Structural and temporal dynamics of pediatric influenza prevention and treatment: a comprehensive bibliometric analysis of historical evolution and emerging trends

Introduction

Influenza is an acute respiratory infection caused by influenza viruses (IV), triggering seasonal epidemics worldwide with significant morbidity and mortality rates (1). Approximately one billion people contract seasonal influenza annually, with 3–5 million severe cases (2). Children are more susceptible due to their immature immune systems and face higher risks of complications (3). Global data indicate that influenza accounts for 10% of respiratory hospitalizations among children under 18 years old (4), with those under 5 years old and children with underlying medical conditions facing particularly high risks of severe illness and death (5-7). In 2018, approximately 109.5 million influenza cases occurred among children under 5 globally. Of these, 10 million progressed to acute lower respiratory infections (ALRI), resulting in 870,000 hospitalizations and 35,000 deaths (8).

Vaccination remains the most effective preventive measure currently available, significantly reducing influenza incidence, hospitalization, and mortality risks (9). The American Academy of Pediatrics (AAP) recommends annual vaccination for all children aged ≥6 months (5). However, the virus’s high mutation rate necessitates continuous vaccine updates, posing challenges for both development and supply (10,11). Furthermore, insufficient vaccine coverage in low- and middle-income countries due to economic and resource constraints means that children continue to bear a heavy influenza burden (12,13). Antiviral drugs such as neuraminidase (NA) inhibitors (oseltamivir) and ribonucleic acid (RNA) polymerase inhibitors (baloxavir marboxil) are essential components of treatment (14), but drug resistance driven by rapid viral mutation threatens their efficacy (15).

In recent years, extensive research has focused on the prevention and control of influenza in children. Bibliometric analysis can objectively reveal trends and hotspots in this field. This study is designed as a comprehensive bibliometric analysis to contextualize the changing research interests in this field. Rather than serving as a rigid analytical framework, bibliometric tools (CiteSpace, HistCite Pro 2.1, and Alluvial Builder) are utilized as guideposts to systematically organize and visualize the historical evolution and structural dynamics of the literature. This methodological positioning allows for interpretative flexibility, enabling us to deeply synthesize research hotspots, acknowledge potential biases in literature selection, and engage in an extrapolative discussion regarding emerging trends. Ultimately, this review aims to summarize historical characteristics, identify research hotspots and emerging directions, and provide evidence for prevention and control practices as well as policy formulation. We present this article in accordance with the BIBLIO reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0086/rc).

Methods

Data collection

This study combines quantitative bibliometric visualization with qualitative literature synthesis. To establish a structured sample of the literature, we selected the Web of Science Core Collection (WoSCC) as the primary database. Although databases such as Scopus and PubMed offer broader coverage, WoSCC was exclusively chosen because it provides the standardized and comprehensive citation metadata (including full cited references) strictly required by advanced bibliometric software (e.g., CiteSpace and HistCite). Merging multiple databases often results in data format incompatibilities and loss of critical citation linkages, which can severely compromise the integrity of co-citation network analyses. Accordingly, we performed a systematic search in WoSCC using the following search criteria for the period 1994–2024: ((((((((((TS=(Influenza)) OR TS=(influenzas)) OR TS=(“Human Influenza”)) OR TS=(“Human Influenzas”)) OR TS=(“Influenza irHumans”)) OR TS=(“Influenza in Human”)) OR TS=(“Grippe”)) OR TS=(“Human Flu”)) OR TS=(Flu))) AND ((((((TS=(prevention)) OR TS=(“prevention and control”)) OR TS=(“preventive measures”)) OR TS=(“preventive therapy”)) OR TS=(prophylaxis)) OR TS=(control) OR ((((TS=(Therapeutics)) OR TS=(Therapy)) OR TS=(Therapies)) OR TS=(Treatment)) OR TS=(Treatments)) AND (((((TS=(infant)) OR TS=(adolescent)) OR TS=(child)) OR TS=(children)) OR TS=(childhood)). The retrieved literature records were then downloaded and saved as plain text files as samples of the data analyzed in this paper in the format of “Full Record and Cited References”. Subsequently, non-English literature, non-article, and non-review article literature were excluded. Then, by reading the titles and abstracts, literature unrelated to the prevention and treatment of influenza in children was further excluded. Finally, a total of 3,515 articles were collected and named DATA. Meanwhile, we collected raw data such as country/region, organization, journal, author, article type of publication, etc. The literature screening and analysis process is shown in Figure 1.

Figure 1 Flowchart of the literature screening and analysis process.

Bibliometric analysis tools

This study employs bibliometric tools as guideposts to identify key thematic shifts, core literature, and academic networks, thereby structurally scaffolding our in-depth qualitative synthesis. Rather than being confined to mere numbers, this approach grants us the interpretative flexibility to deeply synthesize research findings. Ultimately, the quantitative data serve as an objective starting point, enabling a richer and more extrapolative discussion of emerging trends and future policies.

CiteSpace

Co-occurrence networks

Scientific collaboration manifests as multiple authors, institutions, or countries jointly contributing to the same publication, holding significant importance for understanding field development dynamics. Collaboration is typically analyzed across three dimensions: authors, institutions, and countries. By importing relevant literature data into CiteSpace, co-occurrence networks can be constructed to systematically visualize collaborative and conceptual relationships. The software uses color to distinguish nodes and edges: edge colors represent the year the co-occurrence relationship was first established, while nodes are depicted with multi-colored “annual rings”, where ring thickness reflects co-occurrence frequency in a specific year. Red rings indicate citation bursts, while purple rings denote nodes with high intermediary centrality. The latter serve as critical hubs connecting different parts of the network, holding significant structural importance.

