Marini S, Magalis BR, Vandamme A-M, Dellicour S, Scarpino SV, Houldcroft C, Villabona-Arenas J, Paisie TK. Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable. Proceedings of the National Academy of Sciences 2020, 117, 12522-12523.
  39. Miño S, Mojsiejczuk L, Guo W, Zhang H, Qi T, Du C, Zhang X, Wang J, Campos R, Wang X. Equine influenza virus in Asia: Phylogeographic pattern and molecular features reveal circulation of an autochthonous lineage. Journal of Virology 2019, 93, e00116-19.
  40. Murcia PR, Baillie GJ, Daly J, Elton D, Jervis C, Mumford JA, Newton R, Parrish CR, Hoelzer K, Dougan G. Intra-and interhost evolutionary dynamics of equine influenza virus. Journal of Virology 2010, 84(14), 6943-6954.
    doi: 10.1128/jvi.00112-10google scholar: lookup
  41. Murcia PR, Wood JL, Holmes EC. Genome-scale evolution and phylodynamics of equine H3N8 influenza A virus. Journal of Virology 2011, 85, 5312-5322.
  42. Murrell B, Moola S, Mabona A, Weighill T, Sheward D, Kosakovsky Pond SL, Scheffler K. FUBAR: A Fast, Unconstrained Bayesian AppRoximation for inferring selection. Molecular Biology and Evolution 2013, 30, 1196-1205.
    doi: 10.1093/molbev/mst030google scholar: lookup
  43. Murrell B, Wertheim JO, Moola S, Weighill T, Scheffler K, Pond SLK. Detecting individual sites subject to episodic diversifying selection. PLoS Genetics 2012, 8, e1002764.
    doi: 10.1371/journal.pgen.1002764google scholar: lookup
  44. Nemoto M, Yamayoshi S, Bannai H, Tsujimura K, Kokado H, Kawaoka Y, Yamanaka T. A single amino acid change in hemagglutinin reduces the cross-reactivity of antiserum against an equine influenza vaccine strain. Archives of Virology 2019, 164, 2355-2358.
    doi: 10.1007/s00705-019-04328-4google scholar: lookup
  45. Newton JR, Verheyen K, Wood JLN, Yates PJ, Mumford JA. Equine influenza in the United Kingdom in 1998. Veterinary Record 1999, 145, 449-452.
  46. OIE. Expert surveillance panel on equine influenza vaccine composition. Office International des Epizooties Bulletin 2019.
    doi: 10.20506/bull.2019.2.3013google scholar: lookup
  47. OIE. Expert surveillance panel on equine influenza vaccine composition. Office International des Epizooties Bulletin 2020.
    doi: 10.20506/bull.2020.1.3134google scholar: lookup
  48. Paillot R, Rash N, Garrett D, Prowse-Davis L, Montesso F, Cullinane A, Lemaitre L, Thibault J-C, Wittreck S, Dancer A. How to meet the last OIE expert surveillance panel recommendations on equine influenza (EI) vaccine composition: A review of the process required for the recombinant canarypox-based EI vaccine. Pathogens 2016, 5, 64.
  49. Pusterla N, Estell K, Mapes S, Wademan C. Detection of clade 2 equine influenza virus in an adult horse recently imported to the USA. Equine Veterinary Education 2014, 26, 453-455.
  50. Pusterla N, Kass PH, Mapes S, Johnson C, Barnett DC, Vaala W, Gutierrez C, McDaniel R, Whitehead B, Manning J. Surveillance programme for important equine infectious respiratory pathogens in the USA. Veterinary Record 2011, 169, 12.
  51. Pusterla N, Kass PH, Mapes S, Wademan C, Akana N, Barnett C, MacKenzie C, Vaala W. Voluntary surveillance program for equine influenza virus in the United States from 2010 to 2013. Journal of Veterinary Internal Medicine 2015, 29, 417-422.
  52. Pybus OG, Rambaut A. Evolutionary analysis of the dynamics of viral infectious disease. Nature Reviews Genetics 2009, 10, 540.
