Bibliometric Analysis of Pfizer-BioNTech (BNT162B2): A COVID-19 Vaccine

被引:1
作者
Hassan, Waseem [1 ]
Ara, Amina [1 ]
机构
[1] Univ Peshawar, Inst Chem Sci, Peshawar 25120, Khyber Pakhtunk, Pakistan
关键词
Bibliometric analysis; COVID-19; Pfizer Vaccine; INDEX;
D O I
10.22207/JPAM.15.3.11
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The objective of the study was to perform a bibliometric analysis of the Pfizer-BioNTech vaccine. For this purpose Scopus database was used. As of 13th May 2021, one hundred and seventy-three (n=173) research documents are published about it. We used Vosviewer and Biblioshiny (Bibliometrix) in the present report. In all publications, 1160 authors have significantly contributed. The documents per author was 0.119, while authors per document was 8.41. Collaborative Index (CI) was found to be 9.47. By biblioshiny we also applied Lotka's law to depict the author's frequency. 1097 authors were involved in only one (n=1) publication. Based on the Scopus record, the highest documents are published by Dormitzer, P.R. (n=6). In universities and countries categories, Tel Aviv University (n=7) and USA (48) are the most productive. By Vosviewer the collaboration pattern among authors, institutes, and countries is graphically presented. For example, 28 authors, 17 departments and 7 countries directly contributed to one publication. The research documents (133) are published in 102 sources or journals. The highest documents are published in Vaccines (n=8), while the highest citations were recorded for the New England Journal of Medicine (n=838). We also applied co-words analysis to understand the main focus of these publications.
引用
收藏
页码:1211 / 1229
页数:19
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