Burst detection

Jon Kleinberg noted that topics within literature streams often emerge intensely over short periods before fading away. This temporal pattern can be identified through text mining as an “activity outbreak” (16). CiteSpace supports emergence detection across disciplines, keywords, and references, where pronounced citation surges indicate that related topics have garnered widespread attention within the scientific community (17,18).

Cluster analysis

Data from the pediatric influenza prevention and control field were imported into the software (version 6.2.R4), with the time range set to 2002–2021 and a one-year interval between slices. Select “Title”, “Abstract”, “Author Keywords (DE)”, and “Keywords+” as term sources. Set node types according to analysis objectives, leaving other parameters at default values. Automatically generate network maps of countries, institutions, or author collaborations, then manually adjust and optimize visualization effects. The keyword clustering graph follows a similar construction method, with node type set to “Keywords” and time divided into five intervals: 1994–2000, 2001–2006, 2007–2012, 2013–2018, and 2019–2024. For co-citation maps, select “References” nodes and enable “Timeline View” in the “Layout” tab to generate a timeline visualization. Utilize the “View” function in the “Burstness” tab to detect and generate burstness maps for keywords, categories, or references.

HisCite

HistCite Pro 2.1 analyzes citation relationships and identifies highly cited literature within a field, visualizing the temporal evolution and knowledge accumulation of significant publications. The software employs two citation metrics: local citation score (LCS, internal citation frequency within the dataset) and global citation score (GCS, total citation count in the WoSCC). This study imported 3,515 pediatric influenza prevention and treatment publications into the tool, setting “Limit” to 30 with default parameters. The “Make Chart” function generated a research map to rapidly identify key publications.

Alluvial generator

Alluvial Generator visualizes the temporal evolution of research topics, collaborations, and citation trends through streaming graphs, enabling tracking of shifting research foci and disciplinary intersections (19). The specific workflow involves exporting time-segmented keyword co-occurrence networks from CiteSpace and importing them into the tool’s online platform (http://www.mapequation.org/apps/AlluvialGenerator.html). Keywords serve as nodes, clustered into modules by time period. Nodes split or merge into new modules over time, with the latest modules formed from the intersection of previous nodes.

Statistical analysis

Descriptive statistical analyses of the publication metadata, including annual publication volume, institutional contributions, and journal distribution, were systematically performed using Microsoft Excel 2019. Visual representations of categorical data (e.g., the donut plot) were generated using R software (version 4.2.2) with the ggplot2 package (version 3.4.4). For the bibliometric network analyses, quantitative metrics such as the LCS and GCS were calculated using HistCite Pro 2.1. Furthermore, CiteSpace was utilized to compute betweenness centrality to identify critical network hubs, and Kleinberg’s burst detection algorithm was applied to statistically quantify citation burst strength, identifying sudden surges in research interest over specific periods. As this study is based on bibliometric literature data rather than human subject or clinical trial data, traditional inferential statistics (e.g., P values) were not applicable; all quantitative findings are presented as descriptive statistics and network metrics.

Results

Historical features of the literature on influenza prevention and treatment

Distribution of publications

A total of 3,515 documents associated with the prevention and treatment of influenza in children were retrieved, comprising 3,112 research articles and 403 review articles. These publications involved 17,906 authors and 4,774 organizations, and were disseminated across 731 journals in 93 scientific categories (Table 1).

The annual research results are shown in Figure 2A. From 1994 to 1999, the publication volume remained relatively low. However, from 2000 to 2011, there was a sharp increase in the number of publications, followed by a slight decline after 2012.

Figure 2 Publication trends and top journals. (A) The annual distribution of publications. (B) The top 20 fruitful journals.

Vaccine ranked first in terms of the number of publications [290], followed by Pediatric Infectious Disease Journal [155] and PLoS One [133]. Figure 2B presents the top 20 most prolific journals, serving as a reference for researchers when making decisions regarding manuscript submission.

The vein of research on pediatric influenza prevention and treatment

The citation network diagram in Figure 3 reveals extensive connections among research in this field over the past two decades, comprising 1,787 nodes and 8,304 links. The overall structure evolves in a tree-like pattern: early-stage (1994–2010) gray nodes exhibit high density and extensive connections, forming the field’s foundation; mid-stage (2011–2017) blue nodes gradually spread to form main branches; while the recent period (2018–2024) shows nodes clustering into groups, reflecting a trend toward concentrated and specialized research themes. Key influential studies include Dawood FS (2009), Jain S (2009), and Poehling KA (2006), with co-citation frequencies of 125, 111, and 94, respectively. The convergence and differentiation of research clusters will be further elucidated in subsequent timeline diagrams. We additionally employed HisCite Pro 2.1 to plot citation history trajectories, with significant publications summarized in Table 2. Among these, the top three most influential include: mortality associated with influenza and respiratory syncytial virus (RSV) in the United States, the efficacy of live attenuated, cold-adapted, trivalent, intranasal influenza virus vaccine in children, and influenza-associated hospitalizations in the United States.

Figure 3 Literature co-citation graph (color bars from left (grey) to right (red) indicate years 1994 to 2024). Each node in the graph represents a piece of scientific literature, and the size of the node is proportional to the number of citations to that literature. The larger the node, the more the literature has been cited and the more influential it is. The color of the node indicates the year of publication of the literature. The color bar (bottom left of the figure) shows a gradient from white (earlier years) to red (more recent years). For example, white nodes represent earlier published literature and red nodes represent more recent published literature. The connecting line indicates a co-citation relationship between two documents, i.e., these two documents were cited by a third document at the same time. The more connecting lines indicate that these two kinds of literature are more closely related in the research field and may belong to the same research topic or area. Node clusters of different colors indicate different research themes or fields.

