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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">WASJ</journal-id>
<journal-title-group>
<journal-title>World Academy of Sciences Journal</journal-title>
</journal-title-group>
<issn pub-type="ppub">2632-2900</issn>
<issn pub-type="epub">2632-2919</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">WASJ-8-3-00454</article-id>
<article-id pub-id-type="doi">10.3892/wasj.2026.454</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>From antigenic drift to algorithmic prediction: Emerging paradigms in influenza vaccine design and global effectiveness (Review)</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Hamid Mohammed Amin</surname><given-names>Danyar</given-names></name>
<xref rid="af1-WASJ-8-3-00454" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Hars Bapir</surname><given-names>Dunya</given-names></name>
<xref rid="af2-WASJ-8-3-00454" ref-type="aff">2</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Rasul Abdarahman</surname><given-names>Bnar</given-names></name>
<xref rid="af2-WASJ-8-3-00454" ref-type="aff">2</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Hassan Khdr</surname><given-names>Haider</given-names></name>
<xref rid="af1-WASJ-8-3-00454" ref-type="aff">1</xref>
<xref rid="af3-WASJ-8-3-00454" ref-type="aff">3</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Hamid Sidiq</surname><given-names>Shadi</given-names></name>
<xref rid="af4-WASJ-8-3-00454" ref-type="aff">4</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Ali Amin</surname><given-names>Abdalla</given-names></name>
<xref rid="af5-WASJ-8-3-00454" ref-type="aff">5</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Khalid Ahmed</surname><given-names>Sirwan</given-names></name>
<xref rid="af2-WASJ-8-3-00454" ref-type="aff">2</xref>
<xref rid="c1-WASJ-8-3-00454" ref-type="corresp"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Rzgar Qadir</surname><given-names>Rebwar</given-names></name>
<xref rid="af1-WASJ-8-3-00454" ref-type="aff">1</xref>
</contrib>
</contrib-group>
<aff id="af1-WASJ-8-3-00454"><label>1</label>Department of Nursing, Raparin Technical and Vocational Institute, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq</aff>
<aff id="af2-WASJ-8-3-00454"><label>2</label>College of Nursing, University of Raparin, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq</aff>
<aff id="af3-WASJ-8-3-00454"><label>3</label>Animal Resource Department, University of Raparin, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq</aff>
<aff id="af4-WASJ-8-3-00454"><label>4</label>Department of Medical Labs Technology, Raparin Technical and Vocational Institute, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq</aff>
<aff id="af5-WASJ-8-3-00454"><label>5</label>Department of Chemistry, Faculty of Science and Health, Koya University, Koya, Kurdistan Region 46017, Iraq</aff>
<author-notes>
<corresp id="c1-WASJ-8-3-00454"><italic>Correspondence to:</italic> Dr Sirwan Khalid Ahmed, College of Nursing, University of Raparin, Hajiawa, 109 Sardam Street, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq <email>sirwan.k.ahmed@gmail.com</email></corresp>
<fn><p><italic>Abbreviations:</italic> WHO, World Health Organization; NA, neuraminidase; HA, hemagglutinin; H3N2, hemagglutinin type 3 and neuraminidase type 2; AI, artificial intelligence; mRNA, messenger ribonucleic acid; CRISPR, clustered regularly interspaced short palindromic repeats</p></fn>
</author-notes>
<pub-date pub-type="collection"><season>May-Jun</season><year>2026</year></pub-date>
<pub-date pub-type="epub"><day>26</day><month>03</month><year>2026</year></pub-date>
<volume>8</volume>
<issue>3</issue>
<elocation-id>39</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>05</day>
<month>03</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright: &#x00A9; 2026 Mohammed Amin et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.</license-p></license>
</permissions>
<abstract>
<p>Despite widespread annual vaccination efforts, seasonal influenza continues to represent a substantial global public health burden. The present comprehensive review critically discusses the virological, immunological and epidemiological determinants that constrain the effectiveness of contemporary influenza vaccines. A major challenge lies in the rapid evolutionary dynamics of the influenza virus, particularly through antigenic drift and, less frequently, antigenic shift, which frequently result in mismatches between vaccine strains and the circulating variant. The prolonged lead time required for vaccine production, based on early strain prediction, further increases the likelihood of such mismatches. Host-related factors, including an advanced age, immunosenescence, obesity, comorbid conditions and immunological imprinting, contribute to marked variability in vaccine responsiveness across populations. Furthermore, the majority of currently available influenza vaccines predominantly elicit humoral immune responses, with the comparatively limited induction of cellular immunity, which is essential for durable and broad protection. The virus also employs multiple immune-evasion strategies, including glycosylation masking and the suppression of interferon responses, further complicating vaccine effectiveness. Beyond biological constraints, factors such as vaccine hesitancy, inequitable access, and limitations in public health communication hinder vaccine uptake and the development of herd immunity. The present review further discusses emerging strategies, including mRNA vaccine platforms, broadly neutralizing antibodies, universal vaccine candidates targeting conserved viral epitopes and artificial-intelligence0driven models for improved strain prediction. In conclusion, reducing the global burden of seasonal influenza will require an integrated approach that combines advances in vaccine technology with strengthened public health strategies, enhanced global surveillance and equitable vaccine access.</p>
</abstract>
<kwd-group>
<kwd>seasonal influenza</kwd>
<kwd>vaccine effectiveness</kwd>
<kwd>antigenic drift</kwd>
<kwd>host immune system</kwd>
<kwd>viral evolution</kwd>
<kwd>artificial intelligence</kwd>
<kwd>vaccine hesitancy</kwd>
</kwd-group>
<funding-group>
<funding-statement><bold>Funding:</bold> No funding was received.</funding-statement>
</funding-group>
</article-meta>
</front>
<body>
<sec>
<title>1. Introduction</title>
<p>Influenza is an acute viral respiratory infection that occurs annually and is primarily caused by influenza A and B viruses. It continues to impose a substantial global public health burden, affecting millions of individuals annually and contributing to significant morbidity and mortality worldwide. According to the World Health Organization (WHO), influenza is responsible for &#x007E;290,000 to 650,000 respiratory-related deaths globally each year (<xref rid="b1-WASJ-8-3-00454" ref-type="bibr">1</xref>,<xref rid="b2-WASJ-8-3-00454" ref-type="bibr">2</xref>). The impact of influenza varies considerably from year to year, largely due to rapid viral evolution that results in frequent antigenic changes. This continuous viral evolution, combined with heterogeneity in population immunity, contributes to unpredictable and sometimes highly variable severity of seasonal influenza outbreaks (<xref rid="b3-WASJ-8-3-00454" ref-type="bibr">3</xref>,<xref rid="b4-WASJ-8-3-00454" ref-type="bibr">4</xref>).</p>
<p>Vaccination remains the primary strategy for the prevention of seasonal influenza. Influenza vaccines are designed to elicit immune responses against the strains most likely to predominate during a given influenza season. These vaccines primarily target the viral surface glycoproteins hemagglutinin (HA) and neuraminidase (NA), which are essential for viral entry into host cells and subsequent propagation within the respiratory tract. Vaccine composition is determined based on predictions of circulating seasonal strains generated through coordinated surveillance by the WHO and national health authorities (<xref rid="b5-WASJ-8-3-00454" ref-type="bibr">5</xref>,<xref rid="b6-WASJ-8-3-00454" ref-type="bibr">6</xref>). However, the effectiveness of influenza vaccines demonstrates considerable inter-seasonal variability, typically ranging between 40 and 60&#x0025; (<xref rid="b7-WASJ-8-3-00454" ref-type="bibr">7</xref>,<xref rid="b8-WASJ-8-3-00454" ref-type="bibr">8</xref>). This variability is attributable to factors, such as antigenic mismatch, ongoing viral evolution and heterogeneity in host immune responses. The rapid pace of genetic alterations in influenza viruses represents one of the principal barriers to achieving consistently high vaccine effectiveness. Influenza viruses are subject to continuous genetic variation through antigenic drift, characterized by the accumulation of point mutations in the HA and NA genes. These mutations alter surface proteins, enabling the virus to evade immunity acquired through prior infection or vaccination (<xref rid="b9-WASJ-8-3-00454" ref-type="bibr">9</xref>,<xref rid="b10-WASJ-8-3-00454" ref-type="bibr">10</xref>). Consequently, vaccinated