Evidence map›Paper›PMID 36851173›Full record

ArticleVaccines2023

A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19).

Dequan Zeng, Jie Wang, Bin Xiao, Hao Zhang, Xingming Ma

Abstract read
In one paragraph

Article in Vaccines, 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
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

5 authors.

Dequan ZengSchool of Health Management, Xihua University, Chengdu 610039, China.
Jie WangSchool of Food and Biological Engineering, Xihua University, Chengdu 610039, China.
Bin XiaoSchool of Food and Biological Engineering, Xihua University, Chengdu 610039, China.
Hao ZhangDepartment of Nuclear Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong 637199, China.
Xingming MaSchool of Health Management, Xihua University, Chengdu 610039, China.ORCID 0000-0002-1860-4764

Funding

Natural Science Foundation of Sichuan Province 2022NSFSC1587Project for Excellent Talents in Xihua University 202026
6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19), beginning in December 2019, has spread worldwide, leading to the death of millions. Owing to the absence of definitive treatment, vaccination against COVID-19 emerged as an effective strategy against the spread of the pandemic. Acceptance of the COVID-19 vaccine has advanced considerably, and vaccine-related research has significantly increased over the past three years. This study aimed to evaluate the content and external characteristics of COVID-19 vaccine-related literature for tracking research trends related to the global COVID-19 vaccine with the means of bibliometrics and visualization maps. A total of 18,285 records in 3499 journals were retrieved in the Web of Science Core Collection database and included in the final analysis. China was the first to focus on COVID-19 vaccine research, while European and American countries started late but developed rapidly. The USA and the UK are the top contributors to COVID-19 vaccine development, with the largest number of publications. The University of Washington and Harvard Medical School were the leading institutions, while Krammer, F. from Icahn School of Medicine at Mount Sinai was the author most active and influential to the topic.

Indexed as

bibliometricsCitespaceCOVID-19SARS-CoV-2vaccineVOSviewer

Identifiers

PMID36851173
PMCPMC9959778

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.