Scientific cooperation

As shown in Figure 4, the National Collaboration Network (Figure 4A) comprises 137 nodes and 1,706 connections, with the United States occupying a central position. Nodes representing England, Italy, Japan, and China are larger and colored more vividly, indicating their recent prominent contributions. Nodes such as Germany and France, though smaller, remain influential. The Institutional Collaboration Network (Figure 4B) comprises 575 nodes and 964 connections, with core institutions including the Centers for Disease Control and Prevention (CDC)-USA, the University of California System, and Harvard University. The University of Colorado Anschutz Medical Campus occupies a central and large position, while nodes such as Johns Hopkins University and Baylor College of Medicine are large and new, indicating high recent activity. The author collaboration network (Figure 4C) shows Esposito, Susanna and Fry, Alicia M. as leading authors in publications. Nodes such as Fry, Alicia M. and Ambrose, Christopher S. are large and new, with significant recent contributions. Multiple collaborative clusters have formed among authors, such as the group comprising Fry, Alicia M. and Finelli, Lyn, and another group including Ambrose, Christopher S., Belongia, Edward A., and Monto, Arnold S., reflecting a trend toward clustered collaboration. Frequently collaborating countries, institutions, and authors are detailed in Table S1.

Figure 4 The scientific cooperation network. (A) Country cooperation. (B) Institution cooperation. The color of the nodes indicates time, and the color bar (bottom left of the figure) shows a gradient from gray (earlier years) to red (more recent years). For example, gray nodes represent earlier published literature and red nodes represent more recent published literature. (C) Author cooperation. Each node represents a country/academic institution/author. The size of the node indicates the influence or contribution of the country/institution/author in the research field, which is proportional to the total number of citations of the literature published by the country/institution/author. A line indicates a co-citation relationship between two countries/institutions/authors, i.e., the two countries/institutions/authors are cited in a third paper at the same time. More lines indicate that the two countries/institutions/authors are more closely related in the research field and may belong to the same research topic or area. Clusters of nodes of different colors indicate different groups of research collaborations.

Variation of the most active topics

Subject category burst

From 2000 to 2024, citation surges occurred in 108 out of 121 relevant disciplines, indicating significant shifts in research focus. Figure 5 displays the top 50 disciplines by emergence intensity and their temporal distribution. “Allergy” exhibited the highest emergence intensity (8.23, 1997–2007), followed by “Medicine, General & Internal” (6.53, 1994–2009). Emergence patterns diversified across disciplines, exemplified by “Dermatology” (1999–2005), “Gastroenterology & Hepatology” (2007–2012), and “Biotechnology & Applied Microbiology” (2012–2013). Twenty emerging disciplines emerged in 2024 (see Table S2), with “Chemistry, Analytical”, “Environmental Sciences”, and “Electrochemistry” ranking as the top three, reflecting the growing influence of interdisciplinary research in the field of pediatric influenza.

Figure 5 The top 50 subject categories with the most significant citation bursts. Subject Categories, 50 subject categories are listed. Year, the year of the citation outbreak for the subject category. Strength, the strength of the citation outbreak, the larger the value, the faster the citation growth in the period. Begin, the year when the citation outbreak started. End, the year when the citation outbreak ended. Bars, the duration of the citation burst for each subject category, with the red bars indicating the period of the burst and the blue bars indicating the entire observation period.

Keywords burst

During the study period (1994–2024), a total of 720 keywords exhibited emergence activity, with the top 50 in emergence intensity shown in Figure 6. “Seasonal influenza” demonstrated the highest emergence intensity (32.47, 2016–2024), indicating sustained attention. Early keywords such as “virus” (21.46, 1994–2010) and “efficacy” (20.82, 1997–2007) also exhibited significant emergence. In 2024, 20 keywords remain in an emergent state, indicating potential research hotspots. These include “baloxavir marboxil” (11.03, 2019–2024), “influenza” (10.1, 2021–2024), and “China” (7.23, 2020–2024), with the latter potentially linked to the COVID-19 pandemic.

Figure 6 The top 50 keywords exhibiting the most significant citation bursts. Keywords, 50 keywords are listed. Year, the year of the keyword citation burst. Strength, the strength of the citation burst, the larger the value, the faster the citation growth in the period. Begin, the year of the citation bursts start. End, the year of the citation burst end. Bar chart, the duration of each keyword citation burst, with the red bars indicating the period of the burst and the blue bars indicating the entire observation period.

A total of 1,885 publications exhibiting citation salience were identified, with the 30 most frequently cited articles from 1994 to 2024 listed in Figure 7.

Figure 7 The top 30 references with citation bursts in different periods. References, specific citation information. Year, the year the document was published. Strength, the strength of the citation burst, the larger the value, the faster the citation growth during the period. Begin, the year when the citation burst started. End, the year when the citation burst ended. Bars, the duration of each citation burst, with red bars indicating the duration of the burst and blue bars indicating the entire observation period.

Belshe RB (1998) demonstrated the highest citation impact (40.84, 1999–2003), with this multicenter randomized controlled trial confirming the safety and efficacy of cold-adapted trivalent live attenuated influenza vaccine in young children, achieving 93% protection (21); Neuzil KM (2000) (40.56, 2000–2005) quantified the influenza disease burden in infants and young children using Medicaid data, revealing a negative correlation between age and hospitalization risk (50); Izurieta HS (2000) (35.56) emphasized significantly increased hospitalization risk during influenza season among healthy children under 2 years old, supporting routine immunization for this group (51).

In 2024, 98 new emerging literature pieces appeared, with the top 20 in emergence intensity (including 3 reviews and 17 research papers) listed in Table 3. These publications rapidly garnered attention in the year of publication or the following year, significantly advancing pediatric influenza prevention and control research and potentially indicating future research directions.

