Evidence map›Paper›PMID 35421094›Full record

ArticlePloS one2022

Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling study.

Kellyn F Arnold, Mark S Gilthorpe, Nisreen A Alwan, Alison J Heppenstall, Georgia D Tomova, Martin McKee, Peter W G Tennant

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. The attributes of public health leadership.European journal of public health · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. COVID-19 severity is associated with population-level gut microbiome variations.Frontiers in cellular and infection microbiology · 2022
    Article
  14. Economics and economists during the COVID-19 pandemic: a personal view.Swiss journal of economics and statistics · 2022
    Article
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

7 authors.

Kellyn F ArnoldLeeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.ORCID 0000-0002-0911-5029
Mark S GilthorpeLeeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.
Nisreen A AlwanSchool of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.ORCID 0000-0002-4134-8463
Alison J HeppenstallSchool of Social and Political Sciences, MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.
Georgia D TomovaLeeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.ORCID 0000-0003-1984-8055
Martin McKeeLondon School of Hygiene and Tropical Medicine, London, United Kingdom.
Peter W G TennantLeeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.

Funding

Chief Scientist Office SPHSU20Medical Research Council MC_UU_00022/5
6 · The paper itself

Abstract

backgroundDuring the first wave of the COVID-19 pandemic, the United Kingdom experienced one of the highest per-capita death tolls worldwide. It is debated whether this may partly be explained by the relatively late initiation of voluntary social distancing and mandatory lockdown measures. In this study, we used simulations to estimate the number of cases and deaths that would have occurred in England by 1 June 2020 if these interventions had been implemented one or two weeks earlier, and the impact on the required duration of lockdown.

methodsUsing official reported data on the number of Pillar 1 lab-confirmed cases of COVID-19 and associated deaths occurring in England from 3 March to 1 June, we modelled: the natural (i.e. observed) growth of cases, and the counterfactual (i.e. hypothetical) growth of cases that would have occurred had measures been implemented one or two weeks earlier. Under each counterfactual condition, we estimated the expected number of deaths and the time required to reach the incidence observed under natural growth on 1 June.

resultsIntroducing measures one week earlier would have reduced by 74% the number of confirmed COVID-19 cases in England by 1 June, resulting in approximately 21,000 fewer hospital deaths and 34,000 fewer total deaths; the required time spent in full lockdown could also have been halved, from 69 to 35 days. Acting two weeks earlier would have reduced cases by 93%, resulting in between 26,000 and 43,000 fewer deaths.

conclusionsOur modelling supports the claim that the relatively late introduction of social distancing and lockdown measures likely increased the scale, severity, and duration of the first wave of COVID-19 in England. Our results highlight the importance of acting swiftly to minimise the spread of an infectious disease when case numbers are increasing exponentially.

Indexed as

COVID-19Communicable Disease ControlEnglandHumansPandemicsSARS-CoV-2

Identifiers

PMID35421094
PMCPMC9009677

What OpenQuestion holds

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LicenceCC BY
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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.