Abstract: Influenza A viruses (IAVs) are prime examples of emerging viruses in humans and animals. IAV circulation in domestic animals poses a pandemic risk as it provides new opportunities for zoonotic infections. The recent emergence of H5N1 IAV in cows and subsequent spread over multiple states within the USA, together with reports of spillover infections in humans, cats and mice highlight this issue. The horse is a domestic animal in which an avian-origin IAV lineage has been circulating for >60 years. In 2018/19, a Florida Clade 1 (FC1) virus triggered one of the largest epizootics recorded in the UK, which led to the replacement of the Equine Influenza Virus (EIV) Florida Clade 2 (FC2) lineage that had been circulating in the country since 2003. We integrated geographical, epidemiological, and virus genetic data to determine the virological and ecological factors leading to this epizootic. By combining newly-sequenced EIV complete genomes derived from UK outbreaks with existing genomic and epidemiological information, we reconstructed the nationwide viral spread and analysed the global evolution of EIV. We show that there was a single EIV FC1 introduction from the USA into Europe, and multiple independent virus introductions from Europe to the UK. At the UK level, three English regions (East, West Midlands, and North-West) were the main sources of virus during the epizootic, and the number of affected premises together with the number of horses in the local area were found as key predictors of viral spread within the country. At the global level, phylogeographic analysis evidenced a source-sink model for intercontinental EIV migration, with a source population evolving in the USA and directly or indirectly seeding viral lineages into sink populations in other continents. Our results provide insight on the underlying factors that influence IAV spread in domestic animals.
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.
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.
Multiple introductions of equine influenza virus into the United Kingdom led to widespread outbreaks and eventual replacement of the dominant virus lineage. The study analyzed genetic and epidemiological data to understand how different virus strains spread within the UK and globally.
Background and Significance
Influenza A viruses (IAVs) can infect both humans and various animal species and are known for their ability to emerge and adapt.
Domestic animals, including horses, can serve as reservoirs for IAVs, with potential zoonotic transmission risks to humans and other species.
The horse harbors a lineage of IAV of avian origin that has circulated for over 60 years, making it a valuable model for studying virus evolution and transmission.
In 2018-2019, a Florida Clade 1 (FC1) equine influenza virus caused one of the largest outbreaks in the UK, replacing the previously circulating Florida Clade 2 (FC2) since 2003.
Research Objectives
To understand the virological and ecological factors that contributed to the large 2018/19 equine influenza outbreak in the UK.
To reconstruct the spread of the virus across the UK using genomic sequencing combined with epidemiological data.
To analyze the global evolutionary patterns and migration of equine influenza viruses.
Methods
Collection and whole genome sequencing of equine influenza virus samples from UK outbreaks during the epizootic.
Integration of these new genomic data with existing sequences and epidemiological metadata to map viral spread.
Phylogeographic analysis to examine the origin and international movement patterns of equine influenza viruses.
Key Findings
The 2018/2019 outbreak was primarily due to a single introduction of the FC1 virus lineage from the USA into Europe.
Subsequently, multiple independent introductions of the virus occurred from Europe into the UK, rather than a single entry point.
Within the UK, three regions—East, West Midlands, and North-West England—acted as primary sources that contributed to the spread of the virus nationally.
The likelihood of viral spread in a local area was strongly correlated with two factors: the number of infected premises and the local horse population density.
On the global scale, a source-sink model was observed, where the USA acts as a source population for equine influenza viruses, seeding viral lineages to “sink” populations on other continents through direct or indirect transmission routes.
Implications
The study highlights how multiple virus introductions and regional animal densities drive large-scale epizootics.
Understanding viral spread patterns can help in developing improved surveillance, biosecurity, and control strategies in domestic animal populations.
Insights into intercontinental virus migration emphasize the importance of monitoring virus evolution in source populations, particularly in the USA, to predict and mitigate future outbreaks.
It also underscores the zoonotic potential inherent in IAVs circulating in domestic animals and the risk they pose to other species including humans.
Cite This Article
APA
Mojsiejczuk L, Whitlock F, Chen H, Magill C, Aranday-Cortes E, Bone J, Tong L, Da Silva Filipe A, Bryant N, Newton JR, Chambers TM, Reedy SE, Nemoto M, Yamanaka T, Hughes J, Murcia PR.
(2025).
Multiple introductions of equine influenza virus into the United Kingdom resulted in widespread outbreaks and lineage replacement.
PLoS Pathog, 21(6), e1013227.
https://doi.org/10.1371/journal.ppat.1013227
Lemey P, Rambaut A, Bedford T, Faria N, Bielejec F, Baele G. Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2. PLoS Pathog 2014;10(2):e1003932.
Lemey P, Hong SL, Hill V, Baele G, Poletto C, Colizza V. Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2. Nat Commun 2020;11(1):5110.