Emerging trends and new developments

The temporal variation in keyword clusters

Keyword clustering analysis from 1994 to 2024 reveals the evolution of research themes (Figure 8). Studies were divided into five 6-year phases, with the following cluster structures for each: 1994–2000 (169 papers): 8 clusters, primarily comprising #0 “adults”, #1 “a virus,” and #2 “infection” (Figure 8A). 2001–2006 (328 articles): 8 clusters dominated by #0 “influenza vaccine,” #1 “zanamivir,” and #2 “infant” (Figure 8B). 2007–2012 (991 articles): 7 clusters, including #0 “live attenuated influenza vaccine”, #1 “zanamivir”, and #2 “tolerability” (Figure 8C). 2013–2018 (1,047 articles): 6 clusters, dominated by #0 “respiratory syncytial virus”, #1 “influenza A”, and #2 “infection” (Figure 8D). 2019–2024 (980 articles): 8 clusters, e.g., #0 “respiratory syncytial virus”, #1 “influenza A”, and #2 “immunization” (Figure 8E).

Figure 8 The keyword clusters snapshots in five periods. (A) 1994–2000. (B) 2001–2006. (C) 2007–2012. (D) 2013–2018. (E) 2019–2024. Different colors represent different keyword clusters, each containing literature on similar research topics. Nodes of the same color (diamonds) belong to the same cluster, indicating that they are co-cited or co-occurring under similar research themes. The cluster number corresponding to the color (e.g., #0, #1, etc.) indicates the main category they form in the analysis, with smaller numbers indicating the importance of the category or a larger number of documents. Colors are assigned independently within each time period merely to distinguish local clusters; identical colors across different panels (A-E) do not indicate a continuous theme or temporal connection.

Compared to the preceding 15 years, classic research topics such as RSV and influenza vaccines remain prominent research hotspots. However, emerging research clusters—such as #1 “influenza A”, #2 “immunization”, #3 “oseltamivir”, #4 “antibody”, #6 “respiratory pathogens”, and #7 “retrospective cohort”—are increasingly attracting researchers’ attention. Cluster #1 “influenza A” contains 54 articles focused on this specific virus. Clusters #2 “immunization”, #3 “oseltamivir”, and #4 “antibody” comprise 46, 41, and 35 articles, respectively, detailing approaches to treating pediatric influenza. Cluster #6 “respiratory pathogens” includes 29 articles addressing influenza pathogenesis, while cluster #7 “retrospective cohort” contains 9 articles related to large-scale retrospective cohort studies. Detailed data for 2019–2024 can be found in Table S3. Representative keywords within these clusters help identify core research areas in pediatric influenza prevention and treatment during the recent period (2019–2024).

The keyword alluvial flow visualization

As illustrated in Figure 9, associated keywords dynamically reorganized into specific modules, with their formation and dissolution driving the emergence of new research domains. Keywords such as “immunization,” “influenza pandemic”, and “children’s health” remained consistently active during the early period (1994–2000), reflecting sustained attention to vaccination and public health. Meanwhile, terms like “bacteria” gradually receded, indicating a shift in focus toward more pressing issues such as viral infections and novel vaccines. While the visual extremes highlight the historical baseline and current frontiers, the intermediate transitional shifts are fully detailed in available online: https://cdn.amegroups.cn/static/public/tp-2026-1-0086-1.xlsx.

Figure 9 The keywords alluvial map 1994–2024. X axis: time slice. Y axis: counting of modules. Number: order of modules on each time slice sorted by the number of nodes. Different colors represent different research topic modules. To prevent severe visual clutter and emphasize macroscopic flow dynamics, text labels are intentionally provided only for the earliest baseline (leftmost) and the latest 2024 frontiers (rightmost). The intermediate unlabeled bars represent transitional thematic modules. The specific representative keywords and detailed composition for every module across all time slices are comprehensively listed in Table S4. COVID-19, coronavirus disease 2019.

The six major keyword clusters in 2024 (Figure 10) further reveal research frontiers, carrying distinct clinical significance for pediatric practice. For instance, Module 1 (“young children”; Figure 10A), which encompasses keywords like “live attenuated influenza vaccine” and “neuraminidase”, clinically highlights the tailored preventive and therapeutic strategies strictly required for this highly vulnerable demographic, emphasizing age-specific immune responses and accurate antiviral dosing. In sharp contrast, Module 2 (“syncytial virus”; Figure 10B), featuring “clinical characteristics” and “epidemiology”, underscores the diagnostic challenges of viral co-circulation. Clinically, this module reflects the urgent real-world need for pediatricians to differentiate influenza from RSV and effectively manage complex co-infections during overlapping seasonal peaks. Building on these challenges, Module 3 (“COVID-19 pandemic”; Figure 10C), with keywords like “randomized trial” and “impact,” signifies the paradigm shift in managing pediatric respiratory infections post-2020. Clinically, it dictates the necessity to understand viral interference and rigorously evaluate the safety of co-administering influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in children. Module 4 (“immunization”; Figure 10D) revolves around “cost-effectiveness”, “immunogenicity”, and “safety”, directing clinical attention toward the health-economic justification and biological optimization of novel pediatric vaccines, moving beyond basic efficacy to comprehensive clinical utility. Furthermore, Module 5 (“recommendations”; Figure 10E), featuring “vaccine effectiveness” and “advisory committee”, represents the crucial translation of real-world evidence into actionable clinical guidelines. It highlights how organizations [e.g., Advisory Committee on Immunization Practices (ACIP), World Health Organization (WHO)] continuously update annual pediatric vaccination strategies based on circulating drifted strains. Finally, Module 6 (“acute respiratory illness”; Figure 10F) includes “transmission”, “Hong Kong”, and “pandemic influenza”. Clinically, this underscores the vital importance of regional epidemiological surveillance hubs (e.g., Hong Kong as a historical sentinel) in predicting transmission dynamics, preparing pediatric hospital infrastructures, and optimizing infection control protocols to mitigate sudden pandemic surges.

Figure 10 The keywords of top six modules in 2024. (A) Module 1. (B) Module 2. (C) Module 3. (D) Module 4. (E) Module 5. (F) Module 6. The legend lists the keywords or topics corresponding to each color. Each sector of the ring represents a module, and the size of the sector is usually proportional to the importance of the module or the frequency of the keyword. COVID-19, coronavirus disease 2019.

