Evidence map›Paper›PMID 37183072›Full record

ArticleVaccine2023

Development of a Choice-framework for Covid vaccines in India using a multi-criteria decision analysis approach.

Tarun K George, Nayana P Nair, Awnish Kumar Singh, A Dilesh Kumar, Arup Deb Roy, Varshini Neethi Mohan, Gagandeep Kang

Open access · hybridAbstract read
In one paragraph

Article in Vaccine, 2023. 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
0.6field-weighted citation impact, top 17% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  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

7 authors at 4 institutions in 2 countries.

Tarun K GeorgeDepartment of General Medicine, Christian Medical College, Vellore, Tamil Nadu 632002, India. Electronic address: tarunkg@cmcvellore.ac.in.
Nayana P NairWellcome Trust Laboratories, Department of GI Sciences, Christian Medical College, Vellore, Tamil Nadu 632002, India. Electronic address: nayanapnair.chinnu@gmail.com.
Awnish Kumar SinghNTAGI Secretariat, NIHFW, MoHFW, India. Electronic address: awnish.singh@nihfw.org.
A Dilesh KumarWellcome Trust Laboratories, Department of GI Sciences, Christian Medical College, Vellore, Tamil Nadu 632002, India. Electronic address: dilesh.kumara@cmcvellore.ac.in.
Arup Deb RoyJohn Snow India, New Delhi 110070, India. Electronic address: arup_debroy@in.jsi.com.
Varshini Neethi MohanIndian Institute of Technology, Madras, Chennai, Tamil Nadu 6000036, India. Electronic address: varshinim@gmail.com.
Gagandeep KangWellcome Trust Laboratories, Department of GI Sciences, Christian Medical College, Vellore, Tamil Nadu 632002, India. Electronic address: gkang@cmcvellore.ac.in.
Christian Medical College, Vellore · INIndian Institute of Technology Madras · INJohn Snow (United States) · USWWF-India · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVaccines were crucial in controlling the Covid-19 pandemic. As more vaccines receive regulatory approval, stakeholders will be faced with several options and must make an appropriate choice for themselves. We proposed a multi-criteria decision analysis (MCDA) framework to guide decision-makers in comparing vaccines for the Indian context.

methodsWe adhered to the ISPOR guidance for the MCDA process. Seven vaccine options were compared under ten criteria. Through three virtual workshops, we obtained opinions and weights from citizens, private-sector hospitals, and public health organisations. Available evidence was rescaled and incorporated into the performance matrix. The final score for each vaccine was calculated for the different groups. We performed different sensitivity analyses to assess the consistency of the rank list.

resultsThe cost, efficacy and operational score of the vaccines had the highest weights among the stakeholders. From the six scenario groups, Janssen had the highest score in four. This was driven by the advantage of having a single dose of vaccination. In the probabilistic sensitivity analysis for the overall group, Covaxin, Janssen, and Sputnik were the first three options. The participants expressed that availability, WHO approvals and safety, among others, would be crucial when considering vaccines.

conclusionsThe MCDA process has not been capitalised on in healthcare decision-making in India and LMICs. Considering the available data and stakeholder preference at the time of the study, Covaxin, Janssen, and Sputnik were preferred options. The choice framework with the dynamic performance matrix is a valuable tool that could be adapted to different population groups and extended based on increasing vaccine options and emerging evidence. *ISPOR - The Professional Society for Health Economics and Outcomes Research.

Indexed as

COVID-19VaccinesCOVID-19 VaccinesDecision MakingDecision Support TechniquesHumansPandemicsVaccines, InactivatedBBV152 COVID-19 vaccineCOVID-19 VaccinesVaccinesVaccines, InactivatedCovid-19Decision makingHealthcareIndiaMCDAMulticriteria decision analysisVaccines

Identifiers

PMID37183072
PMCPMC10179113
OpenAlexW4376640954

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.