When Assumptions Replace Verification: Influenza Vaccine

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A Structural Audit of DANFLU-2 and GALFLU Influenza Vaccine Trials

Executive Summary

Two large real-world studies assessing high-dose influenza vaccination in adults aged 65 years or older—DANFLU-2 (Denmark, government-sponsored) and GALFLU (Spain, industry-sponsored by Sanofi)—have been widely interpreted as reaching opposing conclusions regarding clinical benefit.

This analysis finds that the apparent contradiction is superficial.
Both studies share a more fundamental structural failure: they begin from the presumption of vaccine effectiveness, inherited from historical laboratory and regulatory claims, and restrict their inquiry to incremental comparisons between formulations.

Neither study re-establishes the causal baseline required for claims of protection in a given influenza season:
in-season immunogenicity, functional neutralization against circulating strains, and absolute effectiveness versus non-vaccination.

As a result, endpoint choice, statistical significance, and narrative tone are shaped more by institutional incentives than by biological verification.
The central scientific question—does the vaccine meaningfully work in this population and season?—is never directly tested.

Five Laws of Epistemic Integrity — Applied Assessment

Law I — Causal Grounding

Violated.
Both studies infer protection without demonstrating a contemporaneous causal chain linking vaccination to neutralizing immunity and laboratory-confirmed infection.

Law II — Referential Continuity

Compromised.
Claims of protection rely on historical immunogenicity data, largely originating from manufacturer studies, rather than evidence generated within the studied populations and influenza seasons.

Law III — Endpoint Integrity

Weakened.
Administrative hospitalization outcomes are treated as valid proxies for biological protection without upstream immunological verification.

Law IV — Counterfactual Availability

Violated.
Despite fully digitalized health systems and the absence of practical sample-size constraints, neither study constructs a non-vaccinated observational control arm.

Law V — Incentive Transparency

Implicit but unacknowledged.
Sponsor incentives influence framing, endpoint interpretation, and conclusion strength, yet are not analytically integrated into the studies’ claims.

Structural Assessment

Sponsor Context and Design Convergence

DANFLU-2, sponsored by the Danish government, adopts a pragmatic registry-based design with conservative conclusions that preserve existing vaccination policy.
GALFLU, sponsored by Sanofi, employs similar real-world methods but advances stronger language, including claims of “superior protection,” aligned with product differentiation.

Despite divergent incentives, both studies converge on the same design constraint:
they compare high-dose versus standard-dose vaccination only, never vaccination versus non-vaccination.

This convergence is not accidental. It reflects a shared institutional reluctance to re-test the hypothesis of absolute vaccine effectiveness.

The Missing Counterfactual Was Feasible

Both Denmark and Galicia maintain population-wide electronic health records with longitudinal linkage across vaccination status, hospitalizations, and mortality.

A target-trial emulation incorporating:

• contemporaneous non-vaccinated individuals,

• propensity-weighted adjustment for baseline risk,

• season-specific follow-up,

was technically straightforward and ethically permissible.

The absence of such an analysis represents institutional avoidance, not methodological limitation.

Immunogenicity Assumed, Not Demonstrated

GALFLU states that “superior protection against laboratory-confirmed influenza has been proved.”
However, the study reports no:

• IgG titer measurements,

• neutralization assays against circulating strains,

• seroconversion or seroprotection rates,

• verification of antigenic match for the studied season.

Protection is inferred from pre-existing laboratory claims, not demonstrated within the cohort itself.

This reverses the correct inferential order:
immunity is presumed, protection is declared, and outcomes are retrospectively interpreted.

Dose Escalation Without Immune Risk Accounting

High-dose vaccination is treated as a benign amplification of benefit.

Yet higher antigen loads imply increased exposure not only to epitopes but also to excipients and innate immune activators.
In older adults—characterized by immunosenescence, inflammaging, and reduced immune tolerance—annual high-intensity stimulation may carry non-trivial biological trade-offs.

Neither study evaluates:

• persistent inflammatory signatures,

• induction or amplification of autoantibodies,

• delayed immune dysregulation,

• non-specific adverse outcomes plausibly linked to immune over-activation.

This omission persists because it occupies a systemic blind spot protected by the “public good” framing of vaccines.

ODP / DFP Analysis (Orthogonal Differentiation Protocol)

Orthogonal Axis 1 — Biological Verification

Both studies score low. Neither generates primary immunological evidence confirming neutralizing immunity in the observed population and season.

