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Exclusive: Bird Flu Outbreak 40 Miles From Wisconsin Lab Sparks Concern About Gain-of-Function Experiments

A bird flu outbreak in a Wisconsin dairy cattle herd has fueled speculation that gain-of-function research at a nearby university lab may be behind the outbreak.

A bird flu outbreak in a Wisconsin dairy cattle herd has fueled speculation that gain-of-function research at a nearby university lab — where scientists are working to develop a bird flu vaccine for cattle — may have played a role in the outbreak.

Last month, the U.S. Department of Agriculture (USDA) identified what it said was the first known case of highly pathogenic bird flu in a Dodge County, Wisconsin, dairy cattle herd.

The USDA’s Animal and Plant Inspection Service (APHIS) characterized the outbreak as a new “spillover” event — from wildlife to cattle.

The two scientists who conducted the whole genome sequencing for APHIS and identified the virus responsible for the Dodge County outbreak work at the University of Wisconsin-Madison School of Veterinary Medicine, the university confirmed.

Those same scientists — Keith Poulsen, DVM, Ph.D., and Yoshihiro Kawaoka, DVM, Ph.D. — have also co-authored studies on gain-of-function research, including studies related to the H5N1 virus.

One of the scientists, Kawaoka, directs the university’s Influenza Research Institute, known to conduct gain-of-function research on H5N1. Kawaoka was director of the high-security lab in 2019, when it came under scrutiny for a safety breach.

The institute’s lab is about 40 miles from the bird flu outbreak in Dodge County.

Kawaoka is also the co-founder of flu vaccine manufacturer FluGen. And he is among a group of scientists working on the development of a bird flu vaccine for livestock.

Will Cushman, with the University of Wisconsin-Madison’s Office of Strategic Communication, confirmed that virologists Poulsen and Kawaoka are performing H5N1 research. However, he denied that it is gain-of-function research.

The research, partially funded by the federal government, is aimed at better understanding the H5N1 strains spreading from wild animals and circulating on farms in the U.S., Cushman told The Defender.

D1.1 bird flu strain linked to 3-year-old’s death in Mexico

Last month, Poulsen and Kawaoka identified the H5N1 clade 2.3.4.4b genotype D1.1 as responsible for the Dodge County outbreak. The D1.1 genotype contains characteristics that may increase the transmissibility of the virus, including to humans.

Karl Jablonowski, Ph.D., senior research scientist for Children’s Health Defense (CHD), said the Dodge County outbreak “is notable” because national databases do not show “a mammalian host of D1.1 anywhere near Wisconsin” in the past year.

Two “isolated” spillover events involving the D1.1 strain were identified earlier in 2025, in Arizona and Nevada, Reuters reported. APHIS said the Wisconsin spillover event is considered unrelated to those two previous spillovers.

According to APHIS, bird flu viruses circulating among birds and cattle in the U.S. “pose a low risk to the general public.”

However, the World Health Organization reported that the April 8, 2025, death of a 3-year-old girl in Mexico was caused by respiratory complications that developed after the child contracted the D1.1 strain of bird flu.

D1.1 contains mutations that ‘could enhance the virus’s ability to infect human cells’

Several recent journal articles have suggested that D1.1 may have characteristics that make it more virulent, potentially to humans, than previous bird flu strains.

A July 2025 article in Nature characterized new bird flu genotypes — including the D1.1 variant — as having “wide distribution and transmissibility … to cattle.”

A November 2025 article in The Journal of Infectious Diseases showed that the D1.1 variant may be “better adapted to human nasal and airway organoids” than genotype B3.13, the previously dominant bird flu genotype in North America.

“D1.1 does show better adaptation to human respiratory tissues than say, B3.13 in lab models due to its higher replication capacity in human nasal/airway organoids,” said immunologist and biochemist Jessica Rose, Ph.D.

In a December 2024 op-ed for Medscape, Italian physician and freelance health journalist Dr. Roberta Villa suggested there may be a connection between the outbreak of D1.1 and gain-of-function research.

Villa wrote that the publication of the complete viral sequence of D1.1 “highlighted mutations that could enhance the virus’s ability to infect human cells.”

“How do we know this?” Villa asked. “From the highly contested ‘gain-of-function’ studies, which artificially modify viruses to understand which genomic points require the most surveillance — those mutations that can make the infectious agent more virulent or more transmissible between people.”

Villa did not elaborate on the possible link between D1.1 and gain-of-function research.

In 2024, Kawaoka and a team of researchers published research in Nature on how the bovine H5N1 virus can spread systemically in mice and ferrets, and bind to human-type receptors.

