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Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza
Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence tim...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243394/ https://www.ncbi.nlm.nih.gov/pubmed/21715400 http://dx.doi.org/10.1098/rsif.2011.0309 |
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author | Truscott, James Fraser, Christophe Cauchemez, Simon Meeyai, Aronrag Hinsley, Wes Donnelly, Christl A. Ghani, Azra Ferguson, Neil |
author_facet | Truscott, James Fraser, Christophe Cauchemez, Simon Meeyai, Aronrag Hinsley, Wes Donnelly, Christl A. Ghani, Azra Ferguson, Neil |
author_sort | Truscott, James |
collection | PubMed |
description | Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. By constraining the output of simple models to match these characteristic features, we investigate the role played by population heterogeneity, multiple strains, cross-immunity and the rate of strain evolution in the generation of incidence time series. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match observed time-series data. Our work gives estimates of the seasonal peak basic reproduction number, R(0), in the range 1.6–3. Estimates of R(0) are strongly correlated with the timescale for waning of immunity to current circulating seasonal influenza strain, which we estimate is between 3 and 8 years. Seasonal variation in transmissibility is largely confined to 15–30% of its mean value. While population heterogeneity and cross-immunity are required mechanisms, the degree of heterogeneity and cross-immunity is not tightly constrained. We discuss our findings in the context of other work fitting to seasonal influenza data. |
format | Online Article Text |
id | pubmed-3243394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-32433942011-12-22 Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza Truscott, James Fraser, Christophe Cauchemez, Simon Meeyai, Aronrag Hinsley, Wes Donnelly, Christl A. Ghani, Azra Ferguson, Neil J R Soc Interface Research Articles Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. By constraining the output of simple models to match these characteristic features, we investigate the role played by population heterogeneity, multiple strains, cross-immunity and the rate of strain evolution in the generation of incidence time series. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match observed time-series data. Our work gives estimates of the seasonal peak basic reproduction number, R(0), in the range 1.6–3. Estimates of R(0) are strongly correlated with the timescale for waning of immunity to current circulating seasonal influenza strain, which we estimate is between 3 and 8 years. Seasonal variation in transmissibility is largely confined to 15–30% of its mean value. While population heterogeneity and cross-immunity are required mechanisms, the degree of heterogeneity and cross-immunity is not tightly constrained. We discuss our findings in the context of other work fitting to seasonal influenza data. The Royal Society 2012-02-07 2011-06-29 /pmc/articles/PMC3243394/ /pubmed/21715400 http://dx.doi.org/10.1098/rsif.2011.0309 Text en This journal is © 2011 The Royal Society http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Truscott, James Fraser, Christophe Cauchemez, Simon Meeyai, Aronrag Hinsley, Wes Donnelly, Christl A. Ghani, Azra Ferguson, Neil Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
title | Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
title_full | Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
title_fullStr | Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
title_full_unstemmed | Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
title_short | Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
title_sort | essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243394/ https://www.ncbi.nlm.nih.gov/pubmed/21715400 http://dx.doi.org/10.1098/rsif.2011.0309 |
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