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Abstract
A risk assessment framework was developed to evaluate the zoonotic potential of avian influenza (AI), focusing on virus mutations linked to phenotypic traits related to mammalian adaptation identified in the literature. Virus sequences were screened for the presence of these mutations and their geographical, temporal and subtype-specific trends. Spillover events to mammals (including humans) and human seroprevalence studies were also reviewed. Thirty-four mutations associated with five phenotypic traits (increased receptor specificity, haemagglutinin stability, neuraminidase specificity, enhanced polymerase activity and evasion of innate immunity) were shortlisted. AI viruses (AIVs) carrying multiple adaptive mutations and traits belonged to both low and highly pathogenic subtypes, mainly to A(H9N2), A(H7N9), A(H5N6) and A(H3N8), were sporadic and primarily detected in Asia. In the EU/EEA, H5Nx viruses of clade 2.3.4.4b, which have increased opportunities for evolution due to widespread circulation in birds and occasional cases/outbreaks in mammals, have acquired the highest number of zoonotic traits. Adaptive traits, such as enhanced polymerase activity and immune evasion, were frequently acquired, while receptor-specific mutations remained rare. Globally, human cases remain rare, with the majority overall due to A(H5N1), A(H5N6), A(H7N9) and A(H9N2) that are among the subtypes that tend to have a higher number of adaptive traits. The main drivers of mammalian adaptation include virus and host characteristics, and external factors increasing AIV exposure of mammals and humans to wild and domestic birds (e.g. human activities and ecological factors). Comprehensive surveillance of AIVs targeting adaptive mutations with whole genome sequencing in animals and humans is essential for early detection of zoonotic AIVs and efficient implementation of control measures. All preparedness, preventive and control measures must be implemented under a One Health framework and tailored to the setting and the epidemiological situation; in particular, enhanced monitoring, biosecurity, genomic surveillance and global collaboration are critical for mitigating the zoonotic risks of AIV.
Keywords
avian influenza, birds, highly pathogenic avian influenza (HPAI), mammals, mutations, preparedness, public health, A(H5N1) VIRUS OUTBREAK, A H5N1 INFECTION, DOMESTIC CATS, A(H7N9) VIRUS, SEROLOGICAL EVIDENCE, HUMANS LESSONS, POULTRY, SURVEILLANCE, ANTIBODIES, HEMAGGLUTININ

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MLA
Alvarez, Julio, et al. “Preparedness, Prevention and Control Related to Zoonotic Avian Influenza.” EFSA JOURNAL, vol. 23, no. 1, 2025, doi:10.2903/j.efsa.2025.9191.
APA
Alvarez, J., Boklund, A., Dippel, S., Dorea, F., Figuerola, J., Herskin, M. S., … Melidou, A. (2025). Preparedness, prevention and control related to zoonotic avian influenza. EFSA JOURNAL, 23(1). https://doi.org/10.2903/j.efsa.2025.9191
Chicago author-date
Alvarez, Julio, Anette Boklund, Sabine Dippel, Fernanda Dorea, Jordi Figuerola, Mette S. Herskin, Virginie Michel, et al. 2025. “Preparedness, Prevention and Control Related to Zoonotic Avian Influenza.” EFSA JOURNAL 23 (1). https://doi.org/10.2903/j.efsa.2025.9191.
Chicago author-date (all authors)
Alvarez, Julio, Anette Boklund, Sabine Dippel, Fernanda Dorea, Jordi Figuerola, Mette S. Herskin, Virginie Michel, Miguel angel Miranda Chueca, Eleonora Nannoni, Soren Saxmose Nielsen, Romolo Nonno, Anja B. Riber, Jan Arend Stegeman, Karl Stahl, Hans-Hermann Thulke, Frank Tuyttens, Christoph Winckler, Claire Brugerolles, Thorsten Wolff, Anna Parys, Erika Lindh, Neus Latorre-Margalef, Marie-Anne Rameix Welti, Ralf Duerrwald, Ramona Trebbien, Sylvie van der Werf, Magnus Gisslen, Isabella Monne, Alice Fusaro, Claire Guinat, Alessio Bortolami, Leonidas Alexakis, Theresa Enkirch, Olov Svartstrom, Katriina Willgert, Francesca Baldinelli, Ludovica Preite, Malin Grant, Alessandro Broglia, and Angeliki Melidou. 2025. “Preparedness, Prevention and Control Related to Zoonotic Avian Influenza.” EFSA JOURNAL 23 (1). doi:10.2903/j.efsa.2025.9191.
