Bibliometric analysis of researches on traditional Chinese medicine for coronavirus disease 2019 (COVID-19)

Abstract

Background: The coronavirus disease 2019 (COVID-19) has caused a worldwide pandemic, and traditional Chinese medicine (TCM) has played an important role in response. We aimed to analyze the published literature on TCM for COVID-19, and provide reference for later research. Methods: This study searched the CBM, CNKI, PubMed, and EMBASE from its establishment to March 11, 2020. VOSviewer 1.6.11 and gCLUTO 2.0 software were used to visually analyze the included studies. Results: A total of 309 studies were included, including 61 journals, 1441 authors, 277 institutions, and 27 provinces. Research collaborations among regions were among those close in geographical distance. The collaborations of institutions and authors were more likely to be restricted to the same region. Among the authors with frequency greater than two (65 authors), only 19 authors had connection with others. More than 70% (358/491) of keywords were only presented once, and 20 keywords were shown more than 10 times. Five research topics were identified: Data mining method based analysis on the medication law of Chinese medicine in prevention and management of COVID-19; exploration of active compounds of Chinese medicine for COVID-19 treatment based on network pharmacology and molecular docking; expert consensus and interpretation of COVID-19 treatment; research on the etiology and pathogenesis of COVID-19; and clinical research of TCM for COVID-19 treatment. Conclusion: The research hotspots were scattered, and the collaboration between authors and institutions needed to be further strengthened. To improve the quality and efficiency of research output, the integration of scientific research and resources, as well as scientific collaboration are needed.

Keywords

• COVID-19
• Traditional Chinese medicine
• Bibliometrics
• Visual analysis