Evidence map›Paper›PMID 37905961›Full record

ArticleHuman vaccines & immunotherapeutics2023

Construction of an indicator framework for vaccine inclusion in public health programs: A Delphi-entropy method study.

Qing Wang, Peixi Dai, Mengmeng Jia, Mingyue Jiang, Juan Li, Weizhong Yang, Luzhao Feng

Open access · goldAbstract read
In one paragraph

Article in Human vaccines & immunotherapeutics, 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
–field-weighted citation impact, top 80% 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, 0 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 3 institutions in 2 countries.

Qing WangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0002-9855-4348
Peixi DaiDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.ORCID 0000-0001-5555-8026
Mengmeng JiaSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0002-8175-7181
Mingyue JiangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0009-0000-3176-6066
Juan LiBeijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China.
Weizhong YangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0002-6599-825X
Luzhao FengSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0002-5206-5995
Chinese Academy of Medical Sciences & Peking Union Medical College · CNBeijing Center for Disease Prevention and Control · CNChinese Center For Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Governments must decide which vaccine priority to include in their public health programs. Using the modified Delphi and entropy method, we developed an indicator framework for vaccine inclusion at the national, provincial, municipal, and district/county levels, each containing three dimensions. In total, 4 primary indicators, 17 secondary indicators, and 45 tertiary indicators were selected, covering vaccine-preventable diseases, candidate vaccines, and social drivers of the supply and demand sides. From a subjective perspective, there was no significant weighting difference in the primary and secondary indicators at all administrative levels. "Vaccine-preventable diseases" as a primary indicator had the greatest weight in the peer group, of which "Health burden" had the highest weight among the secondary indicators. From the objective perspective, the social drivers on the supply and demand sides of the primary indicators accounted for 65% and higher. Among the secondary indicators, "the characteristics of the candidate vaccine" and "vaccine-related policies on the supply side" held 8% of weights or more at both national and provincial levels. "Demographic characteristics" held the highest weight at the municipal (13.50) and district/county (15.45) level. This study indicates that China needs different considerations when using WHO-recommended vaccines at the national, provincial, municipal, and district/county levels. In addition, this study highlights that behavioral and social drivers are important indicators that need to be considered for decision-making. This framework provides a tool for policymakers to determine the inclusion priority of candidate vaccines.

Indexed as

Public HealthVaccinesChinaEntropyImmunization ProgramsVaccinesbehavioral and social driversExpanded program on immunizationpublic health programroutine immunization programvaccines

Identifiers

PMID37905961
PMCPMC10760382
OpenAlexW4388033740

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.