Cited by 249Policy Transfer and LearningCOVID-19 epidemiological studiesPublic Administration and Political Analysis

Explaining the homogeneous diffusion of COVID-19 nonpharmaceutical interventions across heterogeneous countries

Open access
Sebhatu, Abiel, Wennberg, Karl, Arora-Jonsson, Stefan, Lindberg, Staffan I.·2020·Proceedings of the National Academy of Sciences

Abstract

We analyze the adoption of nonpharmaceutical interventions in the Organisation for Economic Co-operation and Development (OECD) countries during the early phase of the coronavirus disease 2019 (COVID-19) pandemic. Given the complexity associated with pandemic decisions, governments are faced with the dilemma of how to act quickly when their core decision-making processes are based on deliberations balancing political considerations. Our findings show that, in times of severe crisis, governments follow the lead of others and base their decisions on what other countries do. Governments in countries with a stronger democratic structure are slower to react in the face of the pandemic but are more sensitive to the influence of other countries. We provide insights for research on international policy diffusion and research on the political consequences of the COVID-19 pandemic.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.2010625117

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Several other factors are also likely to affect the time to school closure, not least the severity of the threat posed by the pandemic and the increasing likelihood of learning as the pandemic progresses.

    “several other factors are also likely to affect the time to school closure, not least the severity of the threat posed by the pandemic -which affects need perceptions of both decision-makers and voters (Bechtel and Mannino 2022) -and the increasing likelihood of learning as the pandemic progresses (Sebhatu et al. 2020; Weible et al. 2020).”

    From Precaution and proportionality in pandemic politics: democracy, state capacity, and COVID-19-related school closures around the world (2022) · cites this paper as Sebhatu et al. 2020

    The International Policy Diffusion under Uncertainty section (page unavailable) says countries may learn about a policy at different times and that earlier adoptions can influence later decisions. But the Discussion says further research is needed to distinguish learning from emulation or coercion; the paper does not establish that learning becomes more likely as the pandemic progresses or that it affects school-closure timing specifically. The severity clause is cited to a different source. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 21

  1. [1]Davies N. G., The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: A modelling study. medRxiv:10.1101/2020.04.01.20049908 (6 April 2020). PMC7266572 32502389 · DOI
  2. [2]Ferguson N., “Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand” (Tech. Rep. 9, Imperial College London, 2020). PMC7140590 32270376
  3. [7]March J. G., A Primer on Decision Making - How Decisions Happen, (The Free Press, New York, NY, 1994).
  4. [11]Economist, Hard choices. The Economist, 4 April 2020, pp. 14–18 (2020).
  5. [13]Ioannidis J. P. A., Coronavirus disease 2019: The harms of exaggerated information and non-evidence-based measures. Eur. J. Clin. Invest. 50, e13222 (2020). 32191341 PMC7163529
  6. [14]Anderson R. M., Heesterbeek H., Klinkenberg D., Hollingsworth T. D., How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancet 395, 931– 934 (2020). 32164834 PMC7158572
  7. [15]Tetlock P., Counterfactual Thought Experiments in World Politics: Logical, Methodological, and Psychological Perspectives, (Princeton University Press, 1996).
  8. [19]Wilson M. C., Successful and failed episodes of democratization: Conceptualization, identification, and description. 10.2139/ssrn.3274599. Accessed 6 May 2020. · DOI
  9. [23]Rogers E., The Diffusion of Innovations, (The Free Press, New York, NY, 1995).
  10. [27]Boxenbaum E., Jonsson S., “ Isomorphism, diffusion and decoupling: Concept evolution and theoretical challenges” in The Sage Handbook of Organizational Institutionalism, Greenwood R., Oliver C., Lawrence T. B., Meyer R. E., Eds. (Sage, 2nd Ed., 2017), pp. 79– 104.
  11. [32]Mainwaring S., Pérez-Liñán A., Democracies and Dictatorships in Latin America: Emergence, Survival, and Fall, (Cambridge University Press, 2013).
  12. [35]Milani F., COVID-19 Outbreak, social response, and early economic effects: A Global VAR analysis of cross-country interdependencies. medRxiv:10.1101/2020.05.07.20094748 (12 May 2020). PMC7437387 32839640 · DOI
  13. [37]Dahl R., Polyarchy, (Yale University Press, New Haven, CT, 1971).
  14. [40]Besley T., Kudamatsu M., Health and democracy. Am. Econ. Rev. 96, 313– 318 (2006). 29131562
  15. [43]Dahl R. A., Democracy and Its Critics, (Yale University Press, 1989).
  16. [46]Przeworski A., Stokes S. C. S., Stokes S. C., Manin B., Democracy, Accountability, and Representation, (Cambridge University Press, 1999).
  17. [48]Coppedge M., Data from "V-Dem Dataset - Version 10." V-Dem. 10.23696/vdemds20. Accessed 1 April 2020. · DOI
  18. [50]Adolph C., Amano K., Bang-Jensen B., Fullman N., Wilkerson J., Pandemic politics: Timing state-level social distancing responses to COVID-19. medRxiv:10.1101/2020.03.30.20046326 (31 March 2020). 32955556 · DOI
  19. [52]Cepaluni G., Dorsch M., Branyiczki R., Political regimes and deaths in the early stages of the COVID-19 pandemic. SSRN 3586767 (29 April 2020).
  20. [54]Dowd J. B.., Demographic science aids in understanding the spread and fatality rates of COVID-19. Proc. Natl. Acad. Sci. U.S.A. 117, 9696– 9698 (2020). 32300018 PMC7211934
  21. [56]Amat F., Arenas A., Falcó-Gimeno A., Muñoz J., Pandemics meet democracy. Experimental evidence from the COVID-19 crisis in Spain. SocArXiv:10.31235/osf.io/dkusw (5 April 2020). · DOI

Cited by

Sorted by citations

Authors
Sebhatu, A., Wennberg, K., Arora-Jonsson, S., & Lindberg, S. I.
Affiliations
  • Linköping University (SE)
  • Department of Business Studies, Uppsala University, SE-751 20 Uppsala, Sweden;
  • University of Gothenburg (SE)
Corresponding author
Sebhatu, Abiel
Venue
Proceedings of the National Academy of Sciences
Published
2020-08-11
Volume
117
Issue
35
Pages
21201-21208
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W3048844313
Cited by
249
References
4
Citations by year
2026: 11 · 2025: 46 · 2024: 28 · 2023: 39 · 2022: 47 · 2021: 65 · 2020: 13
FWCI
141.59
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DiVA (Linkoping University) (submittedVersion, other-oa)
  • KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
Funders
  • Knut och Alice Wallenbergs Stiftelse (2018.0144, Grant 2018.0144)
  • Vetenskapsrådet
  • Göteborgs Universitet
  • H2020 European Research Council (724191)
Topics
  • Social Sciences › Political Science and International Relations › Policy Transfer and Learning
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Social Sciences › Political Science and International Relations › Public Administration and Political Analysis
Keywords
COVID-19 pandemic, non-pharmaceutical interventions, international policy diffusion, policy diffusion, democratic institutions, government decision-making, OECD countries, crisis response
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, Communicable Disease Control, Decision Making, Government, Health Policy, Humans, Models, Theoretical, Pneumonia, Viral, Time Factors, Coronavirus Infections, Uncertainty, Internationality, Pandemics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review