individuals may remain susceptible to infection when circulating strains differ substantially from vaccine strains. Antigenic drift becomes particularly problematic during seasons in which vaccine strains are poorly matched to circulating variants. Evidence indicates that vaccine-virus mismatch significantly reduces vaccine effectiveness and increases the likelihood of breakthrough infections (<xref rid="b11-WASJ-8-3-00454" ref-type="bibr">11</xref>,<xref rid="b12-WASJ-8-3-00454" ref-type="bibr">12</xref>). For example, during the 2014-2015 influenza season, a substantial genetic mismatch between the vaccine and circulating HA type 3 and NA type 2 (H3N2) strains resulted in markedly reduced vaccine effectiveness (<xref rid="b13-WASJ-8-3-00454" ref-type="bibr">13</xref>). In addition to the antigenic drift, influenza viruses may undergo an antigenic shift, a process involving major genetic reassortment that can generate novel viral subtypes. Such shifts may lead to pandemic strains capable of evading existing seasonal vaccines and spreading rapidly within populations. Pandemic strains can evade seasonal vaccines; however, the method through which they function indicates how the virus can spread rapidly within populations despite this (<xref rid="b14-WASJ-8-3-00454" ref-type="bibr">14</xref>,<xref rid="b15-WASJ-8-3-00454" ref-type="bibr">15</xref>). Annual influenza vaccines are formulated based on strain predictions issued by the WHO and national surveillance systems. As vaccine production requires substantial lead time, these predictions are typically made 6 to 9 months prior to the influenza season. This interval increases the risk of mismatch between vaccine strains and circulating viruses due to ongoing antigenic drift (<xref rid="b16-WASJ-8-3-00454" ref-type="bibr">16</xref>,<xref rid="b17-WASJ-8-3-00454" ref-type="bibr">17</xref>). Furthermore, the majority of influenza vaccines contain inactivated or attenuated forms of only three or four viral strains, thereby limiting the breadth of protection (<xref rid="b18-WASJ-8-3-00454" ref-type="bibr">18</xref>,<xref rid="b19-WASJ-8-3-00454" ref-type="bibr">19</xref>). Although quadrivalent vaccines have expanded coverage to include an additional influenza B lineage, protection remains restricted in scope. Ongoing research is focused on the development of broader or universal influenza vaccines capable of conferring cross-strain protection (<xref rid="b20-WASJ-8-3-00454" ref-type="bibr">20</xref>,<xref rid="b21-WASJ-8-3-00454" ref-type="bibr">21</xref>); however, such vaccines are not yet available to the public. Vaccine effectiveness is also strongly influenced by host-related factors. Age, health status and prior influenza exposure can substantially influence vaccine-induced immune responses. Certain populations, particularly older adults and immunocompromised individuals, may exhibit a reduced responsiveness to vaccination (<xref rid="b22-WASJ-8-3-00454" ref-type="bibr">22</xref>,<xref rid="b23-WASJ-8-3-00454" ref-type="bibr">23</xref>). The phenomenon known as &#x2018;original antigenic sin&#x2019;, or immune imprinting, may bias immune responses toward previously encountered strains rather than newly emerging variants (<xref rid="b24-WASJ-8-3-00454" ref-type="bibr">24</xref>). The present review therefore discusses the roles of viral evolution, vaccine design, host immune responses and epidemiological determinants in explaining the persistence of influenza infections despite widespread vaccination.</p>
<p>The present review aimed to: i) Examine the factors that limit influenza vaccine effectiveness; ii) synthesize recent evidence explaining breakthrough infections; and iii) discuss emerging strategies to enhance vaccine performance and global influenza control.</p>
</sec>
<sec>
<title>2. Literature search</title>
<p>The present study was conducted as a structured narrative review to synthesize current evidence on influenza virus evolution, vaccine effectiveness, host-related determinants of vaccine response, and emerging strategies in influenza vaccine design and prediction. The present review aimed to integrate findings from virology, immunology, epidemiology and public-health research to provide a comprehensive and critical overview of factors influencing the global effectiveness of influenza vaccination. Although not designed as a formal systematic review, the study followed a transparent and reproducible search approach to ensure scholarly rigor and breadth of coverage.</p>
<p>A comprehensive literature search was performed using the PubMed/MEDLINE, Scopus, Web of Science and Google Scholar databases to identify relevant publications between January, 2000 and February, 2025. Earlier landmark studies were included where necessary to provide historical context. Search terms combined Medical Subject Headings and keywords related to influenza vaccination and viral evolution, including &#x2018;influenza&#x2019;, &#x2018;influenza vaccine&#x2019;, &#x2018;vaccine effectiveness&#x2019;, &#x2018;antigenic drift&#x2019;, &#x2018;antigenic shift&#x2019;, &#x2018;immune response&#x2019;, &#x2018;immunosenescence&#x2019;, &#x2018;vaccine hesitancy&#x2019;, &#x2018;universal influenza vaccine&#x2019;, &#x2018;mRNA vaccine&#x2019;, &#x2018;genomic surveillance&#x2019;, and &#x2018;artificial intelligence&#x2019;. Boolean operators were applied to refine results, and reference lists of relevant articles were screened manually to identify additional sources.</p>
<p>Studies were included if they addressed influenza vaccine effectiveness, immune responses, viral evolution, vaccine technologies, or public-health determinants of vaccine uptake. Clinical, epidemiological, laboratory and review studies published in the English language were considered. Articles lacking sufficient methodological detail or unrelated to influenza vaccination were excluded. Titles and abstracts were screened for relevance, followed by full-text review of eligible studies. Evidence was synthesized narratively due to the heterogeneity of study designs and outcomes, with emphasis on key themes and emerging trends in vaccine performance, immunological mechanisms, and future vaccine development. Priority was given to peer-reviewed studies, systematic reviews and reports from major public-health organizations to ensure reliability and scientific validity.</p>
</sec>
<sec>
<title>3. Influenza virus evolution and vaccine mismatch</title>
<p>Influenza virus evolution is primarily driven by two mechanisms: Antigenic drift and antigenic shift. These processes result in continuous alterations of viral surface proteins, frequently leading to vaccine mismatch when circulating strains differ from those selected for vaccine production (<xref rid="b9-WASJ-8-3-00454" ref-type="bibr">9</xref>). Such mismatches reduce vaccine effectiveness because viral evolution remains unpredictable while vaccine production timelines are fixed. Consequently, robust global surveillance and regular updates to vaccine formulations are essential to mitigate this challenge. As illustrated in <xref rid="f1-WASJ-8-3-00454" ref-type="fig">Fig. 1</xref>, influenza viruses evolve through gradual mutations (antigenic drift) and major genetic reassortment events (antigenic shift). These mechanisms necessitate frequent vaccine reformulation and, in some cases, facilitate zoonotic transmission events that increase pandemic risk (<xref rid="b9-WASJ-8-3-00454" ref-type="bibr">9</xref>).</p>
<sec>
<title/>
<sec>
<title>Influenza virus and seasonal variability</title>
<p>Seasonal variation in influenza viruses is sufficiently pronounced to require annual reformulation of vaccines (<xref rid="b25-WASJ-8-3-00454" ref-type="bibr">25</xref>). Influenza A and B viruses possess segmented RNA genomes encoding multiple proteins essential for viral replication and immune evasion (<xref rid="b26-WASJ-8-3-00454" ref-type="bibr">26</xref>). The viral envelope is characterized by surface glycoproteins, HA and NA, which are central to viral infectivity (<xref rid="b27-WASJ-8-3-00454" ref-type="bibr">27</xref>). These glycoproteins form the basis of the influenza subtype classification system; for example, &#x2018;H1N1&#x2019; denotes a virus with HA subtype 1 and NA subtype 1. HA mediates viral entry through receptor binding, whereas neuraminidase facilitates viral release by cleaving sialic acid residues. As illustrated in <xref rid="f1-WASJ-8-3-00454" ref-type="fig">Fig. 1</xref>, HA comprises two subunits: The HA1 globular head responsible for receptor binding and the HA2 stalk region that mediates membrane fusion (<xref rid="b28-WASJ-8-3-00454" ref-type="bibr">28</xref>,<xref rid="b29-WASJ-8-3-00454" ref-type="bibr">29</xref>).</p>
