COVID-19 research progress: Bibliometrics and visualization analysis

Background: Coronavirus primarily targets the human respiratory system, COVID-19 (Coronavirus disease 2019) triggered in China in the late 2019. In March 2020, WHO announced the COVID-19 pandemic. This study aims to analyze and visualize the scientific structure of the COVID-19 publications using co-citation and co-authorship. Methods: This is a scientometric study. Web of Science Core Collection (WoSCC) was searched for all documents regarding COVID-19, MERS-Cov, and SARS-Cov from the beginning to 2020. An Excel spreadsheet was applied to gather and analyze the data and the CiteSpace was used to visualize and analyze the data. Results: A total of 5159 records were retrieved in WoSCC. The structure of the network indicated that the network mean silhouette was low (0.1444), implying that the network clusters� identity is not identifiable with high confidence. The network modularity was 0.7309. The cluster analysis of the co-citation network on documents from 2003 to 2020 provided 188 clusters. The largest cluster entitled, �the Middle East respiratory syndrome coronavirus� had 255 nodes. The coauthorship network illustrated that the most prolific countries, USA, China, and Saudi Arabia, have focused on a specific field and have formed separate clusters. Conclusion: The present study identified the important topics of research in the field of COVID-19 based on co-citation networks as well as the analysis of clusters of countries' collaborations. Despite the similarities in the production behavior in prolific countries, their thematic focus varies so that a country like China plays a role in �Quantitative Detection� cluster, while USA is the leading country in the �Biological Evaluation� cluster. © 2021. Iran University of Medical Science