Evidence map›Paper›PMID 36292397›Full record

ArticleHealthcare (Basel, Switzerland)2022

An International Federal Hyperledger Fabric Verification Framework for Digital COVID-19 Vaccine Passport.

Dong-Her Shih, Pai-Ling Shih, Ting-Wei Wu, Shu-Huai Liang, Ming-Hung Shih

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. 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. Review
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

5 authors.

Dong-Her ShihDepartment of Information Management, National Yunlin University of Science and Technology, Douliu 64002, Taiwan.ORCID 0000-0003-1605-8488
Pai-Ling ShihDepartment of Information Management, National Chung Cheng University, Chiayi 621301, Taiwan.
Ting-Wei WuDepartment of Information Management, National Yunlin University of Science and Technology, Douliu 64002, Taiwan.
Shu-Huai LiangDepartment of Information Management, National Yunlin University of Science and Technology, Douliu 64002, Taiwan.
Ming-Hung ShihDepartment of Electrical and Computer Engineering, Iowa State University, 2520 Osborn Drive, Ames, IA 50011, USA.

Funding

Taiwan Ministry of Science and Technology MOST 111-2410-H-224-006
6 · The paper itself

Abstract

The COVID-19 virus has been spreading worldwide on a large scale since 2019, and the most effective way to prevent COVID-19 is to vaccinate. In order to prove that vaccination has been administered to allow access to different areas, paper vaccine passports are produced. However, paper vaccine passport records are vulnerable to counterfeiting or abuse. Previous research has suggested that issuing certificates digitally is an easier way to verify them. This study used the consortium blockchain based on Hyperledger Fabric to upload the digital vaccine passport (DVP) to the blockchain network. In order to enable collaboration across multiple systems, networks, and organizations in different trust realms. Federated Identity Management is considered a promising approach to facilitate secure resource sharing between collaborating partners. Therefore, the international federal identity management architecture proposed in this study enables inspectors in any country to verify the authenticity of the DVP of incoming passengers using the consortium blockchain. Through practical construction, the international federal Hyperledger verification framework for the DVP proposed in this study has shown the feasibility of issuing a global DVP in safety analysis and efficacy testing.

Indexed as

blockchainCOVID-19digital vaccine passport (DVP)federated identity managementHyperledger Fabric

Identifiers

PMID36292397
PMCPMC9601543

What OpenQuestion holds

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LicenceCC BY
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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.