Orthogonal Axis 2 — Causal Inference

Inference is constrained by the absence of a true counterfactual. Relative comparisons are performed without validating absolute effect.

Orthogonal Axis 3 — Institutional Incentives

Government and industry sponsors differ in narrative objectives but converge on preserving the assumption of baseline efficacy.

DFP Projection (Decision-Facing Projection)

When projected forward, the current framework:

• perpetuates marginal optimization without re-validation,

• limits policy adaptability across seasons,

• and accumulates epistemic risk as biological assumptions drift from empirical reality.

The system remains internally coherent but externally under-audited.

Strategic Implications

Influenza’s annual antigenic drift renders historical efficacy claims non-transferable by default.
Without re-establishing the full causal chain each season, incremental formulation comparisons lack decision-grade reliability.

Digital health infrastructure already enables the analyses required to close this gap.
Their absence reflects governance priorities, not scientific impossibility.

Conclusion

DANFLU-2 and GALFLU do not represent conflicting scientific truths.
They represent a shared epistemic omission.

Both operate within a framework where vaccine effectiveness is treated as axiomatic rather than empirical.
Incremental differences are measured while the foundational premise remains unexamined.

Until influenza vaccine studies re-establish the full causal chain—from in-season immunogenicity and functional neutralization to laboratory-confirmed infection and clinical outcomes—claims of “superior protection” will remain incentive-aligned assertions, not verified conclusions.

This is not a failure of data access.
It is a failure of epistemic discipline.

References

1. DANFLU-2 Investigators. High-Dose Influenza Vaccine Effectiveness against Hospitalization in Older Adults. N Engl J Med. 2025;393:2291-2302. doi:10.1056/NEJMoa2509907

2. GALFLU Investigators. High-Dose versus Standard-Dose Influenza Vaccine in Older Adults. N Engl J Med. 2025.

3. Hernán MA, Robins JM. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available. Am J Epidemiol. 2016;183(8):758–764. doi:10.1093/aje/kwv254.

4. Goodwin K, Viboud C, Simonsen L. Antibody response to influenza vaccination in the elderly: a quantitative review. Vaccine. 2006;24(8):1159–1169. doi:10.1016/j.vaccine.2005.08.105..

5. Franceschi C, Garagnani P, Parini P, et al. Inflammaging: a new immune–metabolic viewpoint for age-related diseases. Nat Rev Endocrinol. 2018;14(10):576–590. doi:10.1038/s41574-018-0059-4.

Annex — Methodological and Epistemic Improvements

Toward Decision-Grade Influenza Vaccine Evidence

BioPharma Business Intelligence Unit (BBIU)
Technical Annex · Improvement Framework

A1. Re-establish the Causal Chain Before Measuring Marginal Effects

Problem Identified

Both DANFLU-2 and GALFLU measure incremental differences without re-establishing whether the vaccine is biologically effective in the observed population and season.

Improvement Required

Reorder the inferential logic:

1. In-season immunogenicity

   • IgG titers measured post-vaccination

   • Seroconversion and seroprotection rates

2. Functional validation

   • Neutralization assays against circulating seasonal strains

   • Explicit documentation of antigenic match / mismatch

3. Biological efficacy

   • Laboratory-confirmed influenza incidence (PCR-based)

4. Clinical translation

   • Hospitalization

   • Complications

   • Mortality

Without Steps 1–2, Steps 3–4 cannot support claims of “protection.”

A2. Incorporate a Non-Vaccinated Counterfactual Using EHR Infrastructure

Problem Identified

Absolute vaccine effectiveness is never re-tested, despite full digital health records.

Improvement Required

Implement target trial emulation using existing data:

• Eligibility defined at season start

• Three strategies:

  • No vaccination

  • Standard-dose vaccination

  • High-dose vaccination

• Propensity-weighted adjustment for:

  • age

  • comorbidities

  • prior vaccination history

  • baseline healthcare utilization

• Uniform follow-up window

This design:

• avoids placebo ethics

• removes sample-size constraints

• allows absolute and relative effectiveness estimation

A3. Separate Administrative Outcomes from Biological Outcomes

Problem Identified

Hospitalization codes are treated as proxies for biological protection.

Improvement Required

Explicitly distinguish:

• Biological outcomes

  • PCR-confirmed infection

  • viral load

  • symptom duration

from

• Administrative outcomes

  • hospitalization

  • pneumonia coding

  • cause-of-admission ambiguity

Analyses should present:

• biological outcomes as primary evidence

• administrative outcomes as downstream translation

Not the reverse.