The timeline visualization of references

Timeline visualization analysis identifies classic, emerging, and relatively outdated research themes by tracking citation trends. The visual map comprises 20 clusters (Figure 11A), with clusters #0 “pandemic”, #1 “immunogenicity”, #4 “asthma”, #5 “treatment”, #7 “oseltamivir”, #12 “transmission”, and #13 “adults” representing classic themes that remain closely linked to other studies and continue exerting significant academic influence. In contrast, clusters such as #8 “cost-effectiveness” and #10 “pneumococcal antibodies” exhibit lower activity and a declining research trend. Emerging themes include #2 “baloxavir”, #3 “vaccine effectiveness”, #6 “COVID-19”, #9 “pneumonia”, and #19 “beliefs”. These domains have maintained activity since their emergence, with increasing relevance, demonstrating potential to become future research hotspots. Table S4 provides more detailed information on these emerging clusters. To bridge these bibliometric findings with clinical practice, Table 4 provides a simplified translational summary of these 19 clusters. This table distills the dense bibliometric network into actionable clinical implications, offering pediatricians a clear historical context for current prevention and treatment guidelines.

Figure 11 The reference clusters map. (A) The citation timeline visualization. The X-axis represents time, from 1994 to 2024, with each time point representing a specific year. The Y-axis lists 19 keyword clusters, each of which is numbered and labeled to indicate the main research topic of the cluster. For example, cluster #0 is labeled “pandemic”, cluster #1 is labeled “immunogenicity”, and so on. Each node represents a piece of scientific literature, and the size of the node is usually proportional to the number of citations to the literature. The lines between the nodes indicate co-occurrence relationships between the documents, i.e., they are cited in the same document. The color bars are located at the bottom of the graph and fade from gray (earlier years) to red (more recent years). The colors of the nodes and connecting lines reflect when the literature was published, helping to identify research hotspots in different periods. By looking at the size and color of the nodes, it is possible to identify research hotspots in different periods. For example, “COVID-19” (new crown epidemic) has a significantly high co-occurrence frequency in 2020 and 2021, reflecting the research hotness of the topic during this period. (B) The burst citations in #2, #3, #6, #9, and #19. (C) Citation frequency distribution of the burst citation. COVID-19, coronavirus disease 2019.

Furthermore, several seminal papers have played pivotal roles in advancing specific subfields (Figure 11B). For instance, Iuliano AD (2018) in cluster #2 (52) provided new global estimates of pediatric influenza mortality, offering critical evidence for optimizing prevention and control strategies; Grohskopf LA (2016) (70) in Cluster #3 summarized the latest vaccination guidelines from the ACIP. Olsen SJ (2020, Am J Transplant) (71) in Cluster #6 revealed that non-pharmaceutical interventions (NPIs) offer practical guidance for addressing vaccine hesitancy from a psychological perspective. In contrast, Lafond EK (2016) (72) in Cluster #9 estimated over 1.2 million annual hospitalizations among children under five due to influenza, with developing countries experiencing three times the hospitalization rate of industrialized nations, underscoring the need to expand vaccination coverage. Conversely, Brewer NT (2021) (73) in Cluster #19 explores psychological factors influencing vaccination behavior, offering guidance for addressing vaccine hesitancy. Citation distribution projections indicate (Figure 11C) that these key publications will maintain high academic attention in the coming years.

Discussion

Analysis of the fundamental characterization of publications on pediatric influenza prevention and treatment

Research in pediatric influenza prevention and control remains highly active, with publications having grown steadily and close international collaboration forming a complex partnership network. The diversity of research output highlights its multidisciplinary nature. Temporal analysis revealed three distinct phases in the development of this field. The initial phase (1994–1999) was characterized by a limited number of publications. From 2000 to 2011, there was a period of rapid growth, driven by multiple synergistic advancements. In 1999, the WHO released its first “Influenza Pandemic Preparedness Plan”, emphasizing the importance of strengthening influenza surveillance, enhancing emergency preparedness, and advancing the development of vaccines and antiviral therapies (74). The emergence of novel vaccines and antivirals, along with interdisciplinary collaborations, technological advancements, and growing awareness of the disease burden among high-risk groups such as children, catalyzed research efforts and resource investment in the field, leading to an increase in publications. Following the H1N1 pandemic in 2009, there was a sharp rise in pediatric mortality rates, prompting a global response with the development of guidelines, countermeasures, and extensive research. As a result, the volume of publications surged, peaking in 2011 (75,76). After 2012, although the publication rate slightly declined, the annual number of new articles consistently exceeded 123, reflecting the maturity of this field. Research continues to focus on antiviral therapies, vaccine efficacy, and public health strategies.

Persistent challenges and emerging topics in pediatric influenza prevention and treatment

Research on pediatric influenza prevention and treatment continues to evolve. While classic themes such as “live attenuated vaccine”, “neuraminidase”, and “immune response” remain crucial, emerging keywords like “seasonal influenza”, “baloxavir marboxil”, and “immunization practices” signal future research directions. Keyword clustering and timeline network analysis further reveal that “baloxavir”, “vaccine efficacy”, “COVID-19”, and “pneumonia” have emerged as new research hotspots. Increasing interdisciplinary participation highlights how this field is addressing persistent challenges while continuously generating novel research questions.

Exploration of hot topics

Public health control measures

The COVID-19 pandemic has reshaped the epidemiological patterns of childhood influenza. During the pandemic, widespread implementation of NPIs such as mask-wearing and social distancing not only effectively controlled SARS-CoV-2 transmission but also significantly reduced childhood influenza incidence (71,77,78). With the gradual lifting of NPIs, seasonal influenza activity has largely returned to pre-pandemic levels, except for the B/Yamagata lineage, though regional variations persist (79,80). This suggests that NPIs should be incorporated into routine influenza prevention and control strategies.

