ArticleTropical diseases, travel medicine and vaccines2019
A bibliometric analysis of human strongyloidiasis research (1968 to 2017).
Article in Tropical diseases, travel medicine and vaccines, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 16 citations in OpenAlex.
- Bibliometric Analysis of Research on Traditional Chinese Exercise and Osteoarthritis.Journal of pain research · 2024Article
- Global research activity on antimicrobial resistance in food-producing animals.Archives of public health = Archives belges de sante publique · 2021Article
- Publication Trends in Neglected Tropical Diseases of Latin America and the Caribbean: A Bibliometric Analysis.Pathogens (Basel, Switzerland) · 2021Article
- Bibliometric analysis of peer-reviewed literature on antimicrobial stewardship from 1990 to 2019.Globalization and health · 2021Article
- 30 years of parasitology research analysed by text mining.Parasitology · 2020Article
- Bibliometric analysis of global scientific literature on vaccine hesitancy in peer-reviewed journals (1990-2019).BMC public health · 2020Article
- Bibliometric analysis of peer-reviewed literature on climate change and human health with an emphasis on infectious diseases.Globalization and health · 2020Review
- Bibliometric analysis of global research output on antimicrobial resistance in the environment (2000-2019).Global health research and policy · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStrongyloidiasis is a neglected tropical disease (NTD). It is commonly associated with poverty and poor hygiene. Strongyloidiasis poses an unseen global public health problem. The aim of this study was to assess and analyze peer-reviewed literature on human strongyloidiasis to shed light on the evolution, volume, important topics, and key players in the field of human strongyloidiasis.
methodsA validated bibliometric method was implemented using Scopus database for the study period from 1968 to 2017. The search strategy was developed based on keywords related to strongyloidiasis. Bibliometric indicators and visualization maps were presented.
resultsIn total, 1947 documents were found. Retrieved documents received 32,382 citations, an average of approximately 16.6 per document, and an
conclusionThe volume, growth, and international research collaboration in human strongyloidiasis were inadequate given the long history of the disease, the large number of affected people, and the results obtained for other NTDs. Research in human strongyloidiasis needs to be strengthened and encouraged in endemic regions in Southeast Asia and Latin America. International research networking needs to be established to achieve the goals of Sustainable Development Goals in fighting and eradicating NTDs by 2030.
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.