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Planning for the next influenza H1N1 season: a modelling study

BACKGROUND: The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge. METHODS: This was a modelling study based on data on medical visits for influenza-like illness collected...

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Autores principales: Carrat, Fabrice, Pelat, Camille, Levy-Bruhl, Daniel, Bonmarin, Isabelle, Lapidus, Nathanael
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2975658/
https://www.ncbi.nlm.nih.gov/pubmed/20964814
http://dx.doi.org/10.1186/1471-2334-10-301
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author Carrat, Fabrice
Pelat, Camille
Levy-Bruhl, Daniel
Bonmarin, Isabelle
Lapidus, Nathanael
author_facet Carrat, Fabrice
Pelat, Camille
Levy-Bruhl, Daniel
Bonmarin, Isabelle
Lapidus, Nathanael
author_sort Carrat, Fabrice
collection PubMed
description BACKGROUND: The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge. METHODS: This was a modelling study based on data on medical visits for influenza-like illness collected by the French General Practitioner Sentinel network, as well as pandemic H1N1 vaccination coverage rates, and an individual-centred model devoted to influenza. We estimated infection attack rates during the first 2009 pandemic H1N1 season in France, and the rates of pre- and post-exposure immunity. We then simulated various scenarios in which a pandemic influenza H1N1 virus would be reintroduced into a population with varying levels of protective cross-immunity, and considered the impact of extending influenza vaccination. RESULTS: During the first pandemic season in France, the proportion of infected persons was 18.1% overall, 38.3% among children, 14.8% among younger adults and 1.6% among the elderly. The rates of pre-exposure immunity required to fit data collected during the first pandemic season were 36% in younger adults and 85% in the elderly. We estimated that the rate of post-exposure immunity was 57.3% (95% Confidence Interval (95%CI) 49.6%-65.0%) overall, 44.6% (95%CI 35.5%-53.6%) in children, 53.8% (95%CI 44.5%-63.1%) in younger adults, and 87.4% (95%CI 82.0%-92.8%) in the elderly. The shape of a second season would depend on the degree of persistent protective cross-immunity to descendants of the 2009 H1N1 viruses. A cross-protection rate of 70% would imply that only a small proportion of the population would be affected. With a cross-protection rate of 50%, the second season would have a disease burden similar to the first, while vaccination of 50% of the entire population, in addition to the population vaccinated during the first pandemic season, would halve this burden. With a cross-protection rate of 30%, the second season could be more substantial, and vaccination would not provide a significant benefit. CONCLUSIONS: These model-based findings should help to prepare for a second pandemic season, and highlight the need for studies of the different components of immune protection.
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spelling pubmed-29756582010-11-09 Planning for the next influenza H1N1 season: a modelling study Carrat, Fabrice Pelat, Camille Levy-Bruhl, Daniel Bonmarin, Isabelle Lapidus, Nathanael BMC Infect Dis Research Article BACKGROUND: The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge. METHODS: This was a modelling study based on data on medical visits for influenza-like illness collected by the French General Practitioner Sentinel network, as well as pandemic H1N1 vaccination coverage rates, and an individual-centred model devoted to influenza. We estimated infection attack rates during the first 2009 pandemic H1N1 season in France, and the rates of pre- and post-exposure immunity. We then simulated various scenarios in which a pandemic influenza H1N1 virus would be reintroduced into a population with varying levels of protective cross-immunity, and considered the impact of extending influenza vaccination. RESULTS: During the first pandemic season in France, the proportion of infected persons was 18.1% overall, 38.3% among children, 14.8% among younger adults and 1.6% among the elderly. The rates of pre-exposure immunity required to fit data collected during the first pandemic season were 36% in younger adults and 85% in the elderly. We estimated that the rate of post-exposure immunity was 57.3% (95% Confidence Interval (95%CI) 49.6%-65.0%) overall, 44.6% (95%CI 35.5%-53.6%) in children, 53.8% (95%CI 44.5%-63.1%) in younger adults, and 87.4% (95%CI 82.0%-92.8%) in the elderly. The shape of a second season would depend on the degree of persistent protective cross-immunity to descendants of the 2009 H1N1 viruses. A cross-protection rate of 70% would imply that only a small proportion of the population would be affected. With a cross-protection rate of 50%, the second season would have a disease burden similar to the first, while vaccination of 50% of the entire population, in addition to the population vaccinated during the first pandemic season, would halve this burden. With a cross-protection rate of 30%, the second season could be more substantial, and vaccination would not provide a significant benefit. CONCLUSIONS: These model-based findings should help to prepare for a second pandemic season, and highlight the need for studies of the different components of immune protection. BioMed Central 2010-10-21 /pmc/articles/PMC2975658/ /pubmed/20964814 http://dx.doi.org/10.1186/1471-2334-10-301 Text en Copyright ©2010 Carrat 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 Article
Carrat, Fabrice
Pelat, Camille
Levy-Bruhl, Daniel
Bonmarin, Isabelle
Lapidus, Nathanael
Planning for the next influenza H1N1 season: a modelling study
title Planning for the next influenza H1N1 season: a modelling study
title_full Planning for the next influenza H1N1 season: a modelling study
title_fullStr Planning for the next influenza H1N1 season: a modelling study
title_full_unstemmed Planning for the next influenza H1N1 season: a modelling study
title_short Planning for the next influenza H1N1 season: a modelling study
title_sort planning for the next influenza h1n1 season: a modelling study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2975658/
https://www.ncbi.nlm.nih.gov/pubmed/20964814
http://dx.doi.org/10.1186/1471-2334-10-301
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