A4. Add Immunological Sub-Cohorts Each Season

Problem Identified

Population-level trials generate no immune-level verification.

Improvement Required

Pre-define representative immunological sub-cohorts:

• stratified by age, sex, frailty, comorbidities

• serial sampling:

  • baseline

  • post-vaccination (2–4 weeks)

  • late season

Measured endpoints:

• neutralizing antibodies

• breadth of response

• persistence of immunity

This converts registry trials from black-box outcome studies into mechanistically interpretable systems.

A5. Explicitly Evaluate Dose–Risk Trade-offs in Older Adults

Problem Identified

High-dose vaccination is assumed to be risk-neutral.

Improvement Required

Systematically monitor and report:

• markers of systemic inflammation

• autoantibody induction or amplification

• delayed immune dysregulation

• non-specific hospitalizations temporally associated with vaccination

This does not imply expected harm.
It restores benefit–risk symmetry to dose escalation decisions.

A6. Require Sponsor-Independent Re-Validation of Baseline Efficacy

Problem Identified

Both public and industry-sponsored trials inherit manufacturer claims as axioms.

Improvement Required

For each influenza season:

• baseline efficacy must be re-estimated

• independently of formulation comparisons

• using contemporaneous data

Incremental superiority claims should be conditional on demonstrated baseline effectiveness.

A7. Pre-Register Epistemic, Not Only Statistical, Criteria

Problem Identified

Trials pre-register statistical endpoints but not inferential thresholds.

Improvement Required

Pre-specify:

• what constitutes “biological protection”

• what level of neutralization is considered meaningful

• how discordance between immunology and outcomes will be interpreted

This prevents post-hoc narrative stabilization.

A8. Integrate ODP-DFP as a Decision Filter

Orthogonal Differentiation Protocol (ODP)

Future influenza vaccine trials should be evaluated across orthogonal axes:

• Biological verification

• Causal inference integrity

• Population specificity

• Risk transparency

• Incentive alignment

Decision-Facing Projection (DFP)

Policy conclusions should only be drawn when:

• orthogonal coherence is achieved

• not merely statistical significance

Annex Conclusion

The limitations observed in DANFLU-2 and GALFLU are not technical failures.
They are the result of a system optimized for continuity rather than re-validation.

Digital health infrastructure, modern causal methods, and immunological tools already exist to close these gaps.

Improving influenza vaccine evidence does not require new technology.
It requires restoring epistemic discipline—and accepting that effectiveness must be demonstrated repeatedly, not presumed indefinitely.

Annex 2 — Current Technical Framework

How Seasonal Influenza Vaccines Are Designed Today

B1. Global Surveillance as the Starting Point

Seasonal influenza vaccine design begins with global viral surveillance, coordinated primarily by the WHO Global Influenza Surveillance and Response System (GISRS).

Key elements:

• ~150 National Influenza Centers (NICs) worldwide

• Continuous sampling of circulating influenza A and B viruses

• Genetic sequencing and antigenic characterization

• Monitoring of:

  • strain prevalence

  • geographic spread

  • emerging drift variants

This system does not predict future strains with certainty; it maps current and recent circulation.

B1a. Data Origin and Transparency Characteristics

Primary surveillance data are collected at the national level, through NICs designated by the WHO. These centers receive clinical samples from hospitals and sentinel sites within each country.

Key characteristics:

• Sampling intensity and representativeness vary by country

• Case ascertainment depends on national testing policies and capacity

• Only a subset of detected isolates is forwarded for advanced analysis

Aggregated surveillance outputs (e.g., weekly counts, subtype distribution) are publicly available through WHO platforms such as FluNet, while viral genomic sequences are shared through repositories such as GISAID.

However:

• raw patient-level clinical data are not publicly released

• denominators (who was tested vs. not tested) are incompletely transparent

• criteria for isolate prioritization are not fully standardized across countries

B2. Antigenic Characterization and Drift Assessment

Collected viral isolates undergo:

• hemagglutination inhibition (HI) assays

• genetic sequencing of hemagglutinin (HA) and neuraminidase (NA)

• assessment of antigenic drift relative to prior strains

The goal is to identify:

• dominant circulating lineages

• significant antigenic changes that may reduce prior immunity

• candidate strains likely to dominate the upcoming season

This process is probabilistic, not deterministic.