<p>Annual vaccine composition is determined through WHO-coordinated surveillance and may require modifications each year. The HA head contains five principal antigenic sites (A-E), which are the primary targets of neutralizing antibodies (<xref rid="b30-WASJ-8-3-00454 b31-WASJ-8-3-00454 b32-WASJ-8-3-00454" ref-type="bibr">30-32</xref>). Mutations within these antigenic sites, and within key positions in the stalk region, enable the virus to evade immune recognition, posing substantial challenges for vaccine development (<xref rid="b33-WASJ-8-3-00454" ref-type="bibr">33</xref>,<xref rid="b34-WASJ-8-3-00454" ref-type="bibr">34</xref>). Influenza B viruses exhibit less genetic diversity than influenza A viruses and are categorized into two lineages: Yamagata and Victoria. Current quadrivalent vaccines include antigens from both influenza B lineages alongside H1N1 and H3N2 strains to broaden protection (<xref rid="b35-WASJ-8-3-00454" ref-type="bibr">35</xref>). The WHO monitors global influenza evolution through the Global Influenza Surveillance and Response System (GISRS), established in 1952(<xref rid="b36-WASJ-8-3-00454" ref-type="bibr">36</xref>). This system provides biannual recommendations for vaccine composition in both the Northern and Southern Hemispheres (<xref rid="b37-WASJ-8-3-00454" ref-type="bibr">37</xref>). Historically, the emergence of novel influenza subtypes underscores the importance of continuous surveillance and rapid vaccine adaptation. For example, the A/H2N2 virus responsible for the 1957 Asian influenza pandemic emerged following earlier H1N1 circulation, illustrating the dynamic nature of influenza evolution (<xref rid="b38-WASJ-8-3-00454" ref-type="bibr">38</xref>,<xref rid="b39-WASJ-8-3-00454" ref-type="bibr">39</xref>).</p>
</sec>
<sec>
<title>Antigenic drift and vaccine mismatch</title>
<p>Antigenic drift refers to the gradual accumulation of amino acid substitutions in the HA and NA surface glycoproteins, particularly within antigenic epitopes (<xref rid="b40-WASJ-8-3-00454" ref-type="bibr">40</xref>). This continuous process enables influenza viruses to alter their antigenicity, thereby evading pre-existing host immune responses. Beneficial mutations allow dominant seasonal variants to emerge and replace previously circulating strains (<xref rid="b41-WASJ-8-3-00454" ref-type="bibr">41</xref>,<xref rid="b42-WASJ-8-3-00454" ref-type="bibr">42</xref>). Although detailed evolutionary tracking is complex due to the large volume of viral samples, modern genomic technologies now enable high-resolution phylogenetic analysis of viral diversification (<xref rid="b43-WASJ-8-3-00454" ref-type="bibr">43</xref>).</p>
<p>In addition to point mutations, genetic reassortment substantially contributes to viral diversification, particularly when multiple influenza subtypes co-circulate. Reassortment between related strains increases genomic variability and enhances viral adaptability (<xref rid="b44-WASJ-8-3-00454" ref-type="bibr">44</xref>,<xref rid="b45-WASJ-8-3-00454" ref-type="bibr">45</xref>). Intra-subtype reassortment can transfer a drifted HA gene onto a genetically advantageous viral background, as observed during the severe epidemics in the 1946-1947 and 2003-2004 seasons (<xref rid="b46-WASJ-8-3-00454" ref-type="bibr">46</xref>,<xref rid="b47-WASJ-8-3-00454" ref-type="bibr">47</xref>). Similarly, the emergence of reassortant H1N2 viruses during the 2001-2002 season, which predominated in 41 countries, highlighted the global impact of such events (<xref rid="b48-WASJ-8-3-00454" ref-type="bibr">48</xref>,<xref rid="b49-WASJ-8-3-00454" ref-type="bibr">49</xref>). Surveillance programs rely on hemagglutination inhibition assays and viral RNA sequencing to monitor antigenic drift in HA and NA (<xref rid="b50-WASJ-8-3-00454" ref-type="bibr">50</xref>). Surveillance programs rely on hemagglutination inhibition assays and viral RNA sequencing to monitor these incremental mutations in HA and NA. Greater attention to neuraminidase antigenic drift, assessed through neuraminidase inhibition assays, may improve vaccine-virus matching and enhance vaccine effectiveness (<xref rid="b21-WASJ-8-3-00454" ref-type="bibr">21</xref>,<xref rid="b51-WASJ-8-3-00454" ref-type="bibr">51</xref>).</p>
</sec>
<sec>
<title>Antigenic shift and pandemic potential</title>
<p>In contrast to antigenic drift, antigenic shift involves abrupt and substantial changes in the antigenic properties of influenza A viruses. Such shifts frequently result in the emergence of antigenically novel viruses capable of causing pandemics (<xref rid="b52-WASJ-8-3-00454" ref-type="bibr">52</xref>). Pandemic influenza viruses often acquire HA and NA genes from animal reservoirs that are antigenically distinct from circulating human strains (<xref rid="b53-WASJ-8-3-00454" ref-type="bibr">53</xref>,<xref rid="b54-WASJ-8-3-00454" ref-type="bibr">54</xref>). These shifts may lead to the replacement of previously circulating strains, as observed during the 1957 H2N2 pandemic, which displaced the earlier H1N1 lineage (<xref rid="b55-WASJ-8-3-00454" ref-type="bibr">55</xref>).</p>
<p>The 2009 H1N1 pandemic virus provides a contemporary example, having emerged through reassortment among avian, human, and swine influenza viruses (<xref rid="b56-WASJ-8-3-00454" ref-type="bibr">56</xref>,<xref rid="b57-WASJ-8-3-00454" ref-type="bibr">57</xref>). As illustrated in <xref rid="f2-WASJ-8-3-00454" ref-type="fig">Fig. 2</xref>, antigenic shift generates entirely new viral subtypes, whereas antigenic drift represents gradual genetic evolution that enables pandemic strains to persist as seasonal variants. The figure emphasizes the role of these processes in generating new viral subtypes and sustaining their circulation in humans. A comparison of the influenza A and B viruses is presented in <xref rid="tI-WASJ-8-3-00454" ref-type="table">Table I</xref>, highlighting the greater variability of influenza A, driven by both drift and shift, and its capacity to cause pandemics, in contrast to influenza B, which undergoes antigenic drift only. Its two lineages, Victoria and Yamagata, are included in quadrivalent vaccines for broader protection.</p>
</sec>
</sec>
</sec>
<sec>
<title>4. Host factors influencing vaccine response</title>
<sec>
<title/>
<sec>
<title>Age-related immune response differences</title>
<p>Despite increasing vaccination coverage over recent decades, influenza-related mortality among older adults remains substantial. Age represents a critical determinant of vaccine responsiveness, particularly in older populations. Reduced vaccine effectiveness contributes to heightened susceptibility to infectious diseases among older adults, largely due to immunosenescence, the age-related decline in immune function (<xref rid="b58-WASJ-8-3-00454" ref-type="bibr">58</xref>). Immunosenescence substantially increases susceptibility to infection and disease severity in elderly populations. Age-associated immune deterioration leads to impaired responses to both pathogens and vaccination (<xref rid="b59-WASJ-8-3-00454" ref-type="bibr">59</xref>). Both the quantity and functional quality of the T-cell compartment decline with age, correlating with diminished vaccine-induced immune responses in older adults. Effective vaccine-induced recall immunity requires balanced T-cell responses that support both memory formation and high-affinity antibody production. With advancing age, T-cell responses tend to favor transient effector activity rather than durable memory or follicular helper T-cell responses. Consequently, the protective efficacy of vaccine-induced antibodies is often reduced in older adults (<xref rid="b60-WASJ-8-3-00454" ref-type="bibr">60</xref>,<xref rid="b61-WASJ-8-3-00454" ref-type="bibr">61</xref>). Declining immune integrity leads to reduced resistance to infectious diseases and diminished vaccine effectiveness. Immunosenescence also increases vulnerability to age-associated chronic conditions, including cardiovascular disease and autoimmune disorders (<xref rid="b62-WASJ-8-3-00454" ref-type="bibr">62</xref>,<xref rid="b63-WASJ-8-3-00454" ref-type="bibr">63</xref>). Age-related reductions in antibody responses to influenza vaccination are closely associated with alterations in T-cell function (<xref rid="b64-WASJ-8-3-00454" ref-type="bibr">64</xref>,<xref rid="b65-WASJ-8-3-00454" ref-type="bibr">65</xref>). Primary lymphoid organs, including the thymus and bone marrow, undergo involution with age, resulting in reduced na&#x00EF;ve lymphocyte production. Ageing is also associated with decreased phagocytic activity and reduced numbers of T- and B-cell progenitors. Chronic antigenic stimulation and increased synthesis of proinflammatory cytokines occur concurrently. Thymic involution significantly reduces the output of na&#x00EF;ve T cells, limiting immune adaptability in older adults (<xref rid="b66-WASJ-8-3-00454" ref-type="bibr">66</xref>). Thymic activity declines progressively from early life, accompanied by structural changes in thymic epithelial cells (<xref rid="b67-WASJ-8-3-00454" ref-type="bibr">67</xref>,<xref rid="b68-WASJ-8-3-00454" ref-type="bibr">68</xref>). As a result, the number of na&#x00EF;ve T cells entering peripheral circulation decreases with age, reducing immune repertoire diversity (<xref rid="b69-WASJ-8-3-00454" ref-type="bibr">69</xref>). Although influenza poses a risk across all age groups, children and older adults remain particularly vulnerable (<xref rid="b70-WASJ-8-3-00454" ref-type="bibr">70</xref>). Children may exhibit less mature immune responses, including reduced memory T-cell formation and antibody production compared with adults (<xref rid="b71-WASJ-8-3-00454" ref-type="bibr">71</xref>). Vaccinated infants often demonstrate lower vaccine-induced protection, while unvaccinated infants remain at greatest risk of severe influenza-related morbidity (<xref rid="b72-WASJ-8-3-00454" ref-type="bibr">72</xref>). Neonates possess relatively immature immune systems, characterized by reduced antigen-presenting cell activity and cytokine production compared with older children and adults (<xref rid="b73-WASJ-8-3-00454" ref-type="bibr">73</xref>).</p>
