The emerging COVID-19 research: dynamic and regularly updated science maps and analyses
Methods - Two bibliometric methods were employed, the first is a keyword co-occurrence analysis, based on published work available from PubMed. The second is a bibliometric coupling analysis, based on articles available through Scopus. The results are presented as clustered network graphs; available as interactive network graphs through the webpage.
Results - For research as of March 23rd, keyword co-occurrence analysis showed that research was organized in 4 topic clusters: “Health and pandemic management”, “The disease and its pathophysiology”, “Clinical epidemiology of the disease” and “Treatment of the disease”. Coupling analyses resulted in 4 clusters on literature that relates to “Overview of the new virus”, “Clinical medicine”, “On the virus” and “Reproduction rate and spread”.
Conclusion - We introduced a dynamic resource that will give a wide readership an overview of how the structure of the COVID-19 literature is developing. To illustrate what this can look like, we showed the structure as it stands three months after the virus was identified; the structure is likely to change as we progress to later stages of this pandemic.