Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.

Swallow B., Birrell P., Blake J., Burgman M., Challenor P., Coffeng LE., Dawid P., De Angelis D., Goldstein M., Hemming V., Marion G., McKinley TJ., Overton CE., Panovska-Griffiths J., Pellis L., Probert W., Shea K., Villela D., Vernon I.

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.

DOI

10.1016/j.epidem.2022.100547

Type

Journal article

Journal

Epidemics

Publication Date

10/02/2022

Volume

38

Addresses

School of Mathematics and Statistics, University of Glasgow, Glasgow, UK; Scottish COVID-19 Response Consortium, UK. Electronic address: ben.swallow@glasgow.ac.uk.

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