</sec>
<sec>
<title>Impact of comorbidities</title>
<p>In addition to immunosenescence, comorbid conditions can further impair immune responses to influenza vaccination (<xref rid="b23-WASJ-8-3-00454" ref-type="bibr">23</xref>,<xref rid="b74-WASJ-8-3-00454" ref-type="bibr">74</xref>). Comorbidities exert a substantial influence on vaccine-induced immune responses and overall vaccine effectiveness (<xref rid="b75-WASJ-8-3-00454" ref-type="bibr">75</xref>,<xref rid="b76-WASJ-8-3-00454" ref-type="bibr">76</xref>). Conditions, such as chronic kidney disease, cardiovascular disease, and diabetes mellitus are associated with reduced vaccine immunogenicity (<xref rid="b77-WASJ-8-3-00454" ref-type="bibr">77</xref>,<xref rid="b78-WASJ-8-3-00454" ref-type="bibr">78</xref>). These conditions can impair macrophage and lymphocyte function, thereby weakening post-vaccination immune responses (<xref rid="b78-WASJ-8-3-00454" ref-type="bibr">78</xref>).</p>
<p>Acute infections, including pneumococcal disease and seasonal influenza, are associated with increased morbidity and mortality rates in individuals with cardiovascular disease (<xref rid="b79-WASJ-8-3-00454" ref-type="bibr">79</xref>). Evidence suggests that individuals with cardiovascular disease should receive influenza vaccination as part of comprehensive secondary prevention strategies (<xref rid="b80-WASJ-8-3-00454" ref-type="bibr">80</xref>). Cardiovascular disease-related immune alterations may influence responses to vaccination and inflammatory stimuli. Influenza vaccination may elicit variable inflammatory responses in individuals with coronary artery disease (<xref rid="b81-WASJ-8-3-00454" ref-type="bibr">81</xref>). Influenza vaccination is generally safe in individuals with cardiovascular disease and typically induces protective antibody levels comparable to those in healthy populations. However, individuals with congestive heart failure may exhibit lower post-vaccination antibody titers despite achieving similar seroconversion rates (<xref rid="b80-WASJ-8-3-00454" ref-type="bibr">80</xref>,<xref rid="b82-WASJ-8-3-00454" ref-type="bibr">82</xref>).</p>
<p>Obesity represents a key modifier of immune responses to influenza vaccination. Some studies suggest that individuals with overweight initially demonstrate higher serological responses following vaccination compared with individuals of normal weight (<xref rid="b79-WASJ-8-3-00454" ref-type="bibr">79</xref>). However, obese individuals may exhibit impaired CD8+ T-cell activation and reduced metabolic responses following vaccination (<xref rid="b83-WASJ-8-3-00454" ref-type="bibr">83</xref>). Although individuals with obesity may be more likely to receive influenza vaccination, immune responses may be less robust and less durable (<xref rid="b84-WASJ-8-3-00454" ref-type="bibr">84</xref>), however, many overweighed persons show decreased immune responses (innate and adaptive) to the vaccine and thus make the eventuality of vaccination less efficient (<xref rid="b83-WASJ-8-3-00454" ref-type="bibr">83</xref>). Obesity has also been shown to be associated with a diminished immune response to the influenza vaccine. Experimental models demonstrate that obesity is associated with reduced neutralizing antibody production and impaired viral clearance following vaccination (<xref rid="b85-WASJ-8-3-00454" ref-type="bibr">85</xref>).</p>
</sec>
<sec>
<title>Previous exposure and immunity imprinting</title>
<p>Influenza-related morbidity and mortality remain substantial despite repeated seasonal vaccination programs. The effects of repeated and imprinting seasonal influenza vaccinations were examined to assess the processes and immunological variables influencing influenza vaccine responses (<xref rid="b86-WASJ-8-3-00454" ref-type="bibr">86</xref>). Pre-existing immunity resulting from prior infection or vaccination can influence responses to subsequent influenza vaccination (<xref rid="b87-WASJ-8-3-00454" ref-type="bibr">87</xref>,<xref rid="b88-WASJ-8-3-00454" ref-type="bibr">88</xref>), which influences both the quantity and quality of antibodies generated later in life in response to influenza viruses. Antibody responses later in life are often shaped by early childhood exposure to influenza viruses. This phenomenon, currently commonly termed immune imprinting, reflects both beneficial and detrimental effects of immune history on vaccine effectiveness (<xref rid="b24-WASJ-8-3-00454" ref-type="bibr">24</xref>). Immune imprinting may preferentially stimulate memory B-cell responses to previously encountered strains while limiting responses to novel variants (<xref rid="b23-WASJ-8-3-00454" ref-type="bibr">23</xref>,<xref rid="b24-WASJ-8-3-00454" ref-type="bibr">24</xref>).</p>
<p>Repeated annual vaccination may also influence immune responses to subsequent influenza exposure. Some epidemiological studies suggest reduced vaccine effectiveness among individuals vaccinated across multiple consecutive seasons (<xref rid="b89-WASJ-8-3-00454" ref-type="bibr">89</xref>). However, other studies report sustained or comparable protection with repeated vaccination, indicating mixed evidence (<xref rid="b90-WASJ-8-3-00454" ref-type="bibr">90</xref>,<xref rid="b91-WASJ-8-3-00454" ref-type="bibr">91</xref>).</p>
<p>Vaccine immunogenicity remains a central determinant of vaccine effectiveness (<xref rid="b92-WASJ-8-3-00454" ref-type="bibr">92</xref>). Repeated immunization may alter the immunogenicity of a vaccine, according to previous research (<xref rid="b93-WASJ-8-3-00454" ref-type="bibr">93</xref>). As previously demonstrated, those who had received an influenza vaccine the year before were far less likely to experience seroconversion than those who did not (<xref rid="b94-WASJ-8-3-00454" ref-type="bibr">94</xref>). Repetition of the vaccine may reduce its immunogenicity, which may be one reason. Based on research conducted by Sherman <italic>et al</italic> (<xref rid="b86-WASJ-8-3-00454" ref-type="bibr">86</xref>), the immune response was found to have a lower fold change after many seasonal influenza vaccinations. Using three different vaccine platforms, researchers found that repeated immunizations had a negative impact on antibody binding, antibody affinity maturation, and hemagglutination inhibition responses to H1N1, H3N2 and B strains (<xref rid="b93-WASJ-8-3-00454" ref-type="bibr">93</xref>). Previous findings suggest that repeated vaccination may reduce antibody-secreting cell responses and impair effector B-cell function following subsequent vaccination (<xref rid="b95-WASJ-8-3-00454" ref-type="bibr">95</xref>). Proposed to explain the detrimental consequences of several vaccinations is the phenomena of antigenic imprinting.</p>
</sec>
</sec>
</sec>
<sec>
<title>5. Immunological and molecular mechanisms</title>
<sec>
<title/>
<sec>
<title>Humoral vs. cellular immunity</title>
<p>Influenza vaccines primarily target the hemagglutinin and neuraminidase glycoproteins and function predominantly by eliciting humoral immune responses against these viral surface antigens. Vaccine-induced antibodies play a central role in preventing severe disease by blocking viral entry and enhancing immune clearance through mechanisms such as phagocytosis, complement activation, and antibody-dependent cellular cytotoxicity (<xref rid="b96-WASJ-8-3-00454" ref-type="bibr">96</xref>). However, influenza viruses can evade antibody-mediated immunity through rapid mutation, particularly within the receptor-binding region of hemagglutinin. Consequently, vaccine formulations must be updated annually to match circulating strains. Previous studies have indicated that inactivated influenza vaccines demonstrate reduced effectiveness when circulating viral strains differ antigenically from vaccine strains (<xref rid="b96-WASJ-8-3-00454" ref-type="bibr">96</xref>,<xref rid="b97-WASJ-8-3-00454" ref-type="bibr">97</xref>). By contrast, T-cell-mediated cellular immunity provides an additional layer of protection against influenza infection. CD8<sup>+</sup> T-cells contribute to viral clearance by eliminating infected cells, while CD4<sup>+</sup> T-cells support antibody production through cytokine-mediated activation of B-cells (<xref rid="b98-WASJ-8-3-00454" ref-type="bibr">98</xref>,<xref rid="b99-WASJ-8-3-00454" ref-type="bibr">99</xref>). Individuals with impaired humoral immunity, including older adults and immunocompromised patients, rely heavily on cellular immune responses for protection (<xref rid="b99-WASJ-8-3-00454" ref-type="bibr">99</xref>). Following