Model uncertainty, the COVID-19 pandemic, and the science-policy interface
(2024) In Royal Society Open Science 11(2).- Abstract
- The COVID-19 pandemic illustrated many of the challenges with using science to guide planning and policymaking. One such challenge has to do with how to manage, represent and communicate uncertainties in epidemiological models. This is considerably complicated, we argue, by the fact that the models themselves are often instrumental in structuring the involved uncertainties. In this paper we explore how models ‘domesticate’ uncertainties and what this implies for science-for-policy. We analyse three examples of uncertainty domestication in models of COVID-19 and argue that we need to pay more attention to how uncertainties are domesticated in models used for policy support, and the many ways in which uncertainties are domesticated within... (More)
- The COVID-19 pandemic illustrated many of the challenges with using science to guide planning and policymaking. One such challenge has to do with how to manage, represent and communicate uncertainties in epidemiological models. This is considerably complicated, we argue, by the fact that the models themselves are often instrumental in structuring the involved uncertainties. In this paper we explore how models ‘domesticate’ uncertainties and what this implies for science-for-policy. We analyse three examples of uncertainty domestication in models of COVID-19 and argue that we need to pay more attention to how uncertainties are domesticated in models used for policy support, and the many ways in which uncertainties are domesticated within particular models can fail to fit with the needs and demands of policymakers and planners. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/829614b5-213a-423e-b281-cd7a5b18313f
- author
- Thorén, Henrik LU and Gerlee, Philip
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Royal Society Open Science
- volume
- 11
- issue
- 2
- article number
- 230803
- publisher
- Royal Society Publishing
- external identifiers
-
- scopus:85185335838
- pmid:38356870
- ISSN
- 2054-5703
- DOI
- 10.1098/rsos.230803
- language
- English
- LU publication?
- yes
- id
- 829614b5-213a-423e-b281-cd7a5b18313f
- date added to LUP
- 2024-01-11 14:54:56
- date last changed
- 2024-03-28 03:00:35
@article{829614b5-213a-423e-b281-cd7a5b18313f, abstract = {{The COVID-19 pandemic illustrated many of the challenges with using science to guide planning and policymaking. One such challenge has to do with how to manage, represent and communicate uncertainties in epidemiological models. This is considerably complicated, we argue, by the fact that the models themselves are often instrumental in structuring the involved uncertainties. In this paper we explore how models ‘domesticate’ uncertainties and what this implies for science-for-policy. We analyse three examples of uncertainty domestication in models of COVID-19 and argue that we need to pay more attention to how uncertainties are domesticated in models used for policy support, and the many ways in which uncertainties are domesticated within particular models can fail to fit with the needs and demands of policymakers and planners.}}, author = {{Thorén, Henrik and Gerlee, Philip}}, issn = {{2054-5703}}, language = {{eng}}, number = {{2}}, publisher = {{Royal Society Publishing}}, series = {{Royal Society Open Science}}, title = {{Model uncertainty, the COVID-19 pandemic, and the science-policy interface}}, url = {{http://dx.doi.org/10.1098/rsos.230803}}, doi = {{10.1098/rsos.230803}}, volume = {{11}}, year = {{2024}}, }