  53. Qi T, Guo W, Huang W-Q, Li H-M, Zhao L-P, Dai L-L, He N, Hao X-F, Xiang W-H. Genetic evolution of equine influenza viruses isolated in China. Archives of Virology 2010, 155, 1425-1432.
  54. Rambaut A, Drummond A. TreeAnnotator v1.10.5. Available as part of the BEAST package at http://beast.bio.ed.ac.uk 2019.
  55. Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Systematic Biology 2018, 67, 901-904.
  56. Rambaut A, Lam TT, Max Carvalho L, Pybus OG. Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen). Virus Evolution 2016, 2.
    doi: 10.1093/ve/vew007google scholar: lookup
  57. Rosanowski SM, Carpenter TE, Adamson D, Rogers CW, Pearce P, Burns M, Cogger N. An economic analysis of a contingency model utilising vaccination for the control of equine influenza in a non-endemic country. PLoS One 2019, 14, e0210885.
  58. Scholtens RG, Steele JH, Dowdle WR, Yarbrough WB, Robinson RQ. US epizootic of equine influenza, 1963. Public Health Reports (Washington, DC: 1896) 1964, 79, 393-402.
  59. Shittu I, Meseko CA, Sulaiman LP, Inuwa B, Mustapha M, Zakariya PS, Muhammad AA, Muhammad U, Atuman YJ, Barde IJ. Fatal multiple outbreaks of equine influenza H3N8 in Nigeria, 2019: The first introduction of Florida clade 1 to West Africa. Veterinary Microbiology 2020, 248, 108820.
  60. Shu Y, McCauley J. GISAID: Global initiative on sharing all influenza data-from vision to reality. Eurosurveillance 2017, 22, 30494.
  61. Singh RK, Dhama K, Karthik K, Khandia R, Munjal A, Khurana SK, Chakraborty S, Malik YS, Virmani N, Singh R, Tripathi BN, Munir M, van der Kolk JH. A Comprehensive review on equine influenza virus: Etiology, epidemiology, pathobiology, advances in developing diagnostics, vaccines, and control strategies. Frontiers in Microbiology 2018, 9, 1941.
    doi: 10.3389/fmicb.2018.01941google scholar: lookup
  62. Smyth GB, Dagley K, Tainsh J. Insights into the economic consequences of the 2007 equine influenza outbreak in Australia. Australian Veterinary Journal 2011, 89, 151-158.
  63. Sovinova O, Tumova B, Pouska F, Nemec J. Isolation of a virus causing respiratory disease in horses. Acta virologica 1958, 2, 52.
  64. Squires RB, Noronha J, Hunt V, García-Sastre A, Macken C, Baumgarth N, Suarez D, Pickett BE, Zhang Y, Larsen CN. Influenza research database: An integrated bioinformatics resource for influenza research and surveillance. Influenza and Other Respiratory Viruses 2012, 6, 404-416.
  65. Sreenivasan C, Jandhyala S, Luo S, Hause B, Thomas M, Knudsen D, Leslie-Steen P, Clement T, Reedy S, Chambers T. Phylogenetic analysis and characterization of a sporadic isolate of equine influenza A H3N8 from an unvaccinated horse in 2015. Viruses 2018, 10, 31.
  66. Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evolution 2018, 4.
    doi: 10.1093/ve/vey016google scholar: lookup
  67. Tazi L, Pérez-Losada M, Gu W, Yang Y, Xue L, Crandall KA, Viscidi RP. Population dynamics of Neisseria gonorrhoeae in Shanghai, China: A comparative study. BMC Infectious Diseases 2010, 10, 13.
  68. Tong Y-G, Shi W-F, Liu D, Qian J, Liang L, Bo X-C, Liu J, Ren H-G, Fan H, Ni M. Genetic diversity and evolutionary dynamics of Ebola virus in Sierra Leone. Nature 2015, 524(7563), 93-96.
    doi: 10.1038/nature14490google scholar: lookup
  69. USDA. Equine 2015, Part II: Changes in the US Equine industry, 1998-2015. USDA 2016.
  70. Villabona-Arenas CJ, Hanage WP, Tully DC. Phylogenetic interpretation during outbreaks requires caution. Nature Microbiology 2020, 5, 876-877.
