ReviewFrontiers in public health2021
Bibliometric Analysis of International Scientific Production on Pharmacologic Treatments for SARS-CoV-2/COVID-19 During 2020.
Review in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- SARS-CoV-2 and reproductive system: a scientometric study.Frontiers in reproductive health · 2026Article
- Long COVID Research, 2020-2024: A PubMed-Based Bibliometric Analysis.Healthcare (Basel, Switzerland) · 2025Review
- How does post COVID differ from other post-viral conditions in childhood and adolescence (0-20 years old)? A systematic review.EClinicalMedicine · 2024Article
- A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19).Vaccines · 2023Article
- Bibliometric analysis of tumor necrosis factor in post-stroke neuroinflammation from 2003 to 2021.Frontiers in immunology · 2022Article
- Global Scientific Overview of Dermatology Related to COVID-19: A Bibliometric Analysis.Indian journal of dermatologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: COVID-19 is causing a grave global health and economic crisis and the fight against the pandemic has led to unprecedented scientific activity. Bibliometrics could be a useful tool for guiding future researches lines and promoting international collaboration for an effective treatment. For this purpose, we have conducted a bibliometric analysis of scientific publications on drugs and therapies used to treat COVID-19 during 2020. Methods: Data source: Web of Science. We gathered data on scientific production relating to drugs used to treat COVID-19. We calculated impact factors and analyzed production by institution, country, and journal, visualizing our results in bibliometric networks. Results: In 1 year, production relating to COVID-19 exceeded 100 000 publications, with over 6,500 on Drugs and COVID-19. Research into hydroxychloroquine and chloroquine, remdesivir, lopinavir and ritonavir, tocilizumab and convalescent plasma is particularly noteworthy. Mean citations/study range from 11.9 to 15.4. Producer institutions fall into three groups: one in the US and centered on Harvard Medical School; another in Europe led by INSERS; and another in China led by Huazhong University of Science and Technology. Production by journal is widespread but the Conclusions: The volume of research that is currently under way is comparable to the magnitude of the pandemic itself. Such a high volume of studies is infrequent and the impact they have achieved has no known precedent. The producing countries are those with highest incidence of the pandemic and greatest scientific potential; moreover, inter-agency and international collaboration has reached extraordinarily high levels.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.