Vaccine hesitancy has led to low influenza vaccine coverage in children (81). As indicated by the keyword clustering module, “vaccine hesitancy”, “immunization”, and “coverage” have emerged as key research topics in this field. Despite the proven safety and efficacy of influenza vaccines in preventing childhood influenza, vaccination rates have been declining. The 2023–2024 season saw a child vaccination rate of only 55.4%, representing an 8.3% decrease compared to pre-pandemic levels (82). Vaccine hesitancy is listed by the WHO as a global health threat (83,84). Contributing factors include concerns about side effects/safety (85), low perceived disease severity, and limited confidence in vaccine effectiveness (86), socioeconomic factors (87), and limited public awareness (88). This issue is exacerbated in low-income regions due to inequitable resource distribution and limited healthcare access (12,89), necessitating urgent policy and immunization program interventions.

Mixed respiratory virus infections

In recent years, advances in multiplex respiratory pathogen detection technologies (90,91). have heightened attention on mixed infections in children. Keyword analysis reveals that “RSV”, “oseltamivir”, and “COVID-19 pandemic” emerged as prominent themes between 2019 and 2024, reflecting growing concern over viral co-infections. As a susceptible population, children face significantly higher risks of mixed infections compared to adults (92). Although NPIs reduced influenza and RSV transmission during the COVID-19 pandemic (80,93), these viruses have resurged following the relaxation of measures. Studies indicate that influenza incidence among children in northern China in 2023 has significantly increased compared to the previous 2 years (94), with disease severity approaching pre-pandemic levels (95), potentially linked to “immunological debt” (96).

IV shares similar transmission routes and seasonal activity overlap with RSV and SARS-CoV-2 (97), making co-infection difficult to avoid. However, their interactions are complex, potentially synergistic or antagonistic, and whether they exacerbate clinical severity remains controversial (98).

Regarding IV and RSV co-infection, existing conclusions are inconsistent: experimental studies indicate influenza A virus (IAV) can suppress RSV replication (99), resulting in a reduced viral load during subsequent RSV infection; however, this apparent virological suppression does not necessarily translate into clinical benefit, as IAV pre-infection induces pulmonary congestion and inflammatory injury, thereby compromising lung integrity and increasing susceptibility to secondary damage, ultimately leading to aggravated disease severity and increased mortality upon secondary RSV challenge (100). Epidemiological models suggest prior infection with one virus may provide short-term cross-protection (101). Conversely, evidence also exists that co-infection can generate hybrid virus particles (HVPs), enhancing viral spread and evolution while exacerbating lung injury and mortality (102,103). Infection sequence may influence outcomes, with RSV priming potentially conferring protection by stimulating interferon-γ and innate immunity (104).

Concurrent IV and SARS-CoV-2 infection exhibits marked synergistic effects, upregulating angiotensin-converting enzyme-2 (ACE2) expression and enhancing viral replication, leading to increased mechanical ventilation requirements and mortality risk (105-107). Although the global impact of COVID-19 is diminishing, the virus continues to circulate, with new variants emerging persistently. SARS-CoV-2 is likely to persist as a seasonal virus, similar to influenza, posing a long-term public health risk. Co-circulation of both viruses will exacerbate the healthcare burden and may influence vaccine and drug development strategies (108). Therefore, there is an urgent need for more in-depth epidemiological and mechanistic research, as well as the development of coordinated prevention and control strategies targeting multiple respiratory viruses.

Vaccine development and effectiveness

Vaccination is the core measure for preventing influenza in children. The primary seasonal vaccines used include intramuscularly administered inactivated vaccine (IIV), intranasally administered live attenuated influenza vaccine (LAIV), and intramuscularly administered recombinant vaccine (RIV) (109). LAIV induces both mucosal and systemic immunity, offering approximately 50% higher efficacy than IIV in protecting children aged 6–59 months (P<0.001), particularly against antigenically matched or drifted viruses (110). This effect is associated with local IgA responses and compartmentalized immunity (111). Painless vaccination also improves compliance, but is contraindicated in immunocompromised or asthmatic children (112).

To address declining protection due to antigenic drift and viral subtype diversity (11), current research focuses on antigen engineering, nanoparticle formulations, dose escalation, novel adjuvants, and multi-target strategies to broaden immune responses (113). Although the quadrivalent high-dose inactivated vaccine (IIV4-HD) is not approved for pediatric use, Phase II trials indicate that the 60 µg dose demonstrates superior immunogenicity and good safety in children (1,114).

Adjuvants are critical for enhancing vaccine efficacy. Those approved for human use include aluminum adjuvants, MF59, and AS03 (81). MF59, an oil-in-water adjuvant, is widely used in elderly populations and infants in some countries (115). Systematic reviews indicate it enhances immunogenicity and protective efficacy in unvaccinated children but provides limited benefit for previously vaccinated individuals (116). Novel adjuvants such as saponins and Toll-like receptor (TLR) agonists remain in clinical development (113).

Universal influenza vaccines represent an ideal solution. The NIAID 2018 initiative aims to achieve ≥75% symptomatic protection, immunity lasting over one year, and applicability across all age groups (117,118). Research strategies include targeting conserved regions [e.g., hemagglutinin (HA) stem, matrix protein 2 ectodomain (M2e), NA], eliciting T-cell responses [nucleoprotein (NP), matrix protein 1 (M1)], nanoparticle/virus-like particle (VLP) vaccines, nucleic acid vaccines, and viral vector vaccines (119). However, their immunological persistence and efficacy require further experimental validation.

Novel antiviral drugs

Keyword clustering analysis for 2019–2024 indicates that “oseltamivir” remains a prominent topic of interest, while keyword citation bursts reveal “baloxavir” as an emerging focus of research.