  71. Virmani N, Bera B, Singh B, Shanmugasundaram K, Gulati B, Barua S, Vaid R, Gupta A, Singh R. Equine influenza outbreak in India (2008-09): Virus isolation, sero-epidemiology and phylogenetic analysis of HA gene. Veterinary Microbiology 2010, 143(2-4), 224-237.
    doi: 10.1016/j.vetmic.2009.12.007google scholar: lookup
  72. Weaver S, Shank SD, Spielman SJ, Li M, Muse SV, Kosakovsky Pond SL. Datamonkey 2.0: A modern web application for characterizing selective and other evolutionary processes. Molecular Biology and Evolution 2018, 35, 773-777.
    doi: 10.1093/molbev/msx335google scholar: lookup
  73. Webster RG. Are equine 1 influenza viruses still present in horses?. Equine Veterinary Journal 1993, 25, 537-538.
  74. Woodward AL, Rash AS, Blinman D, Bowman S, Chambers TM, Daly JM, Damiani A, Joseph S, Lewis N, McCauley JW, Medcalf L, Mumford J, Newton JR, Tiwari A, Bryant NA, Elton DM. Development of a surveillance scheme for equine influenza in the UK and characterisation of viruses isolated in Europe, Dubai and the USA from 2010-2012. Veterinary Microbiology 2014, 169, 113-127.
    doi: 10.1016/j.vetmic.2013.11.039google scholar: lookup
  75. Woodward A, Rash AS, Medcalf E, Bryant NA, Elton DM. Using epidemics to map H3 equine influenza virus determinants of antigenicity. Virology 2015, 481, 187-198.
  76. Xie W, Lewis PO, Fan Y, Kuo L, Chen M-H. Improving marginal likelihood estimation for Bayesian phylogenetic model selection. Systematic Biology 2010, 60(2), 150-160.
    doi: 10.1093/sysbio/syq085google scholar: lookup
  77. Yamanaka T, Niwa H, Tsujimura K, Kondo T, Matsumura T. Epidemic of equine influenza among vaccinated racehorses in Japan in 2007. Journal of Veterinary Medical Science 2008, 70, 623-625.
  78. Yongfeng Y, Xiaobo S, Nan X, Jingwen Z, Wenqiang L. Detection of the epidemic of the H3N8 subtype of the equine influenza virus in large-scale donkey farms. International Journal of Veterinary Science and Medicine 2020, 8, 26-30.
  79. Youk S, Lee D-H, Ferreira HL, Afonso CL, Absalon AE, Swayne DE, Suarez DL, Pantin-Jackwood MJ. Rapid evolution of Mexican H7N3 highly pathogenic avian influenza viruses in poultry. PLoS One 2019, 14, e0222457.
    doi: 10.1371/journal.pone.0222457google scholar: lookup

Citations

This article has been cited 3 times.
  1. Branda F, Yon DK, Albanese M, Binetti E, Giovanetti M, Ciccozzi A, Ciccozzi M, Scarpa F, Ceccarelli G. Equine Influenza: Epidemiology, Pathogenesis, and Strategies for Prevention and Control. Viruses 2025 Feb 21;17(3).
    doi: 10.3390/v17030302pubmed: 40143233google scholar: lookup
  2. Wasik BR, Rothschild E, Voorhees IEH, Reedy SE, Murcia PR, Pusterla N, Chambers TM, Goodman LB, Holmes EC, Kile JC, Parrish CR. Understanding the divergent evolution and epidemiology of H3N8 influenza viruses in dogs and horses. Virus Evol 2023;9(2):vead052.
    doi: 10.1093/ve/vead052pubmed: 37692894google scholar: lookup
  3. Gonzalez-Obando J, Forero JE, Zuluaga-Cabrera AM, Ruiz-Saenz J. Equine Influenza Virus: An Old Known Enemy in the Americas. Vaccines (Basel) 2022 Oct 14;10(10).
    doi: 10.3390/vaccines10101718pubmed: 36298583google scholar: lookup
Subscribe to our newsletter
Join 99,357 horse owners like you who receive our email updates on horse health and nutrition.