Mathematical Models in Infectious Disease Epidemiology

The idea that transmission and spread of infectious diseases follows laws that can be formulated in mathematical language is old. In 1766 Daniel Bernoulli published an article where he described the effects of smallpox variolation (a precursor of vaccination) on life expectancy using mathematical li...

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Detalles Bibliográficos
Autores principales: Kretzschmar, Mirjam, Wallinga, Jacco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2009
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178885/
http://dx.doi.org/10.1007/978-0-387-93835-6_12
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author Kretzschmar, Mirjam
Wallinga, Jacco
author_facet Kretzschmar, Mirjam
Wallinga, Jacco
author_sort Kretzschmar, Mirjam
collection PubMed
description The idea that transmission and spread of infectious diseases follows laws that can be formulated in mathematical language is old. In 1766 Daniel Bernoulli published an article where he described the effects of smallpox variolation (a precursor of vaccination) on life expectancy using mathematical life table analysis (Dietz and Heesterbeek 2000). However, it was only in the twentieth century that the nonlinear dynamics of infectious disease transmission was really understood. In the beginning of that century there was much discussion about why an epidemic ended before all susceptibles were infected with hypotheses about changing virulence of the pathogen during the epidemic.
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spelling pubmed-71788852020-04-23 Mathematical Models in Infectious Disease Epidemiology Kretzschmar, Mirjam Wallinga, Jacco Modern Infectious Disease Epidemiology Article The idea that transmission and spread of infectious diseases follows laws that can be formulated in mathematical language is old. In 1766 Daniel Bernoulli published an article where he described the effects of smallpox variolation (a precursor of vaccination) on life expectancy using mathematical life table analysis (Dietz and Heesterbeek 2000). However, it was only in the twentieth century that the nonlinear dynamics of infectious disease transmission was really understood. In the beginning of that century there was much discussion about why an epidemic ended before all susceptibles were infected with hypotheses about changing virulence of the pathogen during the epidemic. 2009-07-28 /pmc/articles/PMC7178885/ http://dx.doi.org/10.1007/978-0-387-93835-6_12 Text en © Springer Science+Business Media, LLC 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 Article
Kretzschmar, Mirjam
Wallinga, Jacco
Mathematical Models in Infectious Disease Epidemiology
title Mathematical Models in Infectious Disease Epidemiology
title_full Mathematical Models in Infectious Disease Epidemiology
title_fullStr Mathematical Models in Infectious Disease Epidemiology
title_full_unstemmed Mathematical Models in Infectious Disease Epidemiology
title_short Mathematical Models in Infectious Disease Epidemiology
title_sort mathematical models in infectious disease epidemiology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178885/
http://dx.doi.org/10.1007/978-0-387-93835-6_12
work_keys_str_mv AT kretzschmarmirjam mathematicalmodelsininfectiousdiseaseepidemiology
AT wallingajacco mathematicalmodelsininfectiousdiseaseepidemiology

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