Clinical use and resistance of oseltamivir

Oseltamivir is the first-line antiviral drug for influenza in children aged 2 weeks and older (5). Systematic reviews indicate that prompt administration of oseltamivir shortens the illness duration by approximately 18 hours in children and reduces the risk of complications such as otitis media, with no significant adverse effects beyond mild gastrointestinal reactions (54). The AAP recommends early initiation of treatment to optimize efficacy. A study confirm that initiating treatment within 24 hours of hospitalization shortens hospital stays and reduces risks of intensive care unit (ICU) transfer, extracorporeal membrane oxygenation (ECMO) use, readmission, and mortality (14). However, widespread use has led to the emergence of resistant strains, particularly in H1N1 viruses. Resistance primarily arises from mutations in the NA active site, reducing binding affinity with the inhibitor. Immunocompromised patients are more susceptible to developing resistant mutations. This susceptibility is associated with prolonged viral replication and incomplete viral clearance under drug pressure, which increases the risk of severe illness and death (120). Furthermore, resistance rates are higher in patients with influenza-associated acute respiratory distress syndrome (ARDS). A French study showed that approximately 23% of H1N1pdm09-associated ARDS patients exhibited the NA-H275Y mutation, and the 28-day mortality rate was significantly higher in the group infected with the mutant strain (121).

Baloxavir marboxil: applications and limitations

Baloxavir, a novel polymerase acid endonuclease inhibitor, demonstrates broad-spectrum antiviral activity against influenza and is approved for children aged ≥5 years in multiple countries (5). It acts by inhibiting the cap-dependent endonuclease activity of the PA subunit of the viral polymerase complex, thereby blocking viral mRNA transcription at an early stage of replication (122). Clinical studies indicate that in uncomplicated influenza patients aged 12–64 years, a single dose demonstrates favorable safety, provides more effective symptom relief than placebo, and reduces viral load more potently than oseltamivir (53). Pediatric studies further confirm its good oral tolerability, rapid reduction in viral titers, and relief of acute symptoms, with adverse event rates comparable to oseltamivir (58,59). However, its application is constrained by emerging resistance, with reports of reduced IV susceptibility and resistant strains (53,68), particularly those associated with substitutions in the polymerase acidic protein (PA) subunit (e.g., I38 variants), which significantly reduce drug susceptibility (67,123), underscoring the urgent need to develop novel antiviral agents with lower resistance risks.

Exploration of novel antiviral drugs

To combat resistance and enhance therapeutic efficacy, the development of novel antiviral drugs is actively advancing, broadly classified into two categories: virus-directed drugs targeting viral components at different stages of the replication cycle, and host-directed drugs targeting host cell factors involved in IV replication and pathogenesis. HA inhibitors act at the early stage of infection by preventing receptor binding or inhibiting the low-Ph-induced conformational changes required for membrane fusion, thereby blocking viral entry into host cells. Additionally, receptor-modulating agents such as DAS181 (Fludase) cleave sialic acid receptors on host cells to prevent viral attachment. Polymerase complex inhibitors, including PA endonuclease inhibitors (e.g., baloxavir marboxil), PB1 nucleoside analogs (e.g., favipiravir), and PB2 cap-binding inhibitors (e.g., pimodivir), interfere with the cap-dependent transcription (“cap-snatching”) mechanism and RNA chain elongation, which are essential for viral mRNA synthesis in the nucleus. NP-targeting agents such as naproxen disrupt viral ribonucleoprotein (vRNP) complex assembly, nuclear trafficking, and genome replication, thereby impairing efficient virion production. In addition, host cell-directed therapies target critical host factors involved in viral replication, such as endosomal acidification, intracellular trafficking pathways, and host proteases required for HA activation, offering a complementary strategy with a potentially higher barrier to resistance. Beyond traditional inhibitors, proteolysis-targeting chimeras (PROTACs) represent a cutting-edge approach by inducing the ubiquitination and degradation of viral proteins (e.g., NA, HA, or PA), providing a more sustained antiviral effect. Notably, compared with viral-targeted therapies, host-directed strategies may confer a higher genetic barrier to resistance, although they require careful evaluation of safety and potential off-target effects (124,125). Future research should focus on optimizing mechanisms, improving pharmacokinetics, reducing resistance risks, and validating safety and efficacy through large-scale clinical trials to develop more effective pediatric influenza prevention and treatment strategies.

Future directions

Optimization of public health control strategies

During the COVID-19 pandemic, the widespread adoption of NPIs led to a significant decline in influenza incidence, highlighting the potential of NPIs for controlling influenza in a SARS-CoV-2 co-circulation context. Moderate community interventions can effectively slow influenza transmission, but further research is needed to balance NPIs intensity with socioeconomic activity to develop more scientifically grounded control strategies (126).

Furthermore, enhancing vaccination coverage and improving healthcare infrastructure remain critical priorities for influenza control. This requires increased public health investment to reduce vaccine hesitancy and improve access to antiviral medications, particularly in low- and middle-income countries. Annual increases in healthcare resources for children, alongside strengthened primary healthcare services and equitable resource distribution, are also essential to reduce disease burden and enhance pandemic preparedness (3).

Research on IV co-infection with multiple respiratory viruses

Influenza and other respiratory viruses share high similarity in transmission routes, susceptible populations, and seasonal patterns, making them prone to co-infection, though the underlying mechanisms remain unclear. The impact of such co-infections on disease severity and transmission dynamics remains controversial, and effective prevention and control strategies are lacking. The persistent circulation of SARS-CoV-2 in the post-pandemic era has further intensified the mixed transmission trend of influenza and its co-infections, complicating diagnosis, treatment, and prognosis while significantly increasing the public health burden (127). Future research should systematically conduct epidemiological investigations of co-infections to clarify their epidemiological characteristics and risk factors, deeply explore the mechanisms of viral interactions, and progressively establish a comprehensive prevention and control system for “multiple disease co-prevention”. This will provide a scientific basis for developing coordinated intervention strategies.