natural infection, influenza-specific CD8<sup>+</sup> T-cell responses often serve as key correlates of protection due to their breadth and durability (<xref rid="b96-WASJ-8-3-00454" ref-type="bibr">96</xref>,<xref rid="b98-WASJ-8-3-00454" ref-type="bibr">98</xref>). Current influenza vaccines, however, often elicit relatively weak T-cell responses, limiting the development of robust cellular immunity in a number of recipients (<xref rid="b100-WASJ-8-3-00454" ref-type="bibr">100</xref>). Although humoral immunity is frequently prioritized due to the ease of measuring antibody titers, cellular immunity plays an equally critical role in cross-strain protection (<xref rid="b97-WASJ-8-3-00454" ref-type="bibr">97</xref>,<xref rid="b98-WASJ-8-3-00454" ref-type="bibr">98</xref>). Cellular immune responses target conserved viral epitopes, potentially providing broader and longer-lasting protection against diverse influenza strains (<xref rid="b101-WASJ-8-3-00454" ref-type="bibr">101</xref>). In summary, while current influenza vaccines predominantly stimulate humoral immunity, insufficient activation of cellular immunity may limit overall vaccine effectiveness. Future vaccine strategies should aim to induce balanced humoral and cellular responses to enhance durability and breadth of protection (<xref rid="b96-WASJ-8-3-00454" ref-type="bibr">96</xref>,<xref rid="b97-WASJ-8-3-00454" ref-type="bibr">97</xref>).</p>
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<title>Immune evasion by the influenza virus</title>
<p>Influenza A viruses employ multiple strategies to evade detection and clearance by the host immune system (<xref rid="b102-WASJ-8-3-00454 b103-WASJ-8-3-00454 b104-WASJ-8-3-00454" ref-type="bibr">102-104</xref>). A defining feature of these viruses is their extensive genetic and antigenic diversity, driven primarily by antigenic drift and antigenic shift. These mechanisms alter viral antigens, reducing recognition by both innate and adaptive immune responses (<xref rid="b101-WASJ-8-3-00454 b102-WASJ-8-3-00454 b103-WASJ-8-3-00454" ref-type="bibr">101-103</xref>,<xref rid="b105-WASJ-8-3-00454" ref-type="bibr">105</xref>,<xref rid="b106-WASJ-8-3-00454" ref-type="bibr">106</xref>). Antigenic drift involves gradual accumulation of point mutations in genes encoding surface glycoproteins such as HA, resulting in reduced antibody binding while maintaining viral fitness. Antigenic shift involves the reassortment of gene segments between different influenza strains, producing novel viruses with distinct antigenic properties (<xref rid="b101-WASJ-8-3-00454" ref-type="bibr">101</xref>,<xref rid="b102-WASJ-8-3-00454" ref-type="bibr">102</xref>,<xref rid="b104-WASJ-8-3-00454" ref-type="bibr">104</xref>).</p>
<p>The glycosylation of viral surface proteins represents another major immune-evasion mechanism. This process involves the addition of oligosaccharide chains to viral proteins, altering antigenic structure and immune recognition. Glycosylation is also crucial since it may affect HA and NA glycoprotein properties. These proteins are also involved in viral entry and escape. The increased glycosylation of HA, particularly within the globular head region, can mask neutralizing epitopes and reduce antibody binding (<xref rid="b102-WASJ-8-3-00454" ref-type="bibr">102</xref>,<xref rid="b107-WASJ-8-3-00454" ref-type="bibr">107</xref>). Recent H3N2 isolates demonstrate progressively increased HA glycosylation, suggesting selective pressure favoring enhanced immune evasion (<xref rid="b102-WASJ-8-3-00454" ref-type="bibr">102</xref>,<xref rid="b107-WASJ-8-3-00454" ref-type="bibr">107</xref>). Thus, by hiding critical regions from the immune system, glycosylation protects viruses from immune evasion.</p>
<p>The innate immune system constitutes the first line of defense against influenza infection, with interferon signaling playing a central role. Influenza viruses have evolved mechanisms to suppress interferon responses, primarily through the activity of the non-structural protein 1 (NS1). NS1 inhibits interferon production and disrupts host antiviral pathways, thereby enhancing viral replication and persistence. NS1 also blocks host gene expression due to pre-messenger ribonucleic acid (mRNA) processing and export of host mRNAs to the nucleus. Additionally, influenza viruses can inhibit protein kinase R and other antiviral signaling pathways, further weakening host defenses (<xref rid="b105-WASJ-8-3-00454" ref-type="bibr">105</xref>). At the adaptive immune level, the influenza A virus can avoid the human immune response by antigen drift and antigen shift (<xref rid="b105-WASJ-8-3-00454" ref-type="bibr">105</xref>,<xref rid="b108-WASJ-8-3-00454" ref-type="bibr">108</xref>). Mutations within viral epitopes recognized by CD8<sup>+</sup> T-cells also facilitate escape from cellular immune responses, contributing to sustained transmission (<xref rid="b101-WASJ-8-3-00454" ref-type="bibr">101</xref>).</p>
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<sec>
<title>Hypotheses on vaccine-induced immune modulation</title>
<p>Emerging research on vaccine-induced immune modulation highlights the importance of adjuvants and delivery systems in shaping immune memory, durability of protection, and responses to variant strains. Adjuvants can be defined as agents that, administered together with a vaccine, enhance the immune response. They improve immunogenicity and may enhance protection against antigenically variable viruses, such as influenza (<xref rid="b109-WASJ-8-3-00454" ref-type="bibr">109</xref>,<xref rid="b110-WASJ-8-3-00454" ref-type="bibr">110</xref>). Adjuvants range from simple mineral salts to complex lipid-based or particulate systems. The use of adjuvants in vaccination dates back to early observations that aluminum salts enhance antibody production when combined with antigens. Adjuvants are divided into provisors and delivery means. Adjuvants function by activating innate immune pathways, including Toll-like receptors and other pattern-recognition receptors, thereby promoting adaptive immune responses. Delivery systems improve antigen stability and facilitate targeting to antigen-presenting cells and lymphoid tissues (<xref rid="b109-WASJ-8-3-00454" ref-type="bibr">109</xref>).</p>
<p>The adjuvants of a delivery system incorporate the antigen in a carrier, which has a dual function of containing the antigen while also triggering a localized proinflammatory response. This response recruits immune cells to the site of injection, thus enhancing immune activation and memory consolidation. This combination of antigen and adjuvant activates pattern recognition receptor pathways, such as pathogen-associated molecular patterns that are negatively associated with self and positively associated with the production of numerous pro-inflammatory cytokines and chemokines, which in turn activate cells of the innate immune system (<xref rid="b111-WASJ-8-3-00454" ref-type="bibr">111</xref>).</p>
<p>Different delivery platforms, including emulsions, nanoparticles and virus-like particles, can substantially influence the magnitude and durability of immune responses. As an adjuvant, aluminum salts are frequently used to enhance immunological response, as well as aid in the retention of the antigen at the injection site, leading to prolonged immune activation. Emulsions like MF59 and AS03 increase the avidity of antigen for immune cells by enhancing their presentation and consequently, the activity of the immune cells, leading to more robust and durable memory of the immune system. The &#x2018;modeling&#x2019; of viruses is crucial in virosomes and virus-like particles which help to amplify immune responses and increase protection against the subsequent infections (<xref rid="b111-WASJ-8-3-00454" ref-type="bibr">111</xref>).</p>
<p>As a result of antigenic drift, the surface proteins of the influenza virus are constantly modified. This dilutes the matching correlation between the virus prevalent in circulation and the strain used in the vaccine. This mismatch can diminish the effectiveness of the vaccine in preventing infection (<xref rid="b110-WASJ-8-3-00454" ref-type="bibr">110</xref>,<xref rid="b112-WASJ-8-3-00454" ref-type="bibr">112</xref>,<xref rid="b113-WASJ-8-3-00454" ref-type="bibr">113</xref>). The inclusion of some adjuvants and delivery systems into the vaccines has the potential to improve management of memory immune response, which can aid in controlling different strains of viruses and more generously reduce the chances of breakthrough infections. Thus, providing longer protection. Indeed, adjuvants or vaccination alone cannot guarantee no infection will occur. Despite ongoing challenges, seasonal influenza vaccination remains the most effective strategy for preventing influenza infection and its complications, particularly among high-risk populations (<xref rid="b96-WASJ-8-3-00454" ref-type="bibr">96</xref>).</p>
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<title>6. Epidemiological and behavioral factors</title>
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<title>Vaccine uptake and herd immunity</title>
