Abstract

Background:

Influenza, a highly contagious respiratory disease, is especially severe for the elderly, children, and immunocompromised individuals. Traditional Chinese medicine (TCM), with its antiviral, immune-modulating, and symptom-relieving properties, has gained attention as a potential treatment. This study uses bibliometric analysis to assess the research trends, hotspots, and progress of TCM in treating influenza.

Methods:

Literature from the Web of Science Core Collection (WOSCC), Scopus, and PubMed was analyzed using CiteSpace, VOSviewer, and Bibliometrix to explore author collaboration, research trends, clinical trials, and key advancements in TCM for influenza.

Result:

Research on TCM for influenza has steadily increased since 2000, with a marked surge post-2019 following the COVID-19 pandemic. China leads the field, contributing nearly two-thirds of the publications. Research focuses on TCM interventions, antiviral mechanisms, and immune modulation, with emerging hotspots in network pharmacology and molecular mechanisms.

Conclusion:

The study shows a steady annual growth rate of 16.94%, reflecting global interest in TCM for respiratory viral infections. Despite China’s leadership, international collaboration remains limited (10.23%). Research has shifted from empirical formulations to modern scientific methods, but further large-scale trials are needed to confirm TCM’s efficacy.

1 Introduction

Influenza, an acute respiratory infectious disease caused by the influenza virus, is primarily characterized by upper respiratory tract inflammation, excessive immune response activation, and viral-induced pulmonary damage (Herold et al., 2015). The influenza virus belongs to the Orthomyxoviridae family and is an RNA virus with a single-stranded, negative-sense genome composed of eight segments of genetic material. These segments include the polymerase basic proteins PB1 and PB2, the acidic polymerase PA, hemagglutinin (HA), nucleoprotein (NP), neuraminidase (NA), matrix protein (M), and nonstructural proteins (NS) (Webster et al., 1992). Based on the composition of NP and M, influenza viruses are classified into three types (A, B, and C) (Zheng et al., 2014). Influenza annually imposes a significant global health burden, particularly affecting the elderly, children, and immunocompromised individuals (GBD 2021 Lower Respiratory Infections and Antimicrobial Resistance Collaborators, 2024). According to the World Health Organization (WHO), influenza epidemics can result in millions of severe cases and hundreds of thousands of deaths (Hay and McCauley, 2018). Current treatment methods primarily rely on antiviral agents, such as neuraminidase inhibitors oseltamivir and zanamivir; however, their efficacy is limited due to issues of drug resistance and adverse effects, and their impact on alleviating influenza complications remains inconclusive (Javanian et al., 2021; Chan and Hui, 2023). As such, the development of novel therapeutic strategies remains a pressing challenge in the field of influenza prevention and treatment.

In recent years, traditional Chinese medicine (TCM) has emerged as a focal point in influenza treatment research, owing to its unique antiviral, immune-modulatory, and symptom-relieving properties (Mousa, 2017). TCM offers a new avenue for influenza treatment through multiple mechanisms, such as modulating immune responses, inhibiting viral replication, and alleviating inflammatory responses (Huang et al., 2021). Chinese herbal formulas, such as Lianhua Qingwen and Chaihu Shugan San, have demonstrated significant clinical efficacy, particularly in alleviating influenza symptoms and shortening the duration of illness (Zhan et al., 2025). However, the diverse forms of TCM applications, coupled with the lack of standardized efficacy evaluation criteria and insufficient verification of drug safety, have posed challenges to its clinical use. These limitations underscore the need for a systematic review of the progress and challenges in TCM-based influenza treatment.

Despite advancements in both clinical and fundamental research on TCM for influenza, bibliometric analyses in this field remain scarce. Existing studies often rely on a single database, overlooking the advantages of integrated database searches, resulting in incomplete data coverage and an inability to fully reflect the dynamic research trends. Furthermore, most bibliometric studies tend to focus on quantitative indicators, such as publication volume and author collaboration, with insufficient attention to in-depth analyses of clinical trial design, efficacy evaluation, and drug safety. To address these gaps, this study integrates data from multiple databases, including the Web of Science Core Collection (WOSCC), Scopus, and PubMed, and employs visualization tools to provide a comprehensive assessment of the research landscape on TCM for influenza. Additionally, this study aims to uncover key scientific issues and technological bottlenecks within the field, offering valuable insights for future research endeavors.

