ReviewGMS hygiene and infection control2023
COVID-19 research in South Asia: a bibliometric analysis of the 100 most-cited articles.
Review in GMS hygiene and infection control, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Post-operative infections after cardiothoracic surgery and vascular procedures: a bibliometric and visual analysis of the 100 most-cited articles in the past 2 decades.GMS hygiene and infection control · 2024Review
- Bibliometric analysis of publication trends on ocular hygiene and infections in the past two decades.GMS hygiene and infection control · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: With the surge in the number of infected individuals during the COVID-19 pandemic, there was also a surge observed in the number of publications discussing its epidemiology, characteristics, path-o-phys-i-ol-o-gy, diagnosis, prevention and treatment. This bibliometric analysis focuses on the papers published on COVID-19 in South Asia. Methods: We searched articles in the Scopus database from December 2019 to October, 2022. After manual screening, a list of the 100 most-cited articles was obtained, which was analyzed for various factors, including the type of article, citation count, author's affiliation, country of origin, funding bodies, etc. Results: The majority of the top 100 articles (n=79) in South Asia were published during 2020. India was affiliated with the highest number of articles (n=68), followed by Bangladesh (n=18) and Pakistan (n=12). However, 7 articles were authored by a researcher in Bangladesh. Female authors were under represented (32.38%), with no female author in lists of authors with 4 or more articles. The average number of citations for each of the top 100 most-cited articles was 180.8. Original articles constituted the major portion of the publications (82%), followed by letters (11%) and reviews (4%). Half of the publications belonged to the field of medicine (n=49), while others were contributed by science, psychology, social sciences, and biochemistry and allied sciences (n=8). Vaccine trials were under-represented. Jahangirnagar University, Bangladesh was affiliated with the maximum number of articles. Most articles were published in Science of The Total Environment (n=8) while Indian Council of Medical Research (n=4) was the top funding body. Conclusion: These findings highlight that South Asia has a great potential to conduct research addressing its challenging health problems. But lack of funds hinders conducting trials of new medications and vaccines. Thus, there is need for allocation of sufficient funds for research and clinical trials by governments and the private sector to enhance the research productivity of this region.
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.