History of accidents at University of Wisconsin lab

Since 1990, Kawaoka has been involved in bird flu gain-of-function research. Dr. Anthony Fauci and the Bill & Melinda Gates Foundation (now the Gates Foundation) funded some of that research.

In 2012, Kawaoka and Dutch researcher Ron Fouchier, Ph.D., published a paper in Science revealing how they had modified H5N1 to enable it to spread between ferrets.

The paper sparked an outcry within the global scientific community. A New York Times editorial called the research “An Engineered Doomsday.”

In 2014, Kawaoka again drew attention after The Independent alleged that Kawaoka’s lab created a new strain of the 2009 H1N1 virus with pandemic potential.

In December 2019, a researcher engaged in an experiment involving the transfer of H5N1 between ferrets was potentially exposed to the virus when her air hose broke, according to USA Today. The lab didn’t notify the university’s biosafety committee or the National Institutes of Health (NIH) until February 2020.

In 2013, a researcher at Kawaoka’s lab accidentally pricked a finger with a needle contaminated with a lab-engineered H5N1 virus.

A week later, another lab worker at the same lab spilled a lab-engineered bird flu virus on a gloved hand. Details about the post-spill protocol that followed are unknown.

In 2015, the University of Wisconsin reported “nine other incidents” at the lab to the NIH between 2012 and 2014.

In 2023, the U.S. House of Representatives Committee on Oversight and Government Reform investigated “dangerous gain-of-function research” conducted at the University of Wisconsin.

That same year, Wisconsin lawmakers proposed Assembly Bill 413, which would have shut down gain-of-function research at universities in the state. The University of Wisconsin lobbied against the bill, which was defeated in April 2024.

Trump’s USDA not focused on vaccine solution for bird flu

As bird flu outbreaks have continued, a bipartisan group of 23 U.S. senators last month co-authored a letter urging the Trump administration to develop a “science-based plan” for developing a bird flu vaccine for livestock.

“Any finalized vaccine strategy must take into account feedback from animal health stakeholders, industry experts, and be grounded in sound science,” the letter stated.

Reuters, quoting a USDA spokesperson, reported that the agency considers farmer biosecurity efforts — and not the development of a vaccine — as the most effective means of fighting the spread of bird flu.

In May 2025, the Trump administration cancelled a $700 million contract with Moderna to develop a human bird flu vaccine.

In a 2024 interview with CHD.TV during a bird flu outbreak in Texas that year, Dr. Richard Bartlett suggested that bird flu vaccines were “ready for mass production.”

Flu, or "Flu Related" mortality.

"Why does the CDC estimate deaths related to seasonal flu?"

From the MMWR:

“CDC does not know the exactly the number of people who die from flu each year"

“CDC feels (?) it is important to convey the full burden of seasonal flu to the public.”

“Does the CDC think that influenza causes most P & I deaths?”

“Only a small proportion of deaths in either of these 2 categories are estimated to be flu related.”

“Only 8.5% of pneumonia, and 2.1% of all respiratory and circulatory deaths are flu related.”

COMMENTARY:
Flu — or Flu Related?
How a statistical trick turned a mild virus into a perennial mass‑death narrative
If forty thousand Americans really died of the flu every year, everyone would know someone.
A coworker. A neighbor. A cousin.
But most people can’t name a single one.

Yet every winter, health officials and media headlines remind us: “Up to 40,000 people die from the flu each year.”
It’s a line so familiar that few ever stop to ask a simple question — where does that number come from?

What “flu‑related” actually means
Buried in an official CDC document, quietly updated in 2016, lies a revealing disclaimer:

“Only 8.5 % of pneumonia deaths and 2.1 % of respiratory and circulatory deaths are estimated to be influenza‑related.”

In other words, about 98 % of the deaths counted as “flu‑related” aren’t influenza at all — they belong to enormous statistical categories whose winter increases simply coincide with flu season.

The agency doesn’t actually count flu deaths in adults.
Instead, it models them, using regression formulas that treat seasonal spikes in heart failure and pneumonia deaths as signals of invisible influenza.

When “flu‑like” isn’t flu
Laboratory surveillance reveals the same pattern. Between 1997 and 2014, the CDC tested millions of respiratory samples from Americans reporting “flu‑like illness.”

The numbers tell their own story:

Season range Avg. samples positive for influenza 1997 – 2014 ≈ 15 %

Meaning: roughly 85 % of people with “flu‑like” illness didn’t have influenza virus at all.
They had rhinovirus, RSV, adenovirus, bacterial bronchitis — anything but “the flu.”

The real death certificates
Data compiled by the American Lung Association — drawn from CDC mortality files — paints an even sharper picture.
Between 1999 and 2006, annual influenza‑coded deaths ranged from 257 to 1 812, averaging roughly 1 200 per year.

