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Epidemic curves made easy using the R package incidence

The epidemiological curve (epicurve) is one of the simplest yet most useful tools used by field epidemiologists, modellers, and decision makers for assessing the dynamics of infectious disease epidemics. Here, we present the free, open-source package incidence for the R programming language, which a...

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Autores principales: Kamvar, Zhian N., Cai, Jun, Pulliam, Juliet R.C., Schumacher, Jakob, Jombart, Thibaut
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509961/
https://www.ncbi.nlm.nih.gov/pubmed/31119031
http://dx.doi.org/10.12688/f1000research.18002.1
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author Kamvar, Zhian N.
Cai, Jun
Pulliam, Juliet R.C.
Schumacher, Jakob
Jombart, Thibaut
author_facet Kamvar, Zhian N.
Cai, Jun
Pulliam, Juliet R.C.
Schumacher, Jakob
Jombart, Thibaut
author_sort Kamvar, Zhian N.
collection PubMed
description The epidemiological curve (epicurve) is one of the simplest yet most useful tools used by field epidemiologists, modellers, and decision makers for assessing the dynamics of infectious disease epidemics. Here, we present the free, open-source package incidence for the R programming language, which allows users to easily compute, handle, and visualise epicurves from unaggregated linelist data. This package was built in accordance with the development guidelines of the R Epidemics Consortium (RECON), which aim to ensure robustness and reliability through extensive automated testing, documentation, and good coding practices. As such, it fills an important gap in the toolbox for outbreak analytics using the R software, and provides a solid building block for further developments in infectious disease modelling. incidence is available from https://www.repidemicsconsortium.org/incidence.
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spelling pubmed-65099612019-05-21 Epidemic curves made easy using the R package incidence Kamvar, Zhian N. Cai, Jun Pulliam, Juliet R.C. Schumacher, Jakob Jombart, Thibaut F1000Res Software Tool Article The epidemiological curve (epicurve) is one of the simplest yet most useful tools used by field epidemiologists, modellers, and decision makers for assessing the dynamics of infectious disease epidemics. Here, we present the free, open-source package incidence for the R programming language, which allows users to easily compute, handle, and visualise epicurves from unaggregated linelist data. This package was built in accordance with the development guidelines of the R Epidemics Consortium (RECON), which aim to ensure robustness and reliability through extensive automated testing, documentation, and good coding practices. As such, it fills an important gap in the toolbox for outbreak analytics using the R software, and provides a solid building block for further developments in infectious disease modelling. incidence is available from https://www.repidemicsconsortium.org/incidence. F1000 Research Limited 2019-01-31 /pmc/articles/PMC6509961/ /pubmed/31119031 http://dx.doi.org/10.12688/f1000research.18002.1 Text en Copyright: © 2019 Kamvar ZN et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Kamvar, Zhian N.
Cai, Jun
Pulliam, Juliet R.C.
Schumacher, Jakob
Jombart, Thibaut
Epidemic curves made easy using the R package incidence
title Epidemic curves made easy using the R package incidence
title_full Epidemic curves made easy using the R package incidence
title_fullStr Epidemic curves made easy using the R package incidence
title_full_unstemmed Epidemic curves made easy using the R package incidence
title_short Epidemic curves made easy using the R package incidence
title_sort epidemic curves made easy using the r package incidence
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509961/
https://www.ncbi.nlm.nih.gov/pubmed/31119031
http://dx.doi.org/10.12688/f1000research.18002.1
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