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BACKGROUND: With an ever growing and expanding body of literature on the newly developed vaccines against the COVID-19, there is an urgent need for a comprehensive analysis of the current state of research on vaccine effectiveness (VE). This study conducted a comprehensive bibliometric analysis to critically examine the productivity and impact of retrieved publications on COVID-19 VE and to predict the future directions of research in the field. METHODS: The global literature on COVID-19 VE from 2021 to 2024 was extracted from the VIEW-hub website. Using bibliometric analysis tools, specifically Microsoft Excel, the R package "bibliometrix, biblioshiny" and VOSviewer, we analyzed publications for trends in productivity, citations, and global collaboration. Key metrics assessed include publication and citation trends, influential authors, collaborative networks, and thematic evolution, offering a comprehensive view of the research landscape on COVID-19 VE. RESULTS: A total of 490 publications were authored by 5031 authors from 934 institutions and 78 countries and published in 119 journals. Most retrieved publications were original articles (99.6 %). The United States was the most productive country with 205 publications (41.8 %). Global research collaborations were mainly within developed countries. Analysis of the thematic evolution of the field illustrated changing research focus over three distinct time clusters. Throughout 2021, studies were focused on outlining infection prevention and control measures, as well as examining the efficacy of novel mRNA vaccines. In 2022, the linchpin of research was shifted towards dissecting the epidemiological correlates of the pandemic in light of the widespread use of vaccines. The final cluster showed special emphasis on the new variants of COVID-19 and the long-term outcomes of vaccines. CONCLUSION: Our study identified geopolitical disparities and weak engagement from developing countries in the ongoing efforts regarding COVID-19 VE. This study can inform researchers, policymakers, and funding agencies as they assess ongoing research and future directions in COVID-19 VE.
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Stored only when both papers are in the corpus — 10 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.