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The coronavirus response: Boxed in by models

Science has a mixed record when it comes to predicting the future. Engineers build bridges based on foreknowledge of the forces that they are likely to encounter – and their constructions tend to withstand the test of time. Predicting the future course of epidemics and building intervention to conta...

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Autor principal: Pawson, Ray
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653015/
http://dx.doi.org/10.1177/1356389020968579
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description Science has a mixed record when it comes to predicting the future. Engineers build bridges based on foreknowledge of the forces that they are likely to encounter – and their constructions tend to withstand the test of time. Predicting the future course of epidemics and building intervention to contain them are much more precarious. And yet simulation models produced in prestigious centres for mathematical biology have played a significant role informing coronavirus policy in the United Kingdom and elsewhere. The predictive uncertainties include the inherent variability of the pathogen, considerable variation in host population immunity as well as the concern of this article, namely, the constantly adapting human judgements of those designing, implementing and experiencing the national response to an outbreak. Assumptions about how interventions are implemented and how people will react are, of course, built into modelling scenarios – but these estimates depict behavioural change in fixed, stimulus-response terms. Real reactions to the complex restrictions introduced to combat the virus unfold in scores of different pathways – people comply, they resist, they learn, they grow weary, they change their minds, they seek exceptions and so on. Model building is intrinsically speculative, and it is important that crisis management is not boxed in by its latent simplifications. A more pluralistic evidence base needs to be drawn on, to understand how complex interventions operate within complex societies.
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spelling pubmed-76530152020-11-10 The coronavirus response: Boxed in by models Pawson, Ray Evaluation (Lond) Platform: Taking a position: making a case Science has a mixed record when it comes to predicting the future. Engineers build bridges based on foreknowledge of the forces that they are likely to encounter – and their constructions tend to withstand the test of time. Predicting the future course of epidemics and building intervention to contain them are much more precarious. And yet simulation models produced in prestigious centres for mathematical biology have played a significant role informing coronavirus policy in the United Kingdom and elsewhere. The predictive uncertainties include the inherent variability of the pathogen, considerable variation in host population immunity as well as the concern of this article, namely, the constantly adapting human judgements of those designing, implementing and experiencing the national response to an outbreak. Assumptions about how interventions are implemented and how people will react are, of course, built into modelling scenarios – but these estimates depict behavioural change in fixed, stimulus-response terms. Real reactions to the complex restrictions introduced to combat the virus unfold in scores of different pathways – people comply, they resist, they learn, they grow weary, they change their minds, they seek exceptions and so on. Model building is intrinsically speculative, and it is important that crisis management is not boxed in by its latent simplifications. A more pluralistic evidence base needs to be drawn on, to understand how complex interventions operate within complex societies. SAGE Publications 2020-11-05 /pmc/articles/PMC7653015/ http://dx.doi.org/10.1177/1356389020968579 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Platform: Taking a position: making a case
Pawson, Ray
The coronavirus response: Boxed in by models
title The coronavirus response: Boxed in by models
title_full The coronavirus response: Boxed in by models
title_fullStr The coronavirus response: Boxed in by models
title_full_unstemmed The coronavirus response: Boxed in by models
title_short The coronavirus response: Boxed in by models
title_sort coronavirus response: boxed in by models
topic Platform: Taking a position: making a case
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653015/
http://dx.doi.org/10.1177/1356389020968579
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