2 Methods2.1 Data retrieval

This study conducted a systematic literature search across three databases: the Web of Science Core Collection (WoSCC), Scopus, and PubMed. The aim was to identify relevant research publications and clinical trials related to the use of traditional Chinese medicine (TCM) in the treatment of influenza, to support bibliometric analysis. Original articles and reviews were retrieved from WoSCC and Scopus, while PubMed was queried for closely related clinical trials. A comprehensive list of the search strategies, including the complete search strings, is provided in Supplementary Table 1. To ensure data integrity and prevent duplication, we employed a combination of automated de-duplication and manual checks. This approach allowed for the elimination of redundant entries (Figure 1). After curating the literature on traditional Chinese medicine-based influenza research, we applied the same standardized data-cleaning workflow to publications on Western antiviral drugs to support subsequent bibliometric analyses and enable robust cross-domain comparisons (Supplementary Figure 1 and Supplementary Table 2). The final search date across all databases was November 1, 2025. The search, de-duplication, and initial data processing were independently conducted by two researchers, and any discrepancies were resolved through discussion and collaboration.

Workflow for literature retrieval and data cleaning in TCM influenza research. This workflow depicts the systematic selection of literature on traditional Chinese medicine (TCM) in influenza research across multiple databases. It traces the process from initial retrieval and deduplication through title/abstract screening and full-text evaluation to final inclusion, ensuring scientific rigor and reproducibility.

2.2 Data analysis

Several leading bibliometric analysis tools were employed to process and analyze the retrieved data, including CiteSpace (version 6.4.R1), VOSviewer (version 1.6.20), and the R-Bibliometrix package (version 5.0) within R-Studio, for visualization and comprehensive analysis (Synnestvedt et al., 2005; Arruda et al., 2022). Additionally, Microsoft Excel 2024 was used to generate bar charts and line graphs. Bibliometrix is a comprehensive analysis package based on the R programming language, equipped with multi-dimensional analysis capabilities and visualization functions. This tool supports cross-database data integration and can handle metadata from multiple sources of literature in a unified manner (Bamahel et al., 2025). In this study, Bibliometrix (version 5.0) was used to merge data from WoSCC and Scopus, and key bibliometric indicators for each database were manually reviewed and recorded (Figure 1).

Furthermore, based on the PubMed search results, we summarized the characteristics of relevant clinical trials, including the herbal components used in the formulations, the study periods, and the conclusions drawn. This provides supplementary insights into the clinical aspects of TCM in influenza treatment research. It is important to note that only studies explicitly employing Chinese herbal components in their interventions were included in the analysis.

2.3 Standardization of author, institution, and keyword data

To address variations in author names, inconsistent capitalization, and formatting discrepancies, we standardized author information, institutions, and keywords in the raw data. Due to the lack of unique author identifiers (e.g., ORCID), some author nodes may still have minor duplication or erroneous merging. Consequently, the results and conclusions are based on macro-level collaboration patterns. To improve consistency in the institution collaboration network, Bibliometrix’s “Institution Name Disambiguation” feature was used to merge variant names for the same institution.

In keyword processing, researchers manually standardized synonyms and near-synonyms and removed generic terms unrelated to the research hotspots to maintain focus on the core themes.

3 Results3.1 Overview of publication trends

Between 2000 and 2025, a total of 640 and 850 publications were retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases, respectively. After de-duplication and consolidation, 959 unique publications were included in the analysis, sourced from 407 distinct journals and publications. The annual average growth rate of literature in this field was 16.94% (combined WOSCC + Scopus), with WOSCC contributing an 18.39% increase and Scopus showing a 16.45% growth rate, reflecting the rapid development of research on traditional Chinese medicine (TCM) in influenza treatment. The average age of the publications was 6.16 years, indicating that the research output is relatively recent, with an average of 27.4 citations per article (for the combined dataset). Notably, publications from the Scopus database had a higher average citation count (30.12), which may be attributed to the inclusion of a greater proportion of review articles (Table 1).

DescriptionWOSSCScopusWOSSC + ScopusTimespan2000:20252000:20252000:2025Sources (journals, books, etc.)247366407Documents640850959Annual growth rate %18.3916.4516.94Document average age5.516.276.16Average citations per doc23.3830.1227.4Keywords plus (ID)1,65511,2997,959Author’s keywords (DE)1,7882,3252,567Authors4,0114,8712,915Authors of single-authored docs72427Single-authored docs72427Co-authors per doc7.717.127.11International co-authorships %15.341810.23Article541659747Review99191212

Comparison of overall statistics between databases (WOSCC, SCOPUS, WOSCC + SCOPUS).

Compares the overall statistics of WOSCC, SCOPUS, and their combined datasets, highlighting key metrics such as publication volume, citation counts, and impact factor.

