An introduction to compartmental modeling for the budding infectious disease modeler

Mathematical models are ubiquitous in the study of the transmission dynamics of infectious diseases, In particular, the classic ‘susceptible-infectious-recovered’ (SIR) paradigm provides a modeling framework that can be adapted to describe the core transmission dynamics of a range of human and wildl...

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Main Authors: Julie C. Blackwood, Lauren M. Childs
Format: Article
Language:English
Published: Intercollegiate Biomathematics Alliance 2018-12-01
Series:Letters in Biomathematics
Subjects:
Online Access:http://dx.doi.org/10.1080/23737867.2018.1509026
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spelling doaj-6b2a1303622246768e21c7a8ff4d24af2020-11-25T03:01:27ZengIntercollegiate Biomathematics AllianceLetters in Biomathematics2373-78672018-12-015119522110.1080/23737867.2018.15090261509026An introduction to compartmental modeling for the budding infectious disease modelerJulie C. Blackwood0Lauren M. Childs1Williams CollegeVirginia TechMathematical models are ubiquitous in the study of the transmission dynamics of infectious diseases, In particular, the classic ‘susceptible-infectious-recovered’ (SIR) paradigm provides a modeling framework that can be adapted to describe the core transmission dynamics of a range of human and wildlife diseases. These models provide an important tool for uncovering the mechanisms generating observed disease dynamics, evaluating potential control strategies, and predicting future outbreaks. With ongoing advances in computational tools as well as access to disease incidence data, the use of such models continues to increase. Here, we provide a basic introduction to disease modeling that is primarily intended for individuals who are new to developing SIR-type models. In particular, we highlight several common issues encountered when structuring and analyzing these models.http://dx.doi.org/10.1080/23737867.2018.1509026Mathematical modelcompartmental modelbasic reproductive numbertransmission
collection DOAJ
language English
format Article
sources DOAJ
author Julie C. Blackwood
Lauren M. Childs
spellingShingle Julie C. Blackwood
Lauren M. Childs
An introduction to compartmental modeling for the budding infectious disease modeler
Letters in Biomathematics
Mathematical model
compartmental model
basic reproductive number
transmission
author_facet Julie C. Blackwood
Lauren M. Childs
author_sort Julie C. Blackwood
title An introduction to compartmental modeling for the budding infectious disease modeler
title_short An introduction to compartmental modeling for the budding infectious disease modeler
title_full An introduction to compartmental modeling for the budding infectious disease modeler
title_fullStr An introduction to compartmental modeling for the budding infectious disease modeler
title_full_unstemmed An introduction to compartmental modeling for the budding infectious disease modeler
title_sort introduction to compartmental modeling for the budding infectious disease modeler
publisher Intercollegiate Biomathematics Alliance
series Letters in Biomathematics
issn 2373-7867
publishDate 2018-12-01
description Mathematical models are ubiquitous in the study of the transmission dynamics of infectious diseases, In particular, the classic ‘susceptible-infectious-recovered’ (SIR) paradigm provides a modeling framework that can be adapted to describe the core transmission dynamics of a range of human and wildlife diseases. These models provide an important tool for uncovering the mechanisms generating observed disease dynamics, evaluating potential control strategies, and predicting future outbreaks. With ongoing advances in computational tools as well as access to disease incidence data, the use of such models continues to increase. Here, we provide a basic introduction to disease modeling that is primarily intended for individuals who are new to developing SIR-type models. In particular, we highlight several common issues encountered when structuring and analyzing these models.
topic Mathematical model
compartmental model
basic reproductive number
transmission
url http://dx.doi.org/10.1080/23737867.2018.1509026
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