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Inference and forecast of H7N9 influenza in China, 2013 to 2015
The recent emergence of A(H7N9) avian influenza poses a significant challenge to public health in China and around the world; however, understanding of the transmission dynamics and progression of influenza A(H7N9) infection in domestic poultry, as well as spillover transmission to humans, remains l...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Centre for Disease Prevention and Control (ECDC)
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322186/ https://www.ncbi.nlm.nih.gov/pubmed/28230525 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.7.30462 |
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author | Li, Ruiyun Bai, Yuqi Heaney, Alex Kandula, Sasikiran Cai, Jun Zhao, Xuyi Xu, Bing Shaman, Jeffrey |
author_facet | Li, Ruiyun Bai, Yuqi Heaney, Alex Kandula, Sasikiran Cai, Jun Zhao, Xuyi Xu, Bing Shaman, Jeffrey |
author_sort | Li, Ruiyun |
collection | PubMed |
description | The recent emergence of A(H7N9) avian influenza poses a significant challenge to public health in China and around the world; however, understanding of the transmission dynamics and progression of influenza A(H7N9) infection in domestic poultry, as well as spillover transmission to humans, remains limited. Here, we develop a mathematical model–Bayesian inference system which combines a simple epidemic model and data assimilation method, and use it in conjunction with data on observed human influenza A(H7N9) cases from 19 February 2013 to 19 September 2015 to estimate key epidemiological parameters and to forecast infection in both poultry and humans. Our findings indicate a high outbreak attack rate of 33% among poultry but a low rate of chicken-to-human spillover transmission. In addition, we generated accurate forecasts of the peak timing and magnitude of human influenza A(H7N9) cases. This work demonstrates that transmission dynamics within an avian reservoir can be estimated and that real-time forecast of spillover avian influenza in humans is possible. |
format | Online Article Text |
id | pubmed-5322186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | European Centre for Disease Prevention and Control (ECDC) |
record_format | MEDLINE/PubMed |
spelling | pubmed-53221862017-03-03 Inference and forecast of H7N9 influenza in China, 2013 to 2015 Li, Ruiyun Bai, Yuqi Heaney, Alex Kandula, Sasikiran Cai, Jun Zhao, Xuyi Xu, Bing Shaman, Jeffrey Euro Surveill Research Article The recent emergence of A(H7N9) avian influenza poses a significant challenge to public health in China and around the world; however, understanding of the transmission dynamics and progression of influenza A(H7N9) infection in domestic poultry, as well as spillover transmission to humans, remains limited. Here, we develop a mathematical model–Bayesian inference system which combines a simple epidemic model and data assimilation method, and use it in conjunction with data on observed human influenza A(H7N9) cases from 19 February 2013 to 19 September 2015 to estimate key epidemiological parameters and to forecast infection in both poultry and humans. Our findings indicate a high outbreak attack rate of 33% among poultry but a low rate of chicken-to-human spillover transmission. In addition, we generated accurate forecasts of the peak timing and magnitude of human influenza A(H7N9) cases. This work demonstrates that transmission dynamics within an avian reservoir can be estimated and that real-time forecast of spillover avian influenza in humans is possible. European Centre for Disease Prevention and Control (ECDC) 2017-02-16 /pmc/articles/PMC5322186/ /pubmed/28230525 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.7.30462 Text en This article is copyright of The Authors, 2017. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made. |
spellingShingle | Research Article Li, Ruiyun Bai, Yuqi Heaney, Alex Kandula, Sasikiran Cai, Jun Zhao, Xuyi Xu, Bing Shaman, Jeffrey Inference and forecast of H7N9 influenza in China, 2013 to 2015 |
title | Inference and forecast of H7N9 influenza in China, 2013 to 2015 |
title_full | Inference and forecast of H7N9 influenza in China, 2013 to 2015 |
title_fullStr | Inference and forecast of H7N9 influenza in China, 2013 to 2015 |
title_full_unstemmed | Inference and forecast of H7N9 influenza in China, 2013 to 2015 |
title_short | Inference and forecast of H7N9 influenza in China, 2013 to 2015 |
title_sort | inference and forecast of h7n9 influenza in china, 2013 to 2015 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322186/ https://www.ncbi.nlm.nih.gov/pubmed/28230525 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.7.30462 |
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