Evidence map›Paper›PMID 34837679›Full record

ArticleCell journal2021

Global Scientific Research on SARS-CoV-2 Vaccines: A Bibliometric Analysis.

Fakher Rahim, Aida Khakimova, Ammar Ebrahimi, Oleg Zolotarev, Fatemeh Rafiei Nasab

Open access · greenAbstract read
In one paragraph

Article in Cell journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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 at 3 institutions in 2 countries.

Fakher RahimThalassemia and Hemoglobinopathy Research Centre, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Aida KhakimovaDepartment of Development of Scientific and Innovation Activities, Russian New University, Moscow, Russia. Email: aida_khatif@mail.ru.
Ammar EbrahimiDepartment of Medical Biotechnology, School of Paramedicine, Guilan University of Medical Sciences, Rasht, Iran.
Oleg ZolotarevDepartment of Information Systems in Economics and Management, Russian New University, Moscow, Russia.
Fatemeh Rafiei NasabDepartment of Scientometrics, Deputy of Research and Technology Affairs, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Ahvaz Jundishapur University of Medical Sciences · IRGuilan University of Medical Sciences · IRRussian New University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe performed this bibliometric analysis to identify global scientific research on the SARS-CoV-2 vaccines. MATERIALS AND

methodsThis bibliometric analysis study inclusive search of English-language publications related to the SARS-CoV-2 vaccines was conducted in the Scopus, PubMed, and Dimensions databases without year limitations. The results of bibliometric analysis comprised a time-dependent citation density trend, the name of the journal, journal impact factor (IF), year of publication, type of article, category, subscription or affiliation, co-authorship, and cooccurrence network.

resultsA study of the scientific literature from three databases (Scopus, PubMed, Dimensions) shows that investigators have focused more on studying the structure of the coronavirus at different levels (organismic, cellular, and molecular). In addition, the method of virus penetration into the cell and features of the influence of coronavirus on animals are well-studied. Various methods and strategies are being used to develop the vaccines, including both animal-tested methods and computer models. The Dimensions database is the most representative in terms of coverage of research on development of the SARS-CoV-2 vaccines.

conclusionThis research is a scientific investigation based on bibliometric analysis of papers related to the SARS-CoV-2 vaccines. The Dimensions database provides the most representative research coverage on the creation of a vaccine against coronavirus. It is characterized by a large number of formed verbose terms (length of more than four words) related to coronavirus, which makes it possible to track trends in the development of methods for creating a vaccine.

Indexed as

Bibliometric AnalysisCOVID-19/SARS-CoV-2Vaccine

Identifiers

PMID34837679
PMCPMC8588811
OpenAlexW3211464644

What OpenQuestion 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 OpenQuestion graph.