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Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020
Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data from the index farm to investigate within‐flock transmission dynamics. A stochastic epidemic model was fitted to the daily mortality data and model parameters were estima...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291964/ https://www.ncbi.nlm.nih.gov/pubmed/34170081 http://dx.doi.org/10.1111/tbed.14202 |
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author | Vergne, Timothée Gubbins, Simon Guinat, Claire Bauzile, Billy Delpont, Mattias Chakraborty, Debapriyo Gruson, Hugo Roche, Benjamin Andraud, Mathieu Paul, Mathilde Guérin, Jean‐Luc |
author_facet | Vergne, Timothée Gubbins, Simon Guinat, Claire Bauzile, Billy Delpont, Mattias Chakraborty, Debapriyo Gruson, Hugo Roche, Benjamin Andraud, Mathieu Paul, Mathilde Guérin, Jean‐Luc |
author_sort | Vergne, Timothée |
collection | PubMed |
description | Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data from the index farm to investigate within‐flock transmission dynamics. A stochastic epidemic model was fitted to the daily mortality data and model parameters were estimated using an approximate Bayesian computation sequential Monte Carlo (ABC‐SMC) algorithm. The model predicted that the first bird in the flock was infected 5 days (95% credible interval, CI: 3–6) prior to the day of suspicion and that the transmission rate was 4.1 new infections per day (95% CI: 2.8–5.8). On average, ducks became infectious 4.1 h (95% CI: 0.7–9.1) after infection and remained infectious for 4.3 days (95% CI: 2.8–5.7). The model also predicted that 34% (50% prediction interval: 8%–76%) of birds would already be infectious by the day of suspicion, emphasizing the substantial latent threat this virus could pose to other poultry farms and to neighbouring wild birds. This study illustrates how mechanistic models can help provide rapid relevant insights that contribute to the management of infectious disease outbreaks of farmed animals. These methods can be applied to future outbreaks and the resulting parameter estimates made available to veterinary services within a few hours. |
format | Online Article Text |
id | pubmed-9291964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92919642022-07-20 Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 Vergne, Timothée Gubbins, Simon Guinat, Claire Bauzile, Billy Delpont, Mattias Chakraborty, Debapriyo Gruson, Hugo Roche, Benjamin Andraud, Mathieu Paul, Mathilde Guérin, Jean‐Luc Transbound Emerg Dis Regular Issue Articles Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data from the index farm to investigate within‐flock transmission dynamics. A stochastic epidemic model was fitted to the daily mortality data and model parameters were estimated using an approximate Bayesian computation sequential Monte Carlo (ABC‐SMC) algorithm. The model predicted that the first bird in the flock was infected 5 days (95% credible interval, CI: 3–6) prior to the day of suspicion and that the transmission rate was 4.1 new infections per day (95% CI: 2.8–5.8). On average, ducks became infectious 4.1 h (95% CI: 0.7–9.1) after infection and remained infectious for 4.3 days (95% CI: 2.8–5.7). The model also predicted that 34% (50% prediction interval: 8%–76%) of birds would already be infectious by the day of suspicion, emphasizing the substantial latent threat this virus could pose to other poultry farms and to neighbouring wild birds. This study illustrates how mechanistic models can help provide rapid relevant insights that contribute to the management of infectious disease outbreaks of farmed animals. These methods can be applied to future outbreaks and the resulting parameter estimates made available to veterinary services within a few hours. John Wiley and Sons Inc. 2021-07-27 2021-11 /pmc/articles/PMC9291964/ /pubmed/34170081 http://dx.doi.org/10.1111/tbed.14202 Text en © 2021 The Authors. Transboundary and Emerging Diseases published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Regular Issue Articles Vergne, Timothée Gubbins, Simon Guinat, Claire Bauzile, Billy Delpont, Mattias Chakraborty, Debapriyo Gruson, Hugo Roche, Benjamin Andraud, Mathieu Paul, Mathilde Guérin, Jean‐Luc Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 |
title | Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 |
title_full | Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 |
title_fullStr | Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 |
title_full_unstemmed | Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 |
title_short | Inferring within‐flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020 |
title_sort | inferring within‐flock transmission dynamics of highly pathogenic avian influenza h5n8 virus in france, 2020 |
topic | Regular Issue Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291964/ https://www.ncbi.nlm.nih.gov/pubmed/34170081 http://dx.doi.org/10.1111/tbed.14202 |
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