<p>Influenza is a critical respiratory disease that substantially contributes to global morbidity and mortality. Timely and effective vaccination remains the primary strategy for reducing influenza-related illness and its complications (<xref rid="b114-WASJ-8-3-00454" ref-type="bibr">114</xref>). High vaccination coverage contributes to herd immunity, a key factor in controlling the spread of infectious diseases at the population level (<xref rid="b115-WASJ-8-3-00454" ref-type="bibr">115</xref>). When a sufficiently large proportion of the population acquires immunity through vaccination or prior infection, transmission can be significantly reduced. Although a precise herd immunity threshold for influenza is difficult to determine due to antigenic variation, a vaccination coverage of approximately 60-80&#x0025; may be required to reduce transmission substantially (<xref rid="b116-WASJ-8-3-00454" ref-type="bibr">116</xref>). Emphasizing the societal benefits of vaccination has been associated with increased uptake. Achieving high vaccination coverage provides both individual protection and indirect protection for the broader community (<xref rid="b117-WASJ-8-3-00454" ref-type="bibr">117</xref>). It can also be considered a prosocial act, as it benefits others, by offering both personal and indirect benefits to unvaccinated individuals, including those who are too young, immunocompromised, or unable to be vaccinated (<xref rid="b118-WASJ-8-3-00454" ref-type="bibr">118</xref>). Vaccination behaviors are influenced by individual beliefs, perceived norms and the availability of accurate information. Public confidence in vaccination programs is therefore essential for sustaining herd immunity and improving vaccination coverage (<xref rid="b119-WASJ-8-3-00454" ref-type="bibr">119</xref>).</p>
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<title>Timing and availability of vaccination</title>
<p>Influenza affects millions of individuals annually and can result in severe complications, hospitalization and death, particularly among high-risk populations (<xref rid="b120-WASJ-8-3-00454" ref-type="bibr">120</xref>). In low- and middle-income countries, early vaccination has been shown to reduce influenza cases and associated mortality during pandemic simulations (<xref rid="b121-WASJ-8-3-00454" ref-type="bibr">121</xref>). However, the effectiveness of vaccination programs depends not only on timing, but also on distribution capacity, accessibility and healthcare infrastructure. In Europe, multiple manufacturers produce influenza vaccines, and the availability of specific formulations varies by region and procurement policies (<xref rid="b122-WASJ-8-3-00454" ref-type="bibr">122</xref>). Vaccine availability in a given location is influenced by licensing, national recommendations, procurement strategies and healthcare delivery systems (<xref rid="b123-WASJ-8-3-00454" ref-type="bibr">123</xref>).</p>
<p>As influenza seasonality varies geographically, vaccination schedules must be tailored to regional epidemiological patterns. Regional public health strategies should therefore focus on optimizing vaccination timing and improving access for local populations. To broaden the reach of the preventative strategy, regional protocols may emphasize the need of influenza vaccination in the local population&#x0027;s native language (<xref rid="b124-WASJ-8-3-00454" ref-type="bibr">124</xref>).</p>
<p>Of note, two main vaccination approaches are commonly used: Seasonal campaigns aligned with influenza peaks and year-round vaccination strategies in regions without clearly defined influenza seasons. Campaign-based vaccination programs often achieve rapid increases in coverage, particularly during initial implementation. Policymakers should consider local epidemiology, healthcare infrastructure, and population characteristics when selecting optimal vaccination strategies (<xref rid="b125-WASJ-8-3-00454" ref-type="bibr">125</xref>).</p>
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<title>Vaccine hesitancy and misinformation</title>
<p>Vaccine hesitancy has been identified by the WHO as a major global health challenge (<xref rid="b125-WASJ-8-3-00454" ref-type="bibr">125</xref>). Vaccine hesitancy has been observed not only in the general population, but also among healthcare professionals. Healthcare workers play a crucial role in vaccine education, administration and the promotion of public confidence (<xref rid="b126-WASJ-8-3-00454" ref-type="bibr">126</xref>). In recent years, vaccine hesitancy has expanded globally, contributing to the resurgence of vaccine-preventable diseases (<xref rid="b127-WASJ-8-3-00454" ref-type="bibr">127</xref>). Factors contributing to hesitancy include misinformation, distrust in healthcare systems, and reliance on non-evidence-based information sources (<xref rid="b128-WASJ-8-3-00454" ref-type="bibr">128</xref>). Public concerns regarding vaccine safety and effectiveness often intensify during outbreaks and pandemics. This erosion of confidence, commonly termed vaccine hesitancy, represents a significant public health risk affecting both vaccinated and unvaccinated populations (<xref rid="b129-WASJ-8-3-00454" ref-type="bibr">129</xref>). Influenza vaccines are generally well tolerated, with the majority of adverse effects being mild and transient, such as injection-site reactions, low-grade fever and myalgia (<xref rid="b6-WASJ-8-3-00454" ref-type="bibr">6</xref>). Serious adverse reactions are rare, and extensive post-licensure safety evaluations have confirmed a favorable safety profile for seasonal influenza vaccines (<xref rid="b130-WASJ-8-3-00454" ref-type="bibr">130</xref>). Nevertheless, misinformation regarding vaccine safety continues to fuel public concern and reduce vaccination uptake.</p>
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<title>7. Recent advances and future directions</title>
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<title>Toward a universal influenza vaccine</title>
<p>The capacity of influenza viruses to evade immune responses through rapid mutation has intensified efforts to develop a universal influenza vaccine (<xref rid="b128-WASJ-8-3-00454" ref-type="bibr">128</xref>). Conventional vaccines provide limited protection when circulating strains differ antigenically from predicted strains. Universal vaccine strategies aim to confer durable protection against multiple influenza subtypes by targeting conserved viral regions. The HA protein, particularly its conserved stem region, represents a primary target for universal vaccine development (<xref rid="b131-WASJ-8-3-00454" ref-type="bibr">131</xref>). The HA stem evolves more slowly than the highly variable globular head, making it an attractive target for broadly neutralizing antibodies. Broadly neutralizing antibodies that bind conserved HA stem epitopes can inhibit viral fusion and provide cross-strain protection (<xref rid="b132-WASJ-8-3-00454" ref-type="bibr">132</xref>). Novel approaches, including epitope scaffolding and headless HA constructs, have demonstrated promise in eliciting broadly neutralizing antibodies (<xref rid="b133-WASJ-8-3-00454" ref-type="bibr">133</xref>).</p>
<p>Sequential vaccination strategies have also been explored to enhance immune responses to conserved viral epitopes. Incremental exposure to antigenically diverse strains may strengthen cross-protective immunity against multiple influenza subtypes (<xref rid="b128-WASJ-8-3-00454" ref-type="bibr">128</xref>,<xref rid="b134-WASJ-8-3-00454" ref-type="bibr">134</xref>).</p>
<p>Despite these advances, the development of a universal influenza vaccine remains challenging due to the immune system&#x0027;s tendency to prioritize responses to variable HA head epitopes. Redirecting immune responses toward conserved regions will likely require optimized adjuvants, innovative immunogen design and combinatorial vaccine strategies (<xref rid="b135-WASJ-8-3-00454" ref-type="bibr">135</xref>).</p>
<p>Artificial intelligence (AI) approaches are increasingly being applied to identify conserved epitopes and optimize vaccine antigen design. AI-driven models may enhance vaccine formulation and predict vaccine effectiveness across diverse populations. Advances in structural biology continue to reveal novel targets for universal vaccine development (<xref rid="b136-WASJ-8-3-00454" ref-type="bibr">136</xref>).</p>
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<title>mRNA-based vaccines and adjuvant innovations</title>
<p>mRNA-based vaccines enable host cells to produce viral antigens, thereby stimulating targeted immune responses. Unlike traditional vaccines, mRNA vaccines can be rapidly developed and adapted to emerging viral strains. This flexibility makes mRNA platforms particularly well suited for influenza viruses characterized by rapid antigenic evolution (<xref rid="b137-WASJ-8-3-00454" ref-type="bibr">137</xref>,<xref rid="b138-WASJ-8-3-00454" ref-type="bibr">138</xref>).</p>
