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Controlling infectious disease outbreaks: Lessons from mathematical modelling

Epidemiological analysis and mathematical models are now essential tools in understanding the dynamics of infectious diseases and in designing public health strategies to contain them. They have provided fundamental concepts, such as the basic and effective reproduction number, generation times, epi...

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Autor principal: Hollingsworth, T Déirdre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Palgrave Macmillan UK 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099230/
https://www.ncbi.nlm.nih.gov/pubmed/19806073
http://dx.doi.org/10.1057/jphp.2009.13
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author Hollingsworth, T Déirdre
author_facet Hollingsworth, T Déirdre
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description Epidemiological analysis and mathematical models are now essential tools in understanding the dynamics of infectious diseases and in designing public health strategies to contain them. They have provided fundamental concepts, such as the basic and effective reproduction number, generation times, epidemic growth rates, and the role of pre-symptomatic infectiousness, which are crucial in characterising infectious diseases. These concepts are outlined and their relevance in designing control policies for outbreaks is discussed. They are illustrated using examples from the 2003 severe acute respiratory syndrome outbreak, which was brought under control within a year, and from pandemic influenza planning, where mathematical models have been used extensively.
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spelling pubmed-70992302020-03-27 Controlling infectious disease outbreaks: Lessons from mathematical modelling Hollingsworth, T Déirdre J Public Health Policy Original Article Epidemiological analysis and mathematical models are now essential tools in understanding the dynamics of infectious diseases and in designing public health strategies to contain them. They have provided fundamental concepts, such as the basic and effective reproduction number, generation times, epidemic growth rates, and the role of pre-symptomatic infectiousness, which are crucial in characterising infectious diseases. These concepts are outlined and their relevance in designing control policies for outbreaks is discussed. They are illustrated using examples from the 2003 severe acute respiratory syndrome outbreak, which was brought under control within a year, and from pandemic influenza planning, where mathematical models have been used extensively. Palgrave Macmillan UK 2009-10-05 2009 /pmc/articles/PMC7099230/ /pubmed/19806073 http://dx.doi.org/10.1057/jphp.2009.13 Text en © Palgrave Macmillan 2009 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Hollingsworth, T Déirdre
Controlling infectious disease outbreaks: Lessons from mathematical modelling
title Controlling infectious disease outbreaks: Lessons from mathematical modelling
title_full Controlling infectious disease outbreaks: Lessons from mathematical modelling
title_fullStr Controlling infectious disease outbreaks: Lessons from mathematical modelling
title_full_unstemmed Controlling infectious disease outbreaks: Lessons from mathematical modelling
title_short Controlling infectious disease outbreaks: Lessons from mathematical modelling
title_sort controlling infectious disease outbreaks: lessons from mathematical modelling
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099230/
https://www.ncbi.nlm.nih.gov/pubmed/19806073
http://dx.doi.org/10.1057/jphp.2009.13
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