BACKGROUND: Influenza causes substantial morbidity and mortality in older adults, and conventional inactivated vaccines often elicit suboptimal immune responses in this population. Recent phase II/III randomized controlled trials (RCTs) have evaluated mRNA-based influenza vaccines, but a quantitative synthesis of their immunogenicity in adults aged ≥65 years is lacking. OBJECTIVE: To determine whether mRNA influenza vaccines yield higher seroconversion rates (SCRs) at 29 days post-vaccination compared to licensed inactivated vaccines in adults aged ≥65 years. DESIGN: Systematic review and meta-analysis of RCTs SETTINGS: Hospital, out-patient and community-based RCTs conducted in the USA METHODS: We searched PubMed, Scopus, Web of Science, and Google Scholar from database inception to July 2025 for RCTs reporting SCR at 29 days post-mRNA influenza vaccination in adults aged ≥65 years. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were estimated using a random-effects model. MAIN OUTCOME MEASURE: SCR at day 29 post-vaccination for each influenza strain (A/H1N1, A/H3N2, B/Victoria, B/Yamagata). SAMPLE SIZE: Seven RCTs out of 4 studies comprising 7,114 participants aged ≥65 years were included. RESULTS: Across the seven RCTs (100% RCTs), mRNA vaccines achieved significantly higher SCRs than controls: A/H1N1 (RR 3.41; 95% CI 2.8–4.2), A/H3N2 (RR 3.54; 95% CI 2.9–4.3), B/Victoria (RR 2.83; 95% CI 2.3–3.5), and B/Yamagata (RR 3.34; 95% CI 2.7–4.2). Heterogeneity was high for all strains (I ² >80%). Sensitivity analyses omitting one study at a time confirmed robustness of the pooled estimates. Funnel plots and Egger's test indicated possible small-study effects. Meta-regression found no significant association between vaccine dose and effect size. RISK OF BIAS: Visual inspection of Begg's funnel plots for the A/H1N1, A/H3N2, and B/Victoria strains revealed asymmetry, suggesting the possibility of publication bias HETEROGENEITY: There was significant heterogeneity among studies for A/H1N1, A/H3N2, and B/Victoria strains but not B/Yamagata strain. CONCLUSION: In adults aged ≥65 years, mRNA influenza vaccines elicit substantially higher seroconversion rates across all four seasonal strains compared with licensed inactivated vaccines, suggesting a promising strategy to enhance immune protection in this high-risk population. Findings should be interpreted with caution given the small number of studies available. LIMITATIONS: Low number of studies included limits full assessment of heterogeneity and bias. REGISTRATION: PROSPERO CRD420251108768

BACKGROUND: Messenger RNA (mRNA)-based influenza vaccines represent a promising advancement in seasonal influenza prevention. However, comprehensive evaluation of their serious safety profile is essential as these vaccines progress toward widespread clinical use. While individual randomized controlled trials (RCTs) have reported low rates of serious adverse outcomes, pooled evidence is limited. OBJECTIVE: This systematic review and meta-analysis of RCTs aim to assess the risk of serious adverse events (SAEs) and adverse events of special interest (AESIs) associated with mRNA-based seasonal influenza vaccines in adults. DESIGN: Systematic review and meta-analysis SETTING: All RCTs included in the meta-analysis were carried out in the USA. METHODS: A systematic literature search was done until December 2025. RCTs evaluating mRNA-based influenza vaccines in adults and reporting participant-level data for SAEs and/or AESIs were included. Risk ratios (RRs) with 95% confidence intervals (CIs) were pooled. MAIN OUTCOME MEASURES: Risks of SAEs and AESIs associated with mRNA-based seasonal influenza vaccines in adults, expressed as pooled risk ratios with 95% CIs. SAMPLE SIZE: Seven RCTs (containing 12 datasets) were included in this meta-analysis. The total number of cases in the intervention and comparator groups were 23,754 and 22,806 respectively. RESULTS: The pooled analysis demonstrated no increased risk of SAEs (RR=0.90, 95% CI: 0.64–1.27, P =.56) and AESI (RR=0.76, 95% CI: 0.41–1.36, P =.35) among mRNA vaccine recipients compared with controls. RISK OF BIAS: Based on funnel plots, there is no evidence of systematic asymmetry or absence of smaller studies with null or adverse findings. Risk-of-bias assessment using the Cochrane traffic-light framework indicated low risk across all domains in all included RCTs. HETEROGENEITY: The heterogeneity was low-to-moderate (τ ² =0.08; I ² =27.79%; H ² =1.38) for SAEs and the Q-test indicated statistically significant heterogeneity (Q=14.46, P =.21). For AESIs, heterogeneity was absent (τ ² =0.00; I ² =0.00%; H ² =1.00), with no evidence of between-study variability by the Q-test (Q=4.70, P =.94). CONCLUSIONS: Pooled evidence shows that mRNA-based seasonal influenza vaccines are not associated with an increased risk of SAEs or AESIs compared with established influenza vaccines or placebo. LIMITATIONS: Low absolute number of AESIs limiting detection of extremely rare events, limited long-term follow-up beyond early and intermediate risk windows, and potential differences between trial populations and real-world vaccine recipients. REGISTRATION: CRD420251271174

Accurate and timely viral diagnostics are central to modern clinical care and public health surveillance, guiding patient management, outbreak control, and population-level interventions. Even though advanced molecular technologies such as RT-qPCR, next-generation sequencing, and CRISPR-based assays have transformed viral detection, the diagnostic performance is shaped not only by analytical platforms but by the integrated flow of principles, platforms, and practice (3P framework). In essence, specimen type, timing of collection, transport conditions, and storage critically influence diagnostic sensitivity, which accounts for up to 60-70% of errors before laboratory analysis even begins. Direct detection approaches, including RT-qPCR, digital PCR, sequencing, and antigen assays, are examined as complementary tools rather than competing technologies, each occupying specialized clinical and public health niches. Indirect detection through serological and cellular immune assays is reviewed as a means of assessing exposure, immunity, and population-level transmission. The practical application of diagnostics is further discussed in key clinical contexts, including acute respiratory infections, chronic viral diseases, and arboviral illnesses, highlighting the importance of algorithmic testing strategies and epidemiological context. The real-world interpretation challenges are addressed, that emphasize on the pretest probability, false-positive and false-negative risks. Limitations of current evidence, including variability in study design, lack of standardization, and underrepresentation of low-resource settings, are critically assessed. Finally, emerging technologies such as CRISPR diagnostics, microfluidics, and lab-on-chip platforms are discussed as drivers of decentralized, rapid, and globally accessible testing. When biological principles, diagnostic technologies, and real-world clinical practice are considered together, it becomes clear that the true effectiveness of viral diagnostics does not rest on analytical performance alone. Rather, meaningful impact depends on how well diagnostic tools are integrated into everyday clinical decision making and public health systems. Looking ahead, the greatest advances are likely to come from diagnostic ecosystems that combine rapid detection with real-time data sharing and context-aware interpretation. Such an interconnected approach has the potential to transform viral diagnostics from isolated laboratory tests into continuous safeguards for both individual patients and population health. This review synthesizes current evidence across all stages of viral diagnostics, with particular emphasis on the often-overlooked pre-analytical and interpretative phases that dominate real world diagnostic error.