Vancouver
1.
Alvarez J, Boklund A, Dippel S, Dorea F, Figuerola J, Herskin MS, et al. Preparedness, prevention and control related to zoonotic avian influenza. EFSA JOURNAL. 2025;23(1).
IEEE
[1]
J. Alvarez et al., “Preparedness, prevention and control related to zoonotic avian influenza,” EFSA JOURNAL, vol. 23, no. 1, 2025.
@article{01JKT3VBNX7BY2534C6AC2FB28,
  abstract     = {{A risk assessment framework was developed to evaluate the zoonotic potential of avian influenza (AI), focusing on virus mutations linked to phenotypic traits related to mammalian adaptation identified in the literature. Virus sequences were screened for the presence of these mutations and their geographical, temporal and subtype-specific trends. Spillover events to mammals (including humans) and human seroprevalence studies were also reviewed. Thirty-four mutations associated with five phenotypic traits (increased receptor specificity, haemagglutinin stability, neuraminidase specificity, enhanced polymerase activity and evasion of innate immunity) were shortlisted. AI viruses (AIVs) carrying multiple adaptive mutations and traits belonged to both low and highly pathogenic subtypes, mainly to A(H9N2), A(H7N9), A(H5N6) and A(H3N8), were sporadic and primarily detected in Asia. In the EU/EEA, H5Nx viruses of clade 2.3.4.4b, which have increased opportunities for evolution due to widespread circulation in birds and occasional cases/outbreaks in mammals, have acquired the highest number of zoonotic traits. Adaptive traits, such as enhanced polymerase activity and immune evasion, were frequently acquired, while receptor-specific mutations remained rare. Globally, human cases remain rare, with the majority overall due to A(H5N1), A(H5N6), A(H7N9) and A(H9N2) that are among the subtypes that tend to have a higher number of adaptive traits. The main drivers of mammalian adaptation include virus and host characteristics, and external factors increasing AIV exposure of mammals and humans to wild and domestic birds (e.g. human activities and ecological factors). Comprehensive surveillance of AIVs targeting adaptive mutations with whole genome sequencing in animals and humans is essential for early detection of zoonotic AIVs and efficient implementation of control measures. All preparedness, preventive and control measures must be implemented under a One Health framework and tailored to the setting and the epidemiological situation; in particular, enhanced monitoring, biosecurity, genomic surveillance and global collaboration are critical for mitigating the zoonotic risks of AIV.}},
  articleno    = {{e9191}},
  author       = {{Alvarez, Julio and Boklund, Anette and Dippel, Sabine and Dorea, Fernanda and Figuerola, Jordi and Herskin, Mette S. and Michel, Virginie and Chueca, Miguel angel Miranda and Nannoni, Eleonora and Nielsen, Soren Saxmose and Nonno, Romolo and Riber, Anja B. and Stegeman, Jan Arend and Stahl, Karl and Thulke, Hans-Hermann and Tuyttens, Frank and Winckler, Christoph and Brugerolles, Claire and Wolff, Thorsten and Parys, Anna and Lindh, Erika and Latorre-Margalef, Neus and Welti, Marie-Anne Rameix and Duerrwald, Ralf and Trebbien, Ramona and van der Werf, Sylvie and Gisslen, Magnus and Monne, Isabella and Fusaro, Alice and Guinat, Claire and Bortolami, Alessio and Alexakis, Leonidas and Enkirch, Theresa and Svartstrom, Olov and Willgert, Katriina and Baldinelli, Francesca and Preite, Ludovica and Grant, Malin and Broglia, Alessandro and Melidou, Angeliki}},
  issn         = {{1831-4732}},
  journal      = {{EFSA JOURNAL}},
  keywords     = {{avian influenza,birds,highly pathogenic avian influenza (HPAI),mammals,mutations,preparedness,public health,A(H5N1) VIRUS OUTBREAK,A H5N1 INFECTION,DOMESTIC CATS,A(H7N9) VIRUS,SEROLOGICAL EVIDENCE,HUMANS LESSONS,POULTRY,SURVEILLANCE,ANTIBODIES,HEMAGGLUTININ}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{109}},
  title        = {{Preparedness, prevention and control related to zoonotic avian influenza}},
  url          = {{http://doi.org/10.2903/j.efsa.2025.9191}},
  volume       = {{23}},
  year         = {{2025}},
}

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