Evidence map›Paper›PMID 34611158›Full record

ArticleNature communications2021

Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe.

Mrinank Sharma, Sören Mindermann, Charlie Rogers-Smith, Gavin Leech, Benedict Snodin, Janvi Ahuja, Jonas B Sandbrink, Joshua Teperowski Monrad, George Altman, Gurpreet Dhaliwal and 14 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed, 3 pooled it
18.2field-weighted citation impact, top 1% of its field
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

124 citing papers in PubMed, 3 syntheses or guidelines pooled it, 224 citations in OpenAlex.

  1. Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023
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64 more citing papers are in PubMed but not listed here.

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

24 authors at 8 institutions in 3 countries.

Mrinank Sharma *Department of Statistics, University of Oxford, Oxford, UK. mrinank.sharma@eng.ox.ac.uk.ORCID http://orcid.org/0000-0002-4304-7963
Sören Mindermann *Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, UK. soren.mindermann@cs.ox.ac.uk.ORCID http://orcid.org/0000-0002-0315-9821
Charlie Rogers-SmithOATML Group (work done while at OATML as an external collaborator), Department of Computer Science, University of Oxford, Oxford, UK.
Gavin LeechDepartment of Computer Science, University of Bristol, Bristol, UK.ORCID http://orcid.org/0000-0002-9298-1488
Benedict SnodinFuture of Humanity Institute, University of Oxford, Oxford, UK.
Janvi AhujaFuture of Humanity Institute, University of Oxford, Oxford, UK.
Jonas B SandbrinkFuture of Humanity Institute, University of Oxford, Oxford, UK.
Joshua Teperowski MonradFuture of Humanity Institute, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-7377-2074
George AltmanManchester University NHS Foundation Trust, Manchester, UK.
Gurpreet DhaliwalThe Francis Crick Institute, London, UK.
Lukas FinnvedenFuture of Humanity Institute, University of Oxford, Oxford, UK.
Alexander John NormanMathematical, Physical and Life Sciences (MPLS) Doctoral Training Centre, University of Oxford, Oxford, UK.
Sebastian B OehmMedical Research Council Laboratory of Molecular Biology, Cambridge, UK.ORCID http://orcid.org/0000-0002-7099-0578
Julia Fabienne SandkühlerUniversity of Essen, Essen, Germany.
Laurence AitchisonDepartment of Computer Science, University of Bristol, Bristol, UK.
Tomáš GavenčiakIndependent scholar, Prague, Czech Republic.
Thomas MellanMedical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
Jan KulveitFuture of Humanity Institute, University of Oxford, Oxford, UK.
Leonid ChindelevitchMedical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
Seth FlaxmanDepartment of Mathematics, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-2477-4217
Yarin GalOxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-2733-2078
Swapnil MishraMedical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK. s.mishra@imperial.ac.uk.ORCID http://orcid.org/0000-0002-8759-5902
Samir BhattMedical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK. s.bhatt@imperial.ac.uk.ORCID http://orcid.org/0000-0002-0891-4611
Jan Markus Brauner *Future of Humanity Institute, University of Oxford, Oxford, UK. jan.brauner@eng.ox.ac.uk.ORCID http://orcid.org/0000-0002-1588-5724
University of Oxford · GBImperial College London · GBUniversity of Bristol · GBManchester University NHS Foundation Trust · GBMRC Laboratory of Molecular Biology · GBOxford Research Group · GBThe Francis Crick Institute · GBUniversity of Copenhagen · DK

Funding

Medical Research Council MC_PC_19012Medical Research Council MR/R015600/1Medical Research Council MR/V038109/1RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/T008784/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/S024050/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/S024050/1)RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/V002910/1
6 · The paper itself

Abstract

European governments use non-pharmaceutical interventions (NPIs) to control resurging waves of COVID-19. However, they only have outdated estimates for how effective individual NPIs were in the first wave. We estimate the effectiveness of 17 NPIs in Europe's second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe. Business closures, educational institution closures, and gathering bans reduced transmission, but reduced it less than they did in the first wave. This difference is likely due to organisational safety measures and individual protective behaviours-such as distancing-which made various areas of public life safer and thereby reduced the effect of closing them. Specifically, we find smaller effects for closing educational institutions, suggesting that stringent safety measures made schools safer compared to the first wave. Second-wave estimates outperform previous estimates at predicting transmission in Europe's third wave.

Indexed as

GovernmentBasic Reproduction NumberCOVID-19EuropeHumansModels, TheoreticalSARS-CoV-2Time Factors

Identifiers

PMID34611158
PMCPMC8492703
OpenAlexW3201866125

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.