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Communicating uncertainty in epidemic models
While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate u...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562068/ https://www.ncbi.nlm.nih.gov/pubmed/34749076 http://dx.doi.org/10.1016/j.epidem.2021.100520 |
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author | McCabe, Ruth Kont, Mara D. Schmit, Nora Whittaker, Charles Løchen, Alessandra Walker, Patrick G.T. Ghani, Azra C. Ferguson, Neil M. White, Peter J. Donnelly, Christl A. Watson, Oliver J. |
author_facet | McCabe, Ruth Kont, Mara D. Schmit, Nora Whittaker, Charles Løchen, Alessandra Walker, Patrick G.T. Ghani, Azra C. Ferguson, Neil M. White, Peter J. Donnelly, Christl A. Watson, Oliver J. |
author_sort | McCabe, Ruth |
collection | PubMed |
description | While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner. |
format | Online Article Text |
id | pubmed-8562068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-85620682021-11-02 Communicating uncertainty in epidemic models McCabe, Ruth Kont, Mara D. Schmit, Nora Whittaker, Charles Løchen, Alessandra Walker, Patrick G.T. Ghani, Azra C. Ferguson, Neil M. White, Peter J. Donnelly, Christl A. Watson, Oliver J. Epidemics Article While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner. Elsevier 2021-12 /pmc/articles/PMC8562068/ /pubmed/34749076 http://dx.doi.org/10.1016/j.epidem.2021.100520 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article McCabe, Ruth Kont, Mara D. Schmit, Nora Whittaker, Charles Løchen, Alessandra Walker, Patrick G.T. Ghani, Azra C. Ferguson, Neil M. White, Peter J. Donnelly, Christl A. Watson, Oliver J. Communicating uncertainty in epidemic models |
title | Communicating uncertainty in epidemic models |
title_full | Communicating uncertainty in epidemic models |
title_fullStr | Communicating uncertainty in epidemic models |
title_full_unstemmed | Communicating uncertainty in epidemic models |
title_short | Communicating uncertainty in epidemic models |
title_sort | communicating uncertainty in epidemic models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562068/ https://www.ncbi.nlm.nih.gov/pubmed/34749076 http://dx.doi.org/10.1016/j.epidem.2021.100520 |
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