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Modelling and analysis of influenza A (H1N1) on networks
BACKGROUND: In April 2009, a new strain of H1N1 influenza virus, referred to as pandemic influenza A (H1N1) was first detected in humans in the United States, followed by an outbreak in the state of Veracruz, Mexico. Soon afterwards, this new virus kept spreading worldwide resulting in a global outb...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317584/ https://www.ncbi.nlm.nih.gov/pubmed/21356138 http://dx.doi.org/10.1186/1471-2458-11-S1-S9 |
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author | Jin, Zhen Zhang, Juping Song, Li-Peng Sun, Gui-Quan Kan, Jianli Zhu, Huaiping |
author_facet | Jin, Zhen Zhang, Juping Song, Li-Peng Sun, Gui-Quan Kan, Jianli Zhu, Huaiping |
author_sort | Jin, Zhen |
collection | PubMed |
description | BACKGROUND: In April 2009, a new strain of H1N1 influenza virus, referred to as pandemic influenza A (H1N1) was first detected in humans in the United States, followed by an outbreak in the state of Veracruz, Mexico. Soon afterwards, this new virus kept spreading worldwide resulting in a global outbreak. In China, the second Circular of the Ministry of Health pointed out that as of December 31, 2009, the country’s 31 provinces had reported 120,000 confirmed cases of H1N1. METHODS: We formulate an epidemic model of influenza A based on networks. We calculate the basic reproduction number and study the effects of various immunization schemes. The final size relation is derived for the network epidemic model. The model parameters are estimated via least-squares fitting of the model solution to the observed data in China. RESULTS: For the network model, we prove that the disease-free equilibrium is globally asymptotically stable when the basic reproduction is less than one. The final size will depend on the vaccination starting time, T, the number of infective cases at time T and immunization schemes to follow. Our theoretical results are confirmed by numerical simulations. Using the parameter estimates based on the observation data of the cumulative number of hospital notifications, we estimate the basic reproduction number R(0) to be 1.6809 in China. CONCLUSIONS: Network modelling supplies a useful tool for studying the transmission of H1N1 in China, capturing the main features of the spread of H1N1. While a uniform, mass-immunization strategy helps control the prevalence, a targeted immunization strategy focusing on specific groups with given connectivity may better control the endemic. |
format | Online Article Text |
id | pubmed-3317584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33175842012-04-04 Modelling and analysis of influenza A (H1N1) on networks Jin, Zhen Zhang, Juping Song, Li-Peng Sun, Gui-Quan Kan, Jianli Zhu, Huaiping BMC Public Health Research BACKGROUND: In April 2009, a new strain of H1N1 influenza virus, referred to as pandemic influenza A (H1N1) was first detected in humans in the United States, followed by an outbreak in the state of Veracruz, Mexico. Soon afterwards, this new virus kept spreading worldwide resulting in a global outbreak. In China, the second Circular of the Ministry of Health pointed out that as of December 31, 2009, the country’s 31 provinces had reported 120,000 confirmed cases of H1N1. METHODS: We formulate an epidemic model of influenza A based on networks. We calculate the basic reproduction number and study the effects of various immunization schemes. The final size relation is derived for the network epidemic model. The model parameters are estimated via least-squares fitting of the model solution to the observed data in China. RESULTS: For the network model, we prove that the disease-free equilibrium is globally asymptotically stable when the basic reproduction is less than one. The final size will depend on the vaccination starting time, T, the number of infective cases at time T and immunization schemes to follow. Our theoretical results are confirmed by numerical simulations. Using the parameter estimates based on the observation data of the cumulative number of hospital notifications, we estimate the basic reproduction number R(0) to be 1.6809 in China. CONCLUSIONS: Network modelling supplies a useful tool for studying the transmission of H1N1 in China, capturing the main features of the spread of H1N1. While a uniform, mass-immunization strategy helps control the prevalence, a targeted immunization strategy focusing on specific groups with given connectivity may better control the endemic. BioMed Central 2011-02-25 /pmc/articles/PMC3317584/ /pubmed/21356138 http://dx.doi.org/10.1186/1471-2458-11-S1-S9 Text en Copyright ©2011 Jin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Jin, Zhen Zhang, Juping Song, Li-Peng Sun, Gui-Quan Kan, Jianli Zhu, Huaiping Modelling and analysis of influenza A (H1N1) on networks |
title | Modelling and analysis of influenza A (H1N1) on networks |
title_full | Modelling and analysis of influenza A (H1N1) on networks |
title_fullStr | Modelling and analysis of influenza A (H1N1) on networks |
title_full_unstemmed | Modelling and analysis of influenza A (H1N1) on networks |
title_short | Modelling and analysis of influenza A (H1N1) on networks |
title_sort | modelling and analysis of influenza a (h1n1) on networks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317584/ https://www.ncbi.nlm.nih.gov/pubmed/21356138 http://dx.doi.org/10.1186/1471-2458-11-S1-S9 |
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