Evidence map›Paper›PMID 36523237›Full record

ArticleBMJ open2022

How missing evidence-based medicine indicators can inform COVID-19 vaccine distribution policies: a scoping review and calculation of indicators from data in randomised controlled trials.

Andrew Larkin, Howard Waitzkin, Ella Fassler, Kesavan Rajasekharan Nayar

Open access · goldAbstract readScoping Review
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 3 institutions in 3 countries.

Andrew LarkinAllende Program in Social Medicine, Albuquerque, New Mexico, USA.ORCID 0000-0003-2214-0031
Howard WaitzkinAllende Program in Social Medicine, Albuquerque, New Mexico, USA waitzkin@unm.edu.ORCID 0000-0001-5084-6117
Ella FasslerAllende Program in Social Medicine, Albuquerque, New Mexico, USA.ORCID 0000-0001-5299-536X
Kesavan Rajasekharan NayarSanthigiri Research Foundation, Thiruvananthapuram, Kerala, India.ORCID 0000-0003-4203-1959
Centro Universitario Allende · MXInstitute of Public Health Bengaluru · INUniversity of New Mexico · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveReports of efficacy, effectiveness and harms of COVID-19 vaccines have not used key indicators from evidence-based medicine (EBM) that can inform policies about vaccine distribution. This study aims to clarify EBM indicators that consider baseline risks when assessing vaccines' benefits versus harms: absolute risk reduction (ARR) and number needed to be vaccinated (NNV), versus absolute risk of the intervention (ARI) and number needed to harm (NNH).

methodsWe used a multimethod approach, including a scoping review of the literature; calculation of risk reductions and harms from data concerning five major vaccines; analysis of risk reductions in population subgroups with varying baseline risks; and comparisons with prior vaccines.

findingsThe scoping review showed few reports regarding ARR, NNV, ARI and NNH; comparisons of benefits versus harms using these EBM methods; or analyses of varying baseline risks. Calculated ARRs for symptomatic infection and hospitalisation were approximately 1% and 0.1%, respectively, as compared with relative risk reduction of 50%-95% and 58%-100%. NNV to prevent one symptomatic infection and one hospitalisation was in the range of 80-500 and 500-4000. Based on available data, ARI and NNH as measures of harm were difficult to calculate, and the balance between benefits and harms using EBM measures remained uncertain. The effectiveness of COVID-19 vaccines as measured by ARR and NNV was substantially higher in population subgroups with high versus low baseline risks.

conclusionsPriorities for vaccine distribution should target subpopulations with higher baseline risks. Similar analyses using ARR/NNV and ARI/NNH would strengthen evaluations of vaccines' benefits versus harms. An EBM perspective on vaccine distribution that emphasises baseline risks becomes especially important as the world's population continues to face major barriers to vaccine access-sometimes termed 'vaccine apartheid'.

Indexed as

COVID-19COVID-19 VaccinesEvidence-Based MedicineHospitalizationHumansPolicyRandomized Controlled Trials as TopicCOVID-19 VaccinesCOVID-19health policypublic health

Identifiers

PMID36523237
PMCPMC9748517
OpenAlexW4311409578

What OpenQuestion holds

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LicenceCC BY-NC
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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.