Evidence map›Paper›PMID 34183915›Full record

ReviewIranian journal of public health2021

A 50-Year Overview of the Coronavirus Family with Science Mapping Techniques: A Review.

Ayhan Tabur, Ali Arslanoğlu

Abstract readReview
In one paragraph

Review in Iranian journal of public health, 2021. 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. Bibliometric Analysis of Global Scientific Production on COVID-19 and Vaccines.International journal of environmental research and public health · 2023
    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

2 authors.

Ayhan TaburEmergency Medical Specialist, SBÜ Diyarbakır Gazi Yaşargil Eğt.ve Araş.Hst., Diyarbakır, Turkey.
Ali ArslanoğluDepartment of Health Management, Faculty of Health Sciences, University of Health Sciences, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic from the coronavirus family is the most important agenda of today's world, also called the "New World". In this outbreak period, declared a pandemic by WHO and affected the whole world and humanity on a global scale, all kinds of scientific information and evidence-based sharing on the subject gained great importance.

methodsOverall, 12,301 articles from the web of Science (WOS) Core Collection database were analyzed using SciMAT software, conducted to examine the development of coronavirus publications in the process and to reveal the scientific mapping related to the subject. To analyze the development in the process based on periods, the articles covering the 50 years were compared as five periods of 10 years.

resultsThe most publications with the Coronavirus theme were made between 2010 and 2020 (n=1020), the total number of citations of these articles was 15,966 and the h-index value was 54. The theme "Coronavirus" was associated with the themes "infection" (w=0.04), "SARS" (w=0.03), "virus" (w=0.04), "identification" (w=0.05) and "swine" (w=0.03). Due to the recent emergence of the COVID-19 theme, it was found to be directly related to the "outbreak" theme (w=0.01). In terms of the distribution of the articles on coronavirus by country, most articles were published by the USA. This country is followed by China, Germany, England and the Netherlands.

conclusionThis research on the coronavirus family can offer a holistic view of the virus family in the scientific world and can make a scientific contribution to the fight against the virus by creating awareness on this issue.

Indexed as

CoronavirusCOVID-19PandemicScience mappingScimat

Identifiers

PMID34183915
PMCPMC8219623

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.