B3. WHO Vaccine Strain Selection Process

Twice yearly, WHO convenes expert consultations:

• February → Northern Hemisphere recommendation

• September → Southern Hemisphere recommendation

Based on surveillance data, WHO recommends:

• 3 strains (trivalent) or

• 4 strains (quadrivalent)

Typically:

• Influenza A (H1N1)

• Influenza A (H3N2)

• Influenza B (Victoria lineage)

• ± Influenza B (Yamagata lineage, increasingly absent post-COVID)

These are recommendations, not mandates.

B3a. Determination of Predominance

Within the strain selection process, the designation of a strain as “predominant” is not based on prevalence alone.

It reflects a composite assessment of:

• geographic spread and trajectory

• antigenic drift significance

• epidemiological momentum

• temporal feasibility for manufacturing timelines

As a result, predominance is a technical determination, not a purely statistical label.

B3b. Interface with Manufacturing Feasibility

Although pharmaceutical manufacturers do not participate in primary surveillance, industrial feasibility enters the process at this stage.

Specifically, candidate strains are evaluated for:

• growth characteristics (egg- or cell-based platforms)

• antigenic stability during propagation

• expected production yield

• timeline compatibility with seasonal deployment

Strains that are biologically relevant but poorly manufacturable may be deprioritized.

This influence is structural rather than directive:

• manufacturers do not select strains

• but production constraints bound what can realistically be advanced

B4. Translation into National and Regulatory Decisions

Regulatory authorities (FDA, EMA, MFDS, etc.) adopt WHO recommendations with minimal modification.

Key characteristics:

• No requirement to re-prove absolute clinical efficacy each season

• Emphasis on:

  • antigenic similarity

  • manufacturing feasibility

  • continuity of supply

Regulatory review focuses on:

• strain change validation

• manufacturing consistency

• safety comparability

Not on de novo efficacy trials.

B5. Manufacturing Platforms

Most seasonal influenza vaccines are produced using:

Egg-based manufacturing

• Fertilized chicken eggs

• Viral adaptation may introduce antigenic changes

• Long production timelines

Cell-based manufacturing

• Mammalian cell lines

• Reduced egg-adaptation risk

• Still limited global capacity

Recombinant HA platforms

• HA protein expressed in insect or other systems

• Faster scalability

• Less widespread adoption

The platform does not alter strain selection logic, only production characteristics.

B6. Antigen Dose and Formulation Strategy

Standard-dose vaccines contain a fixed amount of HA per strain.
High-dose formulations increase HA concentration per strain.

Rationale:

• counteract immunosenescence

• increase antibody titers

• improve seroprotection rates

Key point:

Dose escalation is justified by immunogenicity metrics, not by repeated seasonal efficacy trials.

B7. Immunogenicity as the Regulatory Surrogate

Approval and annual updates rely on:

• hemagglutination inhibition titers

• seroconversion rates

• seroprotection thresholds

These are treated as validated correlates of protection, despite:

• seasonal variability

• strain mismatch risk

• population heterogeneity

Clinical outcomes are not routinely revalidated each season.

B8. Deployment and Policy Implementation

Once approved:

• vaccination campaigns are launched pre-season

• coverage targets drive success metrics

• effectiveness is assessed retrospectively via observational studies

Policy emphasis is placed on:

• uptake

• logistics

• risk-group prioritization

Not on real-time biological verification.

B9. Summary of the Current System Logic

The current influenza vaccine system operates on the following logic:

1. Global surveillance detects circulating strains

2. Expert committees select candidate strains

3. Manufacturing feasibility constrains translation

4. Regulators approve updates based on immunogenicity and continuity

5. Vaccines are deployed at scale

6. Effectiveness is inferred retrospectively

This framework prioritizes:

• speed

• scalability

• supply stability

over:

• season-specific biological re-validation

• individualized response assessment

B10. Institutional Architecture and Distributed Governance

The global influenza vaccine system is governed through a multi-layered institutional architecture in which authority, funding, procurement, and execution are intentionally separated across distinct organizations.

This structure is not accidental; it reflects decades of attempts to balance scientific authority, political legitimacy, financial capacity, and industrial execution at global scale.

B10a. World Health Organization (WHO)

The WHO functions as the normative and technical authority of the system.

Its core responsibilities include:

• defining global surveillance frameworks (e.g., GISRS),

• convening expert consultations for strain selection,

• issuing technical recommendations and position papers,

• coordinating reference laboratories and standards.

Critically:

• WHO does not finance vaccination programs,

• does not procure vaccines,

• and does not implement national immunization campaigns.

WHO’s authority is therefore epistemic and coordinative, not operational or financial.

