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Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling
The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612598/ https://www.ncbi.nlm.nih.gov/pubmed/35180542 http://dx.doi.org/10.1016/j.epidem.2022.100547 |
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author | Swallow, Ben Birrell, Paul Blake, Joshua Burgman, Mark Challenor, Peter Coffeng, Luc E. Dawid, Philip De Angelis, Daniela Goldstein, Michael Hemming, Victoria Marion, Glenn McKinley, Trevelyan J. Overton, Christopher E. Panovska-Griffiths, Jasmina Pellis, Lorenzo Probert, Will Shea, Katriona Villela, Daniel Vernon, Ian |
author_facet | Swallow, Ben Birrell, Paul Blake, Joshua Burgman, Mark Challenor, Peter Coffeng, Luc E. Dawid, Philip De Angelis, Daniela Goldstein, Michael Hemming, Victoria Marion, Glenn McKinley, Trevelyan J. Overton, Christopher E. Panovska-Griffiths, Jasmina Pellis, Lorenzo Probert, Will Shea, Katriona Villela, Daniel Vernon, Ian |
author_sort | Swallow, Ben |
collection | PubMed |
description | The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics. |
format | Online Article Text |
id | pubmed-7612598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76125982022-04-11 Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling Swallow, Ben Birrell, Paul Blake, Joshua Burgman, Mark Challenor, Peter Coffeng, Luc E. Dawid, Philip De Angelis, Daniela Goldstein, Michael Hemming, Victoria Marion, Glenn McKinley, Trevelyan J. Overton, Christopher E. Panovska-Griffiths, Jasmina Pellis, Lorenzo Probert, Will Shea, Katriona Villela, Daniel Vernon, Ian Epidemics Article The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics. 2022-03-01 2022-02-10 /pmc/articles/PMC7612598/ /pubmed/35180542 http://dx.doi.org/10.1016/j.epidem.2022.100547 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Swallow, Ben Birrell, Paul Blake, Joshua Burgman, Mark Challenor, Peter Coffeng, Luc E. Dawid, Philip De Angelis, Daniela Goldstein, Michael Hemming, Victoria Marion, Glenn McKinley, Trevelyan J. Overton, Christopher E. Panovska-Griffiths, Jasmina Pellis, Lorenzo Probert, Will Shea, Katriona Villela, Daniel Vernon, Ian Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
title | Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
title_full | Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
title_fullStr | Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
title_full_unstemmed | Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
title_short | Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
title_sort | challenges in estimation, uncertainty quantification and elicitation for pandemic modelling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612598/ https://www.ncbi.nlm.nih.gov/pubmed/35180542 http://dx.doi.org/10.1016/j.epidem.2022.100547 |
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