Evidence map›Paper›PMID 36227023›Full record

ArticleSocial studies of science2023

Domesticating models: On the contingency of Covid-19 modelling in UK media and policy.

Lukas Engelmann, Catherine M Montgomery, Steve Sturdy, Cristina Moreno Lozano

Abstract read
In one paragraph

Article in Social studies of science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Models of Pandemics: What Should We Do Differently Next Time?Journal of evaluation in clinical practice · 2026
    Article
  2. Article
  3. How Will AI Shape the Future of Pandemic Response? Early Clues From Data Analytics.Risk analysis : an official publication of the Society for Risk Analysis · 2025
    Review
  4. Epistemic preparedness.BMJ global health · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lukas EngelmannUniversity of Edinburgh, Edinburgh, UK.ORCID 0000-0002-2175-0156
Catherine M MontgomeryUniversity of Edinburgh, Edinburgh, UK.ORCID 0000-0002-5829-6137
Steve SturdyUniversity of Edinburgh, Edinburgh, UK.
Cristina Moreno LozanoUniversity of Edinburgh, Edinburgh, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Our article traces the representation of pandemic modelling in UK print media from the emergence of Covid-19 to the early stages of implementing the first UK-wide lockdown in late March 2020. Covid modelling, it is widely assumed, has shaped policy decisions and public responses to the pandemic in unprecedented ways. We analyse how the UK print media has configured modelling as a significant evidence tool in the representation of the pandemic. Interrogating assumptions about infectious disease modelling, we ask why models became the trusted tool of choice for knowing and responding to the Covid pandemic in the UK. Our analysis has yielded four different periods in the evolution of intersecting policy and media frames. Initially, modellers, policymakers and media alike emphasized uncertainty about available data, and hence the speculative character of modelled projections, thus justifying a 'wait and see' approach to government intervention. With growing public pressure for government action, policy and media frames were adjusted to emphasize the importance of timing interventions for best effect, with modelling evidence mobilized to justify inaction. This gave way to a period of crisis, as the press increasingly questioned the reliability of the existing models and policies, leading modellers and policy makers to dramatically revise their projections. Finally, with the imposition of the first UK lockdown, policy and media frames were brought back into alignment with one another, in a process of domestication through which the language of modelling became a basic resource for the discussion of the epidemic. Our epistemological microhistory thus challenges general accounts of the impacts of pandemic modelling and instead emphasizes contingency and interpretative flexibility.

Indexed as

COVID-19Communicable Disease ControlHealth PolicyHumansPandemicsReproducibility of ResultsUnited KingdomCovid-19media analysismodellingpandemic policyperformativity

Identifiers

PMID36227023
PMCPMC9892880

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.