Advancing the development of novel vaccines and antiviral drugs

Development of next-generation vaccines

Efforts should be accelerated to develop universal influenza vaccines offering broad-spectrum and long-lasting protection, leveraging multiple vaccine platforms and technologies such as next-generation sequencing. Advances in virology, immunology, and vaccinology in recent years have brought this goal closer to reality. Future endeavors should focus on integrating multidisciplinary research, optimizing vaccine design and manufacturing processes, and advancing the clinical translation of vaccines with broad-spectrum and durable protective efficacy (117).

Antiviral drug development and combination therapy

To address drug resistance to existing antiviral drugs, research and development of new antiviral drugs targeting different mechanisms should be prioritized to avoid the limitations of single-target drugs. Several promising new antiviral candidates are currently undergoing clinical trials with the potential for future application. In addition to drug development, combination therapy represents a crucial direction for future influenza treatment (15). Personalized treatment strategies for critically ill and immunocompromised patients also enhance therapeutic efficacy. Future efforts should focus on further evaluating the efficacy and safety of combination strategies to advance their clinical translation and application.

Enhancing influenza surveillance with artificial intelligence (AI) and big data platforms

AI and big data analytics have significantly enhanced the accuracy and efficiency of influenza surveillance. By integrating multi-source data and modeling techniques, it is possible to systematically evaluate the impact of viral evolution, population immunity, and behavioral patterns on transmission, providing scientific evidence for vaccine deployment, NPIs, and resource allocation (126). AI also enables real-time monitoring of viral mutations and drug resistance changes, predicting epidemic trends and optimizing control strategies. Future efforts should strengthen multidisciplinary collaboration and enhance data platform development and application to support precision influenza prevention and control.

Translational outlook for pediatric clinical practice

To directly bridge our bibliometric findings with frontline clinical applications, Table 5 summarizes the top five emerging trends in pediatric influenza research and outlines their immediate translational implications for pediatricians. As the landscape of pediatric infectious diseases rapidly evolves, adapting clinical practices to encompass novel antivirals, multiplex diagnostics, and proactive communication strategies will be paramount for optimizing patient outcomes.

Although this study provides valuable insights into pediatric influenza, the following limitations of bibliometric analysis should be noted. First, reliance solely on the WoSCC database inherently introduces a profound English-language bias. While WoSCC captures high-impact international research, it often under-represents localized clinical guidelines, regional epidemiological reports, and public health policies published in native languages. Consequently, our bibliometric findings may disproportionately reflect Western or Anglophone paradigms. This bias specifically limits our ability to fully capture the diverse and highly effective regional public health strategies employed in Asia and non-English-speaking Europe. For instance, localized NPIs, specific national childhood immunization schedules, and the integration of traditional medicine are extensively documented in regional databases but are likely overlooked in this study. Therefore, while our study outlines global megatrends, the generalizability of these findings to culturally and regionally specific public health practices should be interpreted with caution. Second, bibliometric analysis mainly uses quantitative metrics, which can highlight research trends and collaboration networks but offer limited ability to assess the academic value and specific contributions of individual studies. Additionally, due to time lags, some recent studies may have low citation counts, potentially underestimating their impact. The inclusion of only published literature may also introduce publication bias. Lastly, while collaboration network analysis shows partnerships, it does not reflect their depth or quality, which could overstate the influence of certain authors or institutions.

To address these limitations, future studies should incorporate a wider range of data sources, such as PubMed, Scopus, and China National Knowledge Infrastructure (CNKI), and combine quantitative and qualitative methods. This approach will help provide a more complete understanding of research in pediatric influenza prevention and control, thereby supporting evidence-based policy and practice in this important public health field.

Conclusions

Research on pediatric influenza prevention and control has undergone three distinct phases, with current studies focusing on interactions with COVID-19, vaccine hesitancy, influenza vaccine efficacy, and antiviral drug resistance mechanisms. Future research should prioritize elucidating influenza mixed infection pathways, accelerating broad-spectrum vaccine development, and innovating antiviral treatment regimens. Concurrently, strengthening public health interventions and health communication mechanisms is crucial for enhancing global influenza prevention and control efficacy among children.

Acknowledgments

We would like to express our gratitude to the Web of Science Core Collection (WoSCC) database for providing the bibliometric data essential to this study. We also acknowledge the developers of CiteSpace software for creating the tool that enabled the visual analysis of the research. Additionally, we thank all peer reviewers and editorial staff for their valuable comments and guidance during the manuscript revision process.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0086/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0086/prf

Funding: This study was supported by Prevention and Control of Emerging and Major Infectious Diseases-National Science and Technology Major Project (No. 2026ZD01910200); Youth Innovation Talent Program in Ordinary Universities of Department of Education of Guangdong Province, China (No. 2024KQNCX168); Guangdong Provincial Hospital of Chinese Medicine National Natural Science Foundation Cultivation Special Project (No. YN2025GZR49); Guangzhou University of Chinese Medicine “Guben” Project-First – level Discipline Capacity Enhancement Project (No. GZY2025GB0115); the State Administration of Traditional Chinese Medicine, under the project ‘A Project for Chinese Medicine on Ying Lv’s Renowned Expert Inheritance Studio’ (No. E43729); Bureau of Science and Technology of Guangzhou Municipality, under the project ‘Mechanism Study on the Regulation of NLRP3-mediated Pyroptosis by Jianer Jiedu Formula for the Treatment of RSV Pneumonia in Children based on the Lingnan DampHeat Theory’ (No. 2024A03J0125); and the Guangdong Provincial Key Laboratory of Research on Emergency in TCM (No. 2023B1212060062).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-1-0086/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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