In the keyword analysis, a total of 7,959 Keywords Plus and 2,567 Author’s Keywords were extracted, underscoring the breadth and diversity of research within this field. On the author level, 2,915 distinct authors contributed to the publications, with a minimal number of single-author papers (only 27), suggesting that the majority of publications are collaborative in nature. The average number of co-authors per paper was 7.11, reflecting a high degree of team-based collaboration. International collaboration accounted for 10.23% of the total, which remains relatively low. In terms of publication types, research articles (747 papers, 77.9%) predominated, while review articles (212 papers, 22.1%) also constituted a significant portion of the literature (Table 1).

3.2 Publication trends and geographical distribution

One of the most direct ways to assess the evolution of a discipline or field is by observing the changes in annual publication volume. We systematically analyzed the publication trends related to traditional Chinese medicine (TCM) in the treatment of influenza using data from the Web of Science Core Collection (WoSCC), Scopus, and the combined dataset of both sources. Overall, the number of relevant studies has shown a steady increase since 2000, with a significant acceleration in growth from 2010 onwards. Following 2019, a dramatic surge in publications occurred, peaking in 2021 with a total of 105 publications from WoSCC and Scopus combined. This sharp increase reflects the heightened global focus on TCM interventions for respiratory infections in the context of the COVID-19 pandemic. Although there has been some fluctuation in recent years, the overall trend remains elevated, indicating a sustained high level of interest in TCM for influenza treatment (Figure 2A).

Publication trends and geographical distribution. (A) Annual publication trends: displays the annual publication trends in the field of traditional Chinese medicine (TCM) for influenza treatment, based on data from WOSCC, SCOPUS, and their combined datasets. (B) Fitted publication volume curve: illustrates the fitted curve representing publication volume over time for WOSCC, SCOPUS, and their merged dataset. (C) Annual citation trends: depicts the annual citation trends for TCM-related influenza research across WOSCC, SCOPUS, and combined data. (D) Top 10 countries by publication volume: ranks the top 10 countries by publication volume in TCM for influenza research, based on WOSCC and SCOPUS data. (E) Top 10 institutions by publication volume: ranks the top 10 institutions by publication volume in TCM for influenza research, derived from WOSCC and SCOPUS data.

We further fitted the annual publication data to a time-series curve, which revealed a clear nonlinear growth trend across all datasets (WoSCC, Scopus, and the combined dataset). The composite curve from the combined data (red solid line) illustrates a notable acceleration in growth after 2019. Polynomial regression analysis (R2 = 0.883) demonstrated a high level of fit, reinforcing the observation that the research investment and output in this field have both intensified (Figure 2B).

Regarding the cumulative citation distribution of publications by year, early papers (such as those from 2003 and 2009) received higher citation counts due to their relevance to key epidemic events, such as SARS and the H1N1 influenza pandemic. This resulted in two distinct citation peaks (Figure 2C and Table 2).

YearWOSSC mean TC per articleScopus mean TC per articleWOSSC + Scopus mean TC per article200029.0050.5045.00200118.0014.0018.00200255.6756.3351.00200319.00148.80147.402004126.0067.0086.83200542.0069.2366.08200674.0063.8654.29200722.6032.7527.00200831.3350.7048.40200911.00135.56152.12201058.0053.5048.55201138.5555.6750.87201224.4026.4323.91201329.5538.0936.19201436.8235.4032.81201542.3253.9243.90201620.3541.0037.87201745.7968.2351.79201826.0046.9040.72201920.4022.9721.46202054.2548.1945.25202125.5328.4626.48202214.3313.2912.3820238.5910.509.2520245.185.484.9020250.780.700.70

Annual citation analysis by database (WOSCC, SCOPUS, WOSCC + SCOPUS).

Presents the annual citation trends for publications in TCM and influenza research, based on WOSCC, SCOPUS, and their combined dataset.

On a global scale, China leads the publication count by a wide margin, with 644 papers, underscoring its dominant role in the field of TCM-based influenza research. The United States ranks second with 51 papers, followed by India, South Korea, Japan, and other countries, indicating that this area of research is increasingly gaining international attention (Figure 2D). However, despite having far fewer publications than China, countries like the United States, the United Kingdom, and Germany exhibit a high proportion of multi-country publications (MCP), indicating that their research is heavily reliant on international collaboration (Table 3).

CountryArticlesArticles %SCPMCPMCP %CHINA64467.2587579USA515.3371427.5INDIA394.13812.6KOREA202.117315JAPAN151.61500UNITED KINGDOM141.511321.4GERMANY111.18327.3AUSTRALIA1019110IRAN90.9900PAKISTAN70.7700

Top 10 countries by publication volume (WOSCC + SCOPUS).

Ranks the top 10 countries by publication volume in the TCM-influenza research field.