B10b. Strategic Advisory Group of Experts on Immunization (SAGE)

SAGE is an independent advisory body convened by WHO.

Its mandate includes:

• issuing global policy recommendations on vaccine use,

• defining target populations (e.g., elderly, high-risk groups),

• advising on prioritization during constrained supply.

Key characteristics:

• members are required to declare conflicts of interest,

• deliberations are consensus-based,

• recommendations are non-binding.

SAGE does not:

• design vaccines,

• select strains,

• approve products,

• or manage procurement.

Its role is policy framing, not execution.

B10c. WHO Prequalification Programme (PQ)

The Prequalification Programme serves as a technical gatekeeper for global vaccine supply.

Functions include:

• assessing manufacturing quality and consistency,

• reviewing safety and production standards,

• enabling vaccines to be purchased by UN agencies and global donors.

PQ does not:

• conduct efficacy trials,

• determine clinical benefit,

• or compare vaccine effectiveness.

Its focus is manufacturing reliability, not biological performance.

B10d. Gavi, the Vaccine Alliance

Gavi is a financing and market-shaping organization, legally and operationally independent from WHO.

Its responsibilities include:

• mobilizing donor funding,

• negotiating vaccine prices and volumes,

• determining which vaccines are financed for eligible countries.

Governance characteristics:

• public–private partnership structure,

• participation of governments, WHO, UNICEF, World Bank, philanthropic actors, and industry representatives (non-voting).

Gavi does not:

• generate scientific recommendations,

• conduct surveillance,

• or evaluate biological efficacy.

Its decisions are conditional on WHO recommendations.

B10e. UNICEF

UNICEF acts as the primary procurement and logistics agent for vaccines financed by Gavi and other multilateral mechanisms.

Responsibilities include:

• issuing tenders,

• signing supply contracts,

• managing global distribution and cold-chain logistics.

UNICEF does not:

• define vaccine policy,

• assess effectiveness,

• or select strains.

Its mandate is execution and delivery.

B10f. National Regulatory Authorities

National regulators (e.g., FDA, EMA, MFDS) retain sovereign authority over vaccine approval and use.

In the context of seasonal influenza vaccines:

• approvals rely on strain-change supplements,

• immunogenicity and manufacturing comparability are emphasized,

• de novo efficacy trials are generally not required annually.

Regulators typically align with:

• WHO recommendations,

• international harmonization standards.

B11. Responsibility Distribution and Structural Accountability Gap

Across this architecture:

• Scientific guidance is issued by WHO and SAGE.

• Financing decisions are made by Gavi and national governments.

• Procurement and logistics are handled by UNICEF and national systems.

• Manufacturing execution is performed by industry.

• Regulatory authorization is granted by national agencies.

Each institution operates within a clearly defined mandate.
However, no single institution retains end-to-end accountability for:

• reassessing baseline biological effectiveness each season,

• auditing the full upstream decision chain from field data to strain selection,

• or systematically revisiting inherited assumptions when new data capabilities emerge.

Responsibility is therefore:

• distributed,

• shared,

• but not centralized.

This creates a structural condition in which:

• resources and authority flow efficiently,

• while epistemic accountability remains diffuse.

Annex 2 Conclusion

Seasonal influenza vaccine design is not a failure of science, but a system optimized for probabilistic control under time constraints.

Its technical architecture assumes:

• historical validity of immunogenicity surrogates

• acceptability of uncertainty

• tolerance for seasonal variability

While surveillance data are largely transparent in aggregated form, the decision logic translating field data into vaccine strains involves technical weighting steps that are only partially visible externally.

This governance model prioritizes robustness, scalability, and continuity.
At the same time, it complicates comprehensive accountability, as no single actor is structurally mandated to challenge foundational assumptions once the system is in motion.

Understanding this framework is essential before evaluating where, why, and how it may require modernization.

Annex 3 — Farmacoeconomics and Industrial Structure

Seasonal Influenza Vaccines: Market Size, Relative Weight, Manufacturing Geography, and Market Dominance

C1. Global Market Size of Seasonal Influenza Vaccines

The global market for seasonal influenza vaccines represents a large, recurrent, and structurally stable revenue stream within the pharmaceutical sector.

Across multiple industry analyses, current annual revenues converge within a narrow band:

• The seasonal influenza vaccine market is estimated at approximately USD 8–9 billion per year at present.