<p>mRNA vaccines have demonstrated the ability to induce both humoral and cellular immune responses, providing comprehensive protection. Experimental mRNA vaccines targeting conserved HA regions have generated broadly neutralizing antibodies capable of cross-protection against multiple strains (<xref rid="b139-WASJ-8-3-00454" ref-type="bibr">139</xref>).</p>
<p>Adjuvants are incorporated into vaccines to enhance immunogenicity and improve durability of immune responses. Novel adjuvants are being investigated to improve the magnitude and persistence of immune responses elicited by mRNA influenza vaccines. Lipid nanoparticles used for mRNA delivery also function as adjuvants by promoting cellular uptake and immune activation. Toll-like receptor agonists represent another class of adjuvants under investigation for their ability to enhance vaccine-induced immunity (<xref rid="b109-WASJ-8-3-00454" ref-type="bibr">109</xref>,<xref rid="b140-WASJ-8-3-00454" ref-type="bibr">140</xref>).</p>
<p>By allowing accurate genomic changes and improved antigen design, clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technology is emerging as a powerful tool for identifying conserved genomic regions and optimizing antigen design in influenza vaccine development. CRISPR-based approaches enable rapid identification of conserved viral targets and facilitate iterative vaccine optimization (<xref rid="b141-WASJ-8-3-00454" ref-type="bibr">141</xref>).</p>
<p>The integration of mRNA technology, advanced adjuvants and genome-editing tools provides a promising pathway for next-generation influenza vaccines. Future research is required however, to focus on improving durability of protection, expanding clinical trials across diverse populations and ensuring equitable global access (<xref rid="b142-WASJ-8-3-00454" ref-type="bibr">142</xref>).</p>
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<title>Improved surveillance and prediction models</title>
<p>Advances in genomic sequencing technologies enable the rapid analysis of influenza virus evolution and mutation patterns. These technologies facilitate the early detection of emerging strains and provide real-time insights into antigenic changes (<xref rid="b143-WASJ-8-3-00454" ref-type="bibr">143</xref>,<xref rid="b144-WASJ-8-3-00454" ref-type="bibr">144</xref>).</p>
<p>AI models are increasingly used to predict influenza virus evolution and inform vaccine strain selection. Machine-learning algorithms analyze genomic, epidemiological and environmental data to forecast dominant strains for upcoming influenza seasons (<xref rid="b145-WASJ-8-3-00454" ref-type="bibr">145</xref>).</p>
<p>Deep-learning techniques can identify subtle genetic patterns associated with antigenic variation. In order to forecast HA and NA alterations that may evade existing vaccinations, convolutional neural networks have been applied as an example (<xref rid="b146-WASJ-8-3-00454" ref-type="bibr">146</xref>,<xref rid="b147-WASJ-8-3-00454" ref-type="bibr">147</xref>).</p>
<p>Integrating AI-based prediction with genomic surveillance can enhance vaccine strain matching and improve preparedness. Cloud-based technologies facilitate global collaboration by allowing genomic data to be shared among laboratories across the globe. When paired with real-time genetic data, predictive algorithms help bridge the gap between vaccine design and virus evolution (<xref rid="b148-WASJ-8-3-00454" ref-type="bibr">148</xref>).</p>
<p>CRISPR-Cas diagnostics facilitate the rapid identification and characterization of influenza viruses, hence aiding in flu surveillance. A CRISPR-based diagnostic instrument known as Specific High Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK) facilitates real-time monitoring and response strategies through precise detection of viral alterations (<xref rid="b141-WASJ-8-3-00454" ref-type="bibr">141</xref>,<xref rid="b149-WASJ-8-3-00454" ref-type="bibr">149</xref>).</p>
<p>Integrating real-time genetic data with international health networks is essential for influenza surveillance. Predictive models could be further improved by extending AI algorithms to incorporate more varied variables, such as social and environmental elements. Additionally, a promising path for quick strain identification and vaccine adaption is provided by integrating CRISPR techniques with AI-driven genomic surveillance (<xref rid="b150-WASJ-8-3-00454" ref-type="bibr">150</xref>,<xref rid="b151-WASJ-8-3-00454" ref-type="bibr">151</xref>). Sustained investment in genomic surveillance, artificial intelligence, and global data-sharing networks will be essential for improving influenza control and vaccine effectiveness.</p>
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<title>Policy and public health interventions: Advanced strategies for influenza control</title>
<p>Policy initiatives and public health interventions remain critical for reducing the global burden of influenza. Recent developments in encouraging early immunization, overcoming vaccine reluctance and enhancing accessibility indicate great potential in reducing the prevalence of the flu.</p>
<p>Timely vaccination campaigns, improved accessibility, and targeted communication strategies are essential for preventing outbreaks. To guarantee early and extensive vaccine delivery, governments and health organizations are using measures such as &#x2018;flu shot days&#x2019; and mobile immunization units. Research indicates that programs that offer free vaccines or financial incentives can boost uptake, particularly among underprivileged groups (<xref rid="b152-WASJ-8-3-00454" ref-type="bibr">152</xref>,<xref rid="b153-WASJ-8-3-00454" ref-type="bibr">153</xref>).</p>
<p>Vaccine hesitancy continues to pose a major barrier to achieving high vaccination coverage. Recent public health campaigns emphasize transparent communication and community engagement to build trust in vaccination programs. It has been demonstrated that using digital tools for public awareness, such as social media, can successfully refute anti-vaccine propaganda. Personalized reminders and encouragement constitute two behavioral science-based strategies that are becoming more popular for promoting vaccination (<xref rid="b154-WASJ-8-3-00454" ref-type="bibr">154</xref>,<xref rid="b155-WASJ-8-3-00454" ref-type="bibr">155</xref>).</p>
<p>Enhancing the public awareness of influenza risks and the advantages of vaccinations requires educational programs. Programs designed for neighborhood organizations, workplaces and schools to highlight the importance of vaccination in preventing high-risk persons. These approaches reduce logistical hurdles by frequently combining education with vaccine availability at the location of workplaces, schools, or educational institutions (<xref rid="b156-WASJ-8-3-00454" ref-type="bibr">156</xref>,<xref rid="b157-WASJ-8-3-00454" ref-type="bibr">157</xref>).</p>
<p>Ensuring equitable access to vaccines, particularly in underserved and remote communities, remains a key policy priority. Key steps include setting up immunization centers in remote and underserved locations and using technology to optimize vaccine distribution networks. Vaccines are delivered to disadvantaged and distant communities through collaborations with non-governmental organizations and local authorities (<xref rid="b158-WASJ-8-3-00454" ref-type="bibr">158</xref>,<xref rid="b159-WASJ-8-3-00454" ref-type="bibr">159</xref>).</p>
<p>Future strategies should integrate digital technologies, predictive modeling, and international collaboration to optimize vaccine distribution and uptake. Incorporating influenza vaccination into routine immunization programs may further normalize and increase coverage.</p>
</sec>
</sec>
</sec>
<sec>
<title>8. Limitations</title>
<p>The present review has several limitations. As a narrative synthesis, it may be subject to selection bias and does not include formal meta-analysis. Only English-language publications were included, and the rapidly evolving nature of influenza vaccine technologies and AI-based prediction models means that new evidence may emerge following publication. Nevertheless, efforts were made to include recent high-quality studies and authoritative public-health sources to provide a balanced overview of current knowledge.</p>
</sec>
<sec>
<title>9. Conclusion</title>
<p>The prevention of seasonal influenza through vaccination remains a complex challenge influenced by viral evolution, host-related factors, vaccine composition and epidemiological dynamics. Despite advances, such as quadrivalent vaccine formulations, the overall effectiveness of influenza vaccination programs remains constrained by the rapid and continuous evolution of influenza viruses. Antigenic drift remains one of the most significant threats to vaccine performance, as structural changes in viral surface proteins, particularly HA and NA, can reduce the effectiveness of pre-existing immunity. Vaccine-induced protection is also influenced by host-related factors, including immunosenescence, comorbidities and immune imprinting, which contribute to heterogeneous immune responses across populations. The majority of currently available influenza vaccines predominantly induce humoral immune responses, with comparatively limited activation of cellular immunity, which is essential for broader and longer-lasting protection. Beyond biological constraints, vaccine uptake is negatively affected by misinformation, limited access and distrust in public health systems. Nevertheless, emerging technological innovations, including mRNA-based vaccines, novel adjuvants, AI-driven prediction models and universal vaccine strategies, provide promising opportunities to enhance influenza prevention. Achieving meaningful reductions in influenza burden will require coordinated global efforts involving technological innovation, equitable vaccine distribution, public trust, and sustained collaboration between governments, healthcare institutions and communities.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<p>Not applicable.</p>