Lu L, Zhang F, Oude Munnink BB, Munger E, Sikkema RS, Pappa S. West Nile virus spread in Europe: Phylogeographic pattern analysis and key drivers. PLoS Pathog 2024;20(1):e1011880.
Wohl S, Metsky HC, Schaffner SF, Piantadosi A, Burns M, Lewnard JA. Combining genomics and epidemiology to track mumps virus transmission in the United States. PLoS Biol 2020;18(2):e3000611.
Müller NF, Wüthrich D, Goldman N, Sailer N, Saalfrank C, Brunner M. Characterising the epidemic spread of influenza A/H3N2 within a city through phylogenetics. PLoS Pathog 2020;16(11):e1008984.
Baguelin M, Flasche S, Camacho A, Demiris N, Miller E, Edmunds WJ. Assessing optimal target populations for influenza vaccination programmes: an evidence synthesis and modelling study. PLoS Med 2013;10(10):e1001527.
Rambaut A, Pybus OG, Nelson MI, Viboud C, Taubenberger JK, Holmes EC. The genomic and epidemiological dynamics of human influenza A virus. Nature 2008;453(7195):615–9.
Lemey P, Rambaut A, Bedford T, Faria N, Bielejec F, Baele G. Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2. PLoS Pathog 2014;10(2):e1003932.
Nelson MI, Lemey P, Tan Y, Vincent A, Lam TT-Y, Detmer S. Spatial dynamics of human-origin H1 influenza A virus in North American swine. PLoS Pathog 2011;7(6):e1002077.
Dalziel BD, Huang K, Geoghegan JL, Arinaminpathy N, Dubovi EJ, Grenfell BT. Contact heterogeneity, rather than transmission efficiency, limits the emergence and spread of canine influenza virus.. PLoS Pathog 2014;10(10):e1004455.
Park AW, Daly JM, Lewis NS, Smith DJ, Wood JLN, Grenfell BT. Quantifying the impact of immune escape on transmission dynamics of influenza.. Science 2009;326(5953):726–8.
Nelson MI, Viboud C, Simonsen L, Bennett RT, Griesemer SB, St George K. Multiple reassortment events in the evolutionary history of H1N1 influenza A virus since 1918.. PLoS Pathog 2008;4(2):e1000012.
Nemoto M, Reedy SE, Yano T, Suzuki K, Fukuda S, Garvey M. Antigenic comparison of H3N8 equine influenza viruses belonging to Florida sublineage clade 1 between vaccine strains and North American strains isolated in 2021-2022.. Arch Virol 2023;168(3):94.
Voorhees IEH, Dalziel BD, Glaser A, Dubovi EJ, Murcia PR, Newbury S. Multiple Incursions and Recurrent Epidemic Fade-Out of H3N2 Canine Influenza A Virus in the United States.. J Virol 2018;92(16):e00323-18.
Paull SH, Song S, McClure KM, Sackett LC, Kilpatrick AM, Johnson PTJ. From superspreaders to disease hotspots: linking transmission across hosts and space.. Front Ecol Environ 2012;10(2):75–82.
Puspitarani GA, Kao RR, Colman E. A metapopulation model for preventing the reintroduction of Bovine viral diarrhea virus to naïve herds: Scotland case study.. Front Vet Sci 2022;9:846156.
Di Nardo A, Ferretti L, Wadsworth J, Mioulet V, Gelman B, Karniely S. Evolutionary and ecological drivers shape the emergence and extinction of foot-and-mouth disease virus lineages.. Mol Biol Evol 2021;38(10):4346–61.
Zhou B, Donnelly ME, Scholes DT, St George K, Hatta M, Kawaoka Y. Single-reaction genomic amplification accelerates sequencing and vaccine production for classical and Swine origin human influenza a viruses.. J Virol 2009;83(19):10309–13.
Grubaugh ND, Gangavarapu K, Quick J, Matteson NL, De Jesus JG, Main BJ. An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar.. Genome Biol 2019;20(1):8.
Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates.. Nat Methods 2017;14(6):587–9.
Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era.. Mol Biol Evol 2020;37(5):1530–4.
Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W, Gascuel O. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.. Syst Biol 2010;59(3):307–21.
Rambaut A, Lam TT, Max Carvalho L, Pybus OG. Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen). Virus Evol 2016;2(1):vew007.
Martin DP, Varsani A, Roumagnac P, Botha G, Maslamoney S, Schwab T. RDP5: a computer program for analyzing recombination in, and removing signals of recombination from, nucleotide sequence datasets. Virus Evol 2020;7(1):veaa087.
Yu G, Smith DK, Zhu H, Guan Y, Lam TT. ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol 2016;8(1):28–36.
Lu L, Lycett SJ, Leigh Brown AJ. Determining the phylogenetic and phylogeographic origin of highly pathogenic avian influenza (H7N3) in Mexico. PLoS One 2014;9(9):e107330.