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High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats
Avian influenza (AI) is an important disease that has significant implications for animal and human health. High pathogenicity AI (HPAI) has emerged in consecutive seasons within the UK to cause the largest outbreaks recorded. Statutory measures to control outbreaks of AI virus (AIV) at poultry farm...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990394/ https://www.ncbi.nlm.nih.gov/pubmed/36502812 http://dx.doi.org/10.1017/S0950268822001856 |
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author | Wade, Daniel Ashton-Butt, Adham Scott, Graham Reid, Scott M. Coward, Vivien Hansen, Rowena D. E. Banyard, Ashley C. Ward, Alastair I. |
author_facet | Wade, Daniel Ashton-Butt, Adham Scott, Graham Reid, Scott M. Coward, Vivien Hansen, Rowena D. E. Banyard, Ashley C. Ward, Alastair I. |
author_sort | Wade, Daniel |
collection | PubMed |
description | Avian influenza (AI) is an important disease that has significant implications for animal and human health. High pathogenicity AI (HPAI) has emerged in consecutive seasons within the UK to cause the largest outbreaks recorded. Statutory measures to control outbreaks of AI virus (AIV) at poultry farms involve disposal of all birds on infected premises. Understanding of the timing of incursions into the UK could facilitate decisions on improved responses. During the autumnal migration and wintering period (autumn 2019– spring 2020), three active sampling approaches were trialled for wild bird species considered likely to be involved in captive AI outbreaks with retrospective laboratory testing undertaken to define the presence of AIV. Faecal sampling of birds (n = 594) caught during routine and responsive mist net sampling failed to detect AIV. Cloacal sampling of hunter-harvested waterfowl (n = 146) detected seven positive samples from three species with the earliest detection on the 17 October 2020. Statutory sampling first detected AIV in wild and captive birds on 3 November 2020. We conclude that hunter sourced sampling of waterfowl presents an opportunity to detect AI within the UK in advance of outbreaks on poultry farms and allow for early intervention measures to protect the national poultry flock. |
format | Online Article Text |
id | pubmed-9990394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99903942023-03-08 High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats Wade, Daniel Ashton-Butt, Adham Scott, Graham Reid, Scott M. Coward, Vivien Hansen, Rowena D. E. Banyard, Ashley C. Ward, Alastair I. Epidemiol Infect Original Paper Avian influenza (AI) is an important disease that has significant implications for animal and human health. High pathogenicity AI (HPAI) has emerged in consecutive seasons within the UK to cause the largest outbreaks recorded. Statutory measures to control outbreaks of AI virus (AIV) at poultry farms involve disposal of all birds on infected premises. Understanding of the timing of incursions into the UK could facilitate decisions on improved responses. During the autumnal migration and wintering period (autumn 2019– spring 2020), three active sampling approaches were trialled for wild bird species considered likely to be involved in captive AI outbreaks with retrospective laboratory testing undertaken to define the presence of AIV. Faecal sampling of birds (n = 594) caught during routine and responsive mist net sampling failed to detect AIV. Cloacal sampling of hunter-harvested waterfowl (n = 146) detected seven positive samples from three species with the earliest detection on the 17 October 2020. Statutory sampling first detected AIV in wild and captive birds on 3 November 2020. We conclude that hunter sourced sampling of waterfowl presents an opportunity to detect AI within the UK in advance of outbreaks on poultry farms and allow for early intervention measures to protect the national poultry flock. Cambridge University Press 2022-12-11 /pmc/articles/PMC9990394/ /pubmed/36502812 http://dx.doi.org/10.1017/S0950268822001856 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Original Paper Wade, Daniel Ashton-Butt, Adham Scott, Graham Reid, Scott M. Coward, Vivien Hansen, Rowena D. E. Banyard, Ashley C. Ward, Alastair I. High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
title | High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
title_full | High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
title_fullStr | High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
title_full_unstemmed | High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
title_short | High pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
title_sort | high pathogenicity avian influenza: targeted active surveillance of wild birds to enable early detection of emerging disease threats |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990394/ https://www.ncbi.nlm.nih.gov/pubmed/36502812 http://dx.doi.org/10.1017/S0950268822001856 |
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