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?:abstract
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BACKGROUND: The COVID-19 pandemic has spread with alarming speed and an effective treatment for the disease is still lacking. The body of evidence on COVID-19 increases at an impressive pace, calling for a method to rapidly assess the current knowledge and identify key information. Gold standard methods, such as systematic reviews and meta-analyses are unsuitable due to their narrow scope and high time-consumption. OBJECTIVE: To explore the published scientific literature on COVID-19 and map the research evolution during the early phase of the COVID-19 pandemic. METHODS: We analyzed the titles, keywords, and abstracts of articles on COVID-19 from PubMed. We used latent Dirichlet allocation modeling to extract topics and conducted trend analysis to explore the temporal changes of research for each topic, journal impact factor (JIF), and geographical origin. RESULTS: Our search identified 16 670 relevant articles dated between February 14, 2020, and June 1, 2020. Of these articles, six were reports from peer-reviewed randomized trials on COVID-19 patients. We identified 14 main research topics. The most common topics were healthcare response, and clinical manifestations with 2 812/16 670 (16.9%) and 1 828/16 670 (11.0%) publications, respectively. We found a growing trend of publications on clinical manifestations, and protective measures, and a decrease in research on disease transmission, epidemiology, healthcare response, and radiology. Publications on protective measures, immunology, and clinical manifestations were associated with the highest JIF. We calculated an overall median JIF of 3.7 (IQR 2.6-5.9) and found that the publications\' JIF declined over time. The top countries of research origin were the USA, China, Italy, and the UK. CONCLUSIONS: In less than six months since the detection of the novel coronavirus, a remarkably high number of articles on COVID-19 have been published. We present the temporal changes of the available COVID-19 research during the early phase of the pandemic. Our findings may aid researchers and policy makers to form a structured view of the current COVID-19 evidence base and provide further research directions.
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