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Determining the dynamics of influenza transmission by age

Identifieur interne : 000E73 ( Main/Exploration ); précédent : 000E72; suivant : 000E74

Determining the dynamics of influenza transmission by age

Auteurs : Laura F. White [États-Unis] ; Brett Archer [Afrique du Sud] ; Marcello Pagano [États-Unis]

Source :

RBID : PMC:3997935

Abstract

Background

It is widely accepted that influenza transmission dynamics vary by age; however methods to quantify the reproductive number by age group are limited. We introduce a simple method to estimate the reproductive number by modifying the method originally proposed by Wallinga and Teunis and using existing information on contact patterns between age groups. We additionally perform a sensitivity analysis to determine the potential impact of differential healthcare seeking patterns by age. We illustrate this method using data from the 2009 H1N1 Influenza pandemic in Gauteng Province, South Africa.

Results

Our results are consistent with others in showing decreased transmission with age. We show that results can change markedly when we make the account for differential healthcare seeking behaviors by age.

Conclusions

We show substantial heterogeneity in transmission by age group during the Influenza A H1N1 pandemic in South Africa. This information can greatly assist in targeting interventions and implementing social distancing measures.


Url:
DOI: 10.1186/1742-7622-11-4
PubMed: 24656239
PubMed Central: 3997935


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<p>It is widely accepted that influenza transmission dynamics vary by age; however methods to quantify the reproductive number by age group are limited. We introduce a simple method to estimate the reproductive number by modifying the method originally proposed by Wallinga and Teunis and using existing information on contact patterns between age groups. We additionally perform a sensitivity analysis to determine the potential impact of differential healthcare seeking patterns by age. We illustrate this method using data from the 2009 H1N1 Influenza pandemic in Gauteng Province, South Africa.</p>
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<p>Our results are consistent with others in showing decreased transmission with age. We show that results can change markedly when we make the account for differential healthcare seeking behaviors by age.</p>
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<p>We show substantial heterogeneity in transmission by age group during the Influenza A H1N1 pandemic in South Africa. This information can greatly assist in targeting interventions and implementing social distancing measures.</p>
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