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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

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Authors

Ben Swallow

Paul Birrell

Joshua Blake

Mark Burgman

Peter Challenor

Luc E. Coffeng

Philip Dawid

Daniela De Angelis

Victoria Hemming

Glenn Marion

Trevelyan J. McKinley

Christopher E. Overton

Jasmina Panovska-Griffiths

Lorenzo Pellis

Will Probert

Katriona Shea

Daniel Villela



Abstract

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.

Citation

Swallow, B., Birrell, P., Blake, J., Burgman, M., Challenor, P., Coffeng, L. E., …Vernon, I. (2022). Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 38, https://doi.org/10.1016/j.epidem.2022.100547

Journal Article Type Article
Acceptance Date Feb 9, 2022
Online Publication Date Feb 15, 2022
Publication Date 2022-03
Deposit Date Apr 5, 2022
Publicly Available Date Apr 6, 2022
Journal Epidemics
Print ISSN 1755-4365
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 38
DOI https://doi.org/10.1016/j.epidem.2022.100547

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