Evidence map›Paper›PMID 39227968›Full record

ArticleJournal of translational medicine2024

Trends and insights in dengue virus research globally: a bibliometric analysis (1995-2023).

Yumeng Liu, MengMeng Wang, Ning Yu, Wenxin Zhao, Peng Wang, He Zhang, Wenchao Sun, Ningyi Jin, Huijun Lu

Abstract read
In one paragraph

Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Review
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  9. Review
  10. Resistance status ofNarra J · 2025
    Review
  11. Mapping the Global Landscape of Dengue Fever Research: A Scientometric Analysis.Interdisciplinary perspectives on infectious diseases · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yumeng LiuCollege of Animal Science and Technology, Guangxi University, Nanning, China. yumengliu0909@163.com.ORCID 0000-0002-3124-0627
MengMeng WangChangchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China.
Ning YuChangchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China.
Wenxin ZhaoChangchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China.
Peng WangChangchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China.
He ZhangChangchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China.
Wenchao SunWenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China. sunwenchao131@163.com.
Ningyi JinCollege of Animal Science and Technology, Guangxi University, Nanning, China. ningyik@126.com.
Huijun LuChangchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China. huijun_lu@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDengue virus (DENV) is the most widespread arbovirus. The World Health Organization (WHO) declared dengue one of the top 10 global health threats in 2019. However, it has been underrepresented in bibliometric analyses. This study employs bibliometric analysis to identify research hotspots and trends, offering a comprehensive overview of the current research dynamics in this field.

resultsWe present a report spanning from 1995 to 2023 that provides a unique longitudinal analysis of Dengue virus (DENV) research, revealing significant trends and shifts not extensively covered in previous literature. A total of 10,767 DENV-related documents were considered, with a notable increase in publications, peaking at 747 articles in 2021. Plos Neglected Tropical Diseases has become the leading journal in Dengue virus research, publishing 791 articles in this field-the highest number recorded. Our bibliometric analysis provides a comprehensive mapping of DENV research across multiple dimensions, including vector ecology, virology, and emerging therapies. The study delineates a complex network of immune response genes, including IFNA1, DDX58, IFNB1, STAT1, IRF3, and NFKB1, highlighting significant trends and emerging themes, particularly the impacts of climate change and new outbreaks on disease transmission. Our findings detail the progress and current status of key vaccine candidates, including the licensed Dengvaxia, newer vaccines such as Qdenga and TV003, and updated clinical trials. The study underscores significant advancements in antiviral therapies and vector control strategies for dengue, highlighting innovative drug candidates such as AT-752 and JNJ-1802, and the potential of drug repurposing with agents like Ribavirin, Remdesivir, and Lopinavir. Additionally, it discusses biological control methods, including the introduction of Wolbachia-infected mosquitoes and gene-editing technologies.

conclusionThis bibliometric study underscores the critical role of interdisciplinary collaboration in advancing DENV research, identifying key trends and areas needing further exploration, including host-virus dynamics, the development and application of antiviral drugs and vaccines, and the use of artificial intelligence. It advocates for strengthened partnerships across various disciplines to effectively tackle the challenges posed by DENV.

Indexed as

BibliometricsDengue VirusAnimalsBiomedical ResearchDengueHistory, 20th CenturyHistory, 21st CenturyHumansAntiviral therapiesBibliometric AnalysisDengue Virus (DENV)Global Research TrendsVaccine DevelopmentVector Control Strategies

Identifiers

PMID39227968
PMCPMC11370300

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.