• Medium-term projections indicate growth toward USD 12–13 billion by the end of the decade, driven primarily by:

  • aging populations in high-income countries,

  • expansion of high-dose and adjuvanted formulations,

  • increased policy emphasis on respiratory disease prevention post-COVID.

Unlike many vaccine segments, influenza demand is non-episodic: it recurs annually, independent of outbreaks, which confers exceptional predictability to manufacturers and purchasers.

C2. Share of Influenza within the Global Vaccine Market

The global vaccines market as a whole is estimated in the range of USD 65–85 billion annually, depending on inclusion criteria (routine pediatric vaccines, adult vaccines, travel vaccines, pandemic stockpiles).

Within this context:

• Seasonal influenza vaccines account for approximately 10–13% of total global vaccine revenues.

• This places influenza among the largest single vaccine categories worldwide, comparable in economic weight to entire therapeutic clusters.

This proportion is notable because influenza vaccines:

• do not rely on outbreak-driven demand,

• are supported by standing public-health recommendations,

• and benefit from entrenched procurement mechanisms.

From a pharmacoeconomic perspective, influenza vaccines function as a core revenue anchor within vaccine portfolios rather than as a marginal product.

C3. Manufacturing Geography and Capacity

Seasonal influenza vaccine manufacturing is highly centralized, capital-intensive, and geographically concentrated.

Key structural characteristics include:

• Global production is carried out by approximately 30 manufacturers, but

• more than 85% of worldwide supply is produced by fewer than 7 manufacturers.

Manufacturing capacity is unevenly distributed:

• Europe and North America host a large proportion of legacy egg-based and cell-based facilities.

• Asia-Pacific (Japan, China, South Korea, Australia, India) represents a growing share of both bulk production and fill–finish operations.

• Latin America maintains regional manufacturing and fill–finish capacity, often linked to national immunization programs.

Global seasonal production capacity is estimated at ~1.5 billion doses per year, a figure that has remained relatively stable since before the COVID-19 pandemic.

This capacity constraint is critical: influenza vaccines must be designed, manufactured, released, and distributed within a fixed annual window. Industrial feasibility is therefore inseparable from strain selection.

C4. Dominant Market Participants

The influenza vaccine market operates as a supply-side oligopoly.

A small number of multinational manufacturers dominate global production, distribution, and regulatory engagement. These include:

• Sanofi

• CSL Seqirus

• GSK

• AstraZeneca (primarily live-attenuated platforms)

Alongside these, several state-affiliated or regional manufacturers supply domestic or regional markets, often under technology transfer or licensing arrangements.

While these regional producers are important for local supply security, global market dynamics are set by the dominant manufacturers, who control:

• the majority of bulk antigen production,

• platform know-how (egg-based, cell-based, recombinant),

• and global regulatory interaction.

C5. Pricing Structure and Economic Segmentation

Seasonal influenza vaccines are not economically homogeneous.

The market is segmented into:

• standard-dose inactivated vaccines,

• high-dose formulations,

• adjuvanted vaccines,

• and live-attenuated vaccines.

High-dose and adjuvanted products command price premiums, particularly in older adult populations, justified primarily by:

• higher antigen content,

• enhanced immunogenicity metrics,

• and policy-driven recommendations for elderly cohorts.

Pricing is largely determined through:

• public procurement and tenders,

• national immunization program negotiations,

• and reimbursement frameworks in high-income countries.

This structure reinforces predictable margins and reduces exposure to classic market competition.

C6. Structural Implications for the Upstream Decision Chain

Given the size, concentration, and predictability of the influenza vaccine market:

• strain selection decisions carry non-trivial economic consequences,

• manufacturing feasibility becomes a binding constraint rather than a secondary consideration,

• and continuity of supply is prioritized over experimental variability.

This does not imply improper influence, but it does establish a structural dependency between:

• global surveillance outputs,

• strain selection feasibility,

• and industrial execution.

In pharmacoeconomic terms, seasonal influenza vaccines represent a systemically important product class: too large to fail operationally, and too recurrent to tolerate disruption.

Annex 3 Conclusion

Seasonal influenza vaccines occupy a unique position in global pharmacoeconomics:

• economically significant,

• structurally concentrated,

• and operationally time-bound.

Their design and deployment cannot be understood solely through virology or immunology. They are embedded in an industrial system optimized for scale, reliability, and annual repetition.

Any evaluation of scientific, regulatory, or evidentiary standards surrounding influenza vaccines must therefore account for this economic and industrial architecture, as it shapes not only what is produced—but also what is considered feasible, acceptable, and sustainable within the system.