Among the top 10 research institutions by publication volume, Beijing University of Chinese Medicine leads with 77 papers, followed by Guangzhou University of Chinese Medicine (71 papers) and China Medical University, Taiwan (65 papers). This reflects the central role of Chinese traditional medicine universities in this field (Figure 2E). Additionally, we have compiled the Research Organization Reference ID (RORID) for the top 10 institutions to eliminate any potential ambiguities (Table 4).

AffiliationROR IDArticlesBEIJING UNIVERSITY OF CHINESE MEDICINE05damtm7077GUANGZHOU UNIVERSITY OF CHINESE MEDICINE03qb7bg9571CHINA MEDICAL UNIVERSITY TAIWAN00v408z3465FUDAN UNIVERSITY013q1eq0862GUANGZHOU MEDICAL UNIVERSITY00zat6v6158CHINA ACADEMY OF CHINESE MEDICAL SCIENCES042pgcv6856SHANDONG UNIVERSITY OF TRADITIONAL CHINESE MEDICINE0523y5c1949CHENGDU UNIVERSITY OF TRADITIONAL CHINESE MEDICINE00pcrz47048CAPITAL MEDICAL UNIVERSITY013xs5b6041NANJING UNIVERSITY OF CHINESE MEDICINE04523zj1941

Top 10 institutions by publication volume (WOSCC + SCOPUS).

Ranks the top 10 institutions by publication volume in the TCM-influenza research field.

3.3 Author, institution, and country productivity analysis

Although the field boasts a large number of researchers, publication output is relatively concentrated among a few high-producing authors. Authors such as WANG, YUTAO, ZHANG, Y., and YANG, ZIFENG have consistently maintained high research output over an extended period, highlighting their significant contributions and leadership in the field (Figure 3A). Analysis based on Lotka’s law reveals that approximately 80% of authors have published only one paper, while fewer than 10% have authored three or more articles, illustrating the high degree of imbalance in scientific output (Figure 3B). This “long-tail distribution” phenomenon suggests that while a few core experts lead the research frontier, much of the work remains exploratory, underscoring the need to establish more effective collaborative mechanisms to enhance overall research efficiency. Furthermore, we used the R package to calculate the top 10 authors ranked by academic contribution indicators (such as the H-index) (Table 5).

Author, institution, and country productivity analysis. (A) Annual author productivity: presents the yearly output of authors in TCM-influenza research, using data from WOSCC and SCOPUS. (B) Annual country productivity: shows the annual publication output of countries in the field of TCM for influenza treatment. (C) Annual institution productivity: depicts the yearly publication output of institutions in the TCM-influenza research area. (D) Author productivity following Lotka’s law: displays the distribution of author productivity in the field of TCM for influenza, illustrating the skewness in publication frequency based on Lotka’s law.

Authorh_indexg_indexm_indexTCNPPY_startWANG YUTAO23421.4381,915782010LI Y20301.3331,004502011LI, JING19321.1181,122502009YANG ZIFENG19381.1881,514402010WANG XINHUA17310.851,018522006ZHANG Y17350.681,268522001LIU Y16360.81,299462006LI X154211,772482011LI Z14280.56825322001WANG Z14300.933914342011

Top 10 authors by H-index (WOSCC + SCOPUS).

Ranks the top 10 authors by their H-index in the TCM-influenza research field.

At the institutional level, Beijing University of Chinese Medicine has experienced steady growth in publications since 2011, with a significant breakthrough in 2020, positioning it as one of the most active research centers in this field. Similarly, China Medical University, Taiwan, has demonstrated strong research momentum since 2010, reflecting the collaborative advancement of TCM research across the Taiwan Strait (Figure 3C).

At the national level, China is the undisputed leader in this field, with its publication output surpassing that of other countries since 2010. While the United States, Japan, India, the United Kingdom, and other nations have made contributions, their output is relatively small, and their growth momentum remains insufficient. Apart from China, research investment from other countries in this area remains limited, indicating an urgent need to strengthen international collaboration (Figure 3D).

In terms of journal distribution, Journal of Ethnopharmacology leads with 112 publications, making it the most influential international journal in this field. It is followed by Frontiers in Pharmacology (44 papers), Evidence-Based Complementary and Alternative Medicine (29 papers), and others, all of which are prominent journals in the fields of pharmacology and complementary and alternative medicine. The concentration of publications in these journals indicates that TCM-based influenza research is increasingly integrated into mainstream international scientific frameworks, with its findings being disseminated and published in high-impact platforms (Figure 3E). We also calculated the academic metrics and publishing information of high-impact journals in the field of TCM-based influenza research, covering the top 10 international journals with the most publications in this domain (Table 6