Confidence in Covid-19 models

Nguyen, James (2024) Confidence in Covid-19 models. Synthese, 203 (4). ISSN 0039-7857

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Abstract

Epidemiological models of the transmission of SARS-CoV-2 played an important role in guiding the decisions of policy-makers during the pandemic. Such models provide output projections, in the form of time -series of infections, hospitalisations, and deaths, under various different parameter and scenario assumptions. In this paper I caution against handling these outputs uncritically: raw model-outputs should not be presented as direct projections in contexts where modelling results are required to support policy -decisions. I argue that model uncertainty should be handled and communicated transparently. Drawing on methods used by climate scientists in the fifth IPCC report I suggest that this can be done by: attaching confidence judgements to projections based on model results; being transparent about how multi-model ensembles are supposed to deal with such uncertainty; and using expert judgement to ‘translate’ model-outputs into projections about the actual world. In a slogan: tell me what you think (and why), not (just) what your models say. I then diffuse the worry that this approach infects model-based policy advice with some undesirably subjective elements, and explore how my discussion fares if one thinks the role of a scientific advisor is to prompt action, rather than communicate information.

Item Type:	Article
Official URL:	https://link.springer.com/journal/11229
Additional Information:	© 2024 The Author(s)
Divisions:	CPNSS
Subjects:	B Philosophy. Psychology. Religion > B Philosophy (General) R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine H Social Sciences > HV Social pathology. Social and public welfare. Criminology
Date Deposited:	11 Apr 2024 15:03
Last Modified:	15 Nov 2024 05:57
URI:	http://eprints.lse.ac.uk/id/eprint/122612

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