Evidence map›Paper›PMID 33039678›Full record

ArticlePublic health2020

A simple tool for comparing benefits and 'costs' of COVID-19 exit strategies.

John Frank, Andrew J Williams

Abstract read
In one paragraph

Article in Public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

John FrankUsher Institute, University of Edinburgh, UK. Electronic address: john.frank@ed.ac.uk.
Andrew J WilliamsSchool of Medicine, University of St Andrews, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGovernments and health policymakers are now looking for strategies to lift the COVID-19 lockdown, while reducing risk to the public.

methodsWe propose the population attributable risk (PAR) as an established epidemiological tool that could support decision-making through quickly estimating the main benefits and costs of various exit strategies.

resultsWe demonstrate the feasibility of use of PAR using pandemic data, that were publicly available in mid-May 2020 from Scotland and the US, to estimate the proportion of COVID-19 hospital admissions which might be avoided, and the proportion of adverse labour market effects - for various scenarios - based on maintaining the lockdown for those of certain ages with and without comorbidities.

conclusionThese calculations could be refined and applied in different countries to inform important COVID-19 policy decisions, using routinely collected data.

Indexed as

Public PolicyAdultAgedCoronavirus InfectionsCOVID-19EmploymentFeasibility StudiesHospitalizationHumansMiddle AgedPandemicsPneumonia, ViralQuarantineRisk AssessmentScotlandUnited StatesCOVID-19Lockdown exit strategyPopulation attributable riskRisk-benefit analysis

Identifiers

PMID33039678
PMCPMC7831639

What OpenQuestion holds

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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.