A Bibliometric Analysis Using Vosviewer of Publications on Covid-19 Vaccines

Abstract

In late December 2019, an unknown pneumonia was identified in Wuhan, China, which a few days later introduced the novel coronavirus as the cause of this unexplained pneumonia. It spread rapidly, resulting in a global pandemic. By the end of 2020, several vaccines had become available in different parts of the world. This pandemic has caused publishing number of vaccine-related researches. Therefore, a bibliometric analysis of these publications may provide guidance for future research hot and trend topics and help researchers gain comprehensive information about COVID-19 vaccines and research on COVID-19 vaccines with a more comprehensive view.The global literatures about COVID-19 vaccine without time limitation were scanned in the Web of Science collection database. COVID-19 vaccine was used as the keyword to search the relevant publications. VOS viewer was applied to perform the bibliometric analysis of these articles.ResultsTotally 8,782 publications on the topic of COVID-19 Vaccine were identified and COVID-19 with a total link strength of 12197 appeared as the most frequent keyword, which had a strong link to SARS-COV-2, coronavirus and Vaccine. The highestranking journal was Vaccines with 254 publications and the most cited journal was Nature with 7010 citation counts. 20 articles written by Florian Krammer have been cited for 2117 times and 81 articles from University of North Carolina have been cited for 4,590 times which are the most cited author and organization. The main partners of USA are England, China and India. The published literatures have focused on these areas: immunology, medicine general internal, medicine research public environmental occupational health and experimental, pharmacology pharmacy. The current growth trends predict a large increase in the number of global publications on COVID-19 Vaccine. USA made the most outstanding contribution within this important field. The main limitation of this study was the repetition of some keywords when analyzing the data, which should be integrated before analyzing these keywords. Pandemic, vaccine hesitancy, public health, spike protein and treatment may be hotspots in the future.