</ack>
<sec sec-type="data-availability">
<title>Availability of data and materials</title>
<p>Not applicable.</p>
</sec>
<sec>
<title>Authors&#x0027; contributions</title>
<p>DHMA and DHB conceptualized and designed the study. All authors (DHMA, DHB, HHK, BRA, SHS, AAA, SKA and RRQ) contributed to writing, literature review and manuscript revision. All authors read and approved the final manuscript. Data authentication is not applicable.</p>
</sec>
<sec>
<title>Ethics approval and consent to participate</title>
<p>Not applicable.</p>
</sec>
<sec>
<title>Patient consent for publication</title>
<p>Not applicable.</p>
</sec>
<sec sec-type="COI-statement">
<title>Competing interests</title>
<p>The authors declare that they have no competing interests.</p>
</sec>
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</back>
<floats-group>
<fig id="f1-WASJ-8-3-00454" position="float">
<label>Figure 1</label>
<caption><p>Influenza virus variability and pandemic potential: antigenic drift and shift. The image illustrates the evolution of the influenza viruses through antigenic drift and antigenic shift. (Left panel) Influenza virus and seasonal variability: The image depicts influenza A (H1N1 and H3N2) and B viruses, highlighting their key proteins, HA and NA, which are targeted by the immune response. These proteins have high mutation rates, necessitating frequent updates to vaccines. (Middle panel) Antigenic drift and vaccine mismatch: This process involves gradual mutations in the HA protein, particularly in antigenic sites A-E, which can lead to mismatches between circulating strains and vaccine strains, reducing vaccine effectiveness. (Right panel) Antigenic shift and pandemic potential: Antigenic shift occurs when the reassortment of viral genes leads to the emergence of novel strains with the potential for cross-species transmission, such as the swine-origin virus from the 2009 H1N1 pandemic. This process increases the risk of pandemics. NA, neuraminidase; HA, hemagglutinin.</p></caption>
<graphic xlink:href="wasj-08-03-00454-g00.tif"/>
</fig>
<fig id="f2-WASJ-8-3-00454" position="float">
<label>Figure 2</label>
<caption><p>Genetic changes in influenza viruses: Antigenic drift and antigenic shift. The image illustrates the genetic changes in influenza A viruses through antigenic shift and antigenic drift. Avian H3Nx is a subtype of influenza A found in birds, characterized by the H3 hemagglutinin protein and a variety of neuraminidase (N) subtypes. It circulates in wild and domestic birds and occasionally crosses species, posing a potential risk to humans and other animals (<xref rid="b160-WASJ-8-3-00454" ref-type="bibr">160</xref>). Seasonal Human H2N2 refers to a subtype that caused the 1957 Asian flu pandemic. This strain, with H2 HA and N2 NA, circulated seasonally until it was replaced by H3N2 in 1968 (<xref rid="b161-WASJ-8-3-00454" ref-type="bibr">161</xref>,<xref rid="b162-WASJ-8-3-00454" ref-type="bibr">162</xref>). Pandemic human H3N2 emerged in 1968, causing the Hong Kong flu pandemic, and resulted from a reassortment event between avian and human influenza viruses. It continues to circulate seasonally. Seasonal human H3N2 evolved from the 1968 pandemic strain and continues to cause seasonal flu infections, especially affecting vulnerable populations (<xref rid="b163-WASJ-8-3-00454" ref-type="bibr">163</xref>,<xref rid="b164-WASJ-8-3-00454" ref-type="bibr">164</xref>). NA, neuraminidase; HA, hemagglutinin.</p></caption>
<graphic xlink:href="wasj-08-03-00454-g01.tif"/>
</fig>
<table-wrap id="tI-WASJ-8-3-00454" position="float">
<label>Table I</label>
<caption><p>Comparison of influenza A and B.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">Feature/aspect</th>
<th align="center" valign="middle">Influenza A (Refs.)</th>
<th align="center" valign="middle">Influenza B (Refs.)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Subtypes/lineages Mechanism of change</td>
<td align="left" valign="middle">H1N1, H3N2 (main subtypes) (<xref rid="b165-WASJ-8-3-00454" ref-type="bibr">165</xref>)</td>
<td align="left" valign="middle">Victoria lineage, Yamagata lineage (<xref rid="b165-WASJ-8-3-00454" ref-type="bibr">165</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- Antigenic drift: Gradual mutations in HA and NA proteins (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
<td align="left" valign="middle">- Antigenic drift only (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- Antigenic shift: Genetic reassortment between strains (pandemics) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
<td align="left" valign="middle">- Lower variability compared to influenza A (<xref rid="b165-WASJ-8-3-00454" ref-type="bibr">165</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Pandemic potential</td>
<td align="left" valign="middle">High due to antigenic shift (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>) Examples:</td>
<td align="left" valign="middle">Low Antigenic shift does not occur; no history of pandemics (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 1918 H1N1 Pandemic (Spanish flu) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 1957 H2N2 Pandemic (Asian flu) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 1968 H3N2 Pandemic (Hong Kong flu) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 2009 H1N1 Pandemic (swine flu) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Seasonal impact</td>
<td align="left" valign="middle">Causes major seasonal epidemics with significant mortality and morbidity (<xref rid="b165-WASJ-8-3-00454" ref-type="bibr">165</xref>)</td>
<td align="left" valign="middle">Causes seasonal outbreaks, generally milder than Influenza A (<xref rid="b168-WASJ-8-3-00454" ref-type="bibr">168</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Vaccine inclusion</td>
<td align="left" valign="middle">Annual vaccines include:</td>
<td align="left" valign="middle">Included in quadrivalent vaccines:</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- H1N1 (2009 pandemic strain)</td>
<td align="left" valign="middle">- Victoria lineage</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- H3N2 subtype (<xref rid="b169-WASJ-8-3-00454" ref-type="bibr">169</xref>,<xref rid="b170-WASJ-8-3-00454" ref-type="bibr">170</xref>)</td>
<td align="left" valign="middle">- Yamagata lineage (<xref rid="b169-WASJ-8-3-00454 b170-WASJ-8-3-00454 b171-WASJ-8-3-00454" ref-type="bibr">169-171</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">Surveillance</td>
<td align="left" valign="middle">WHO&#x0027;s GISRS monitors circulating strains globally (<xref rid="b168-WASJ-8-3-00454" ref-type="bibr">168</xref>,<xref rid="b173-WASJ-8-3-00454" ref-type="bibr">173</xref>)</td>
<td align="left" valign="middle">Part of GISRS monitoring; included to ensure broader protection in vaccines</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- Biannual updates for northern and southern hemispheres (<xref rid="b169-WASJ-8-3-00454" ref-type="bibr">169</xref>,<xref rid="b172-WASJ-8-3-00454" ref-type="bibr">172</xref>,<xref rid="b173-WASJ-8-3-00454" ref-type="bibr">173</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Examples of reassortment</td>
<td align="left" valign="middle">Genetic reassortment events drive pandemics and diversity (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
<td align="left" valign="middle">Not applicable due to lack of antigenic shift</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">Example: 2009 H1N1 (swine-origin virus combining swine, human, and avian segments) (<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Historical examples</td>
<td align="left" valign="middle">- 1918 Spanish flu (H1N1) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">No historical pandemics; seasonal infections only (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>,<xref rid="b167-WASJ-8-3-00454" ref-type="bibr">167</xref>)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 1957 Asian flu (H2N2) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 1968 Hong Kong flu (H3N2) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="left" valign="middle">- 2009 swine flu pandemic (H1N1) (<xref rid="b166-WASJ-8-3-00454" ref-type="bibr">166</xref>)</td>
<td align="left" valign="middle">&#x00A0;</td>
</tr>
</tbody>
</table>
</table-wrap>
</floats-group>
</article>