That’s a rounding error next to the “40,000 deaths” cited in campaigns every winter.
Even the 2016 CDC paper acknowledges that > 90 % of truly influenza‑associated deaths occur among seniors ≥ 65 years, the very group for whom vaccine efficacy is lowest.

The math behind the myth
So how did 1,200 actual deaths become 40,000 “annual flu deaths”?

Through what epidemiologists call the Serfling regression model — a statistical method from the 1960s that estimates “excess winter mortality.”
Here’s the trick:

Analyze baseline deaths in summer when flu activity is minimal.

Subtract that baseline from winter deaths.

Attribute the unexplained difference to “influenza.”

Thus, if 60,000 more people die in January than in July, and only a few thousand are confirmed flu cases, the model still credits tens of thousands of those excess deaths to influenza — sight unseen.

The result is mathematically elegant and empirically hollow.

Why the exaggeration persists
Numbers shape policy — and budgets.
The bigger the burden, the greater the justification for vaccine funding, advertising, and emergency stockpiles. No agency willingly admits it has overstated danger for decades.
And for journalists accustomed to quoting press releases, “flu kills 40 000 people” is easier copy than dissecting statistical models.

It keeps the wheel turning: fear ↔ funding ↔ reinforcement.

The linguistic sleight of hand
Notice how public‑health language fuses flu and flu‑related into one rhetorical blur.
“Flu or flu‑related complications” sounds precise — but it’s a semantic loophole wide enough to drive policy through.
The modifier “‑related” performs the heavy lifting, transforming correlation into causation, modeling into mortality.

When counting stopped, modeling began
Until the early 2000s, CDC published the raw influenza death numbers straight from the National Vital Statistics System.
Once those figures proved too small to justify mass vaccination narratives, the practice shifted: real counts vanished; modeled estimates replaced them.
The “flu season toll” became an annual press release ritual, detached from laboratory confirmation.

The truth hiding in plain sight
If the yearly toll were truly 40,000, you would already know someone who’d died of flu.

But you probably don’t — because the real figure, according to the government’s own data, is closer to one or two thousand, not forty.
Every other “flu death” exists only as a probability inside an algorithm.

Public trust doesn’t die from influenza; it dies from the word “related.”

References to hyperlink for readers
CDC (2016): Estimating Seasonal Influenza‑Associated Deaths
[archived source: web.archive.org/web/20161016153741/http://www.cdc.gov/flu/about/disease/2015‑16.htm]

CDC Weekly Influenza Surveillance Reports, 1997–2014

American Lung Association, Trends in Pneumonia and Influenza Morbidity and Mortality (2010) https://www.lung.org/getmedia/98f088b5- ... rt.pdf.pdf

The math behind the myth.
“Excess‐Mortality Modeling in 30 Seconds”
The CDC’s influenza death estimates come from a Serfling regression, first described in 1963.
Here’s the layman’s version:

Define a baseline – Use deaths from non‑flu months (summer) to predict how many deaths should occur each week if influenza weren’t present. Call that the expected line.

Measure the winter peak – Count all “respiratory + circulatory” deaths each week.

Subtract the baseline from the observed peak – The leftover “extra” deaths are labeled influenza‑associated.

Mathematically:

Flu‑Associated Deaths = Observed R&C Deaths − Expected Baseline

That’s it. No lab verification — just subtraction.

If January’s respiratory + cardiac deaths rise 10 %, the model assumes influenza caused the entire difference, ignoring cold weather, vitamin D dips, hospital staffing gaps, dietary changes, or other seasonal biological stresses.

Australian senate forces answers on why Covid vaccine deaths were not investigated

After US regulators linked child deaths to Covid-19 mRNA vaccines, an Australian senator has demanded to know why reported child deaths in Australia were not escalated for expert causality assessment.

Why can't anyone show us the study showing vaccines save lives?

Where is the study in the US using record-level data showing that kids who are fully vaccinated die less? According to AI, no such study exists. Vaccine mandates are all based on belief, not science.

There are really bad studies using modelling data claiming vaccines save lives, but the models assume vaccines don’t kill people.

Where is the study, using record-level data, showing vaccines save lives? I can’t find it.

What I did find is the CDC 2017 study showing vaccination does NOT save lives.

Where is the study showing it does save lives?

According to AlterAI, there is no such study:

Which raises the question

So why are states mandating vaccines if there no such study? At a minimum they should notify the public that the policy is based 100% on belief and not science.

Please share with your friends. Maybe they can help answer my question.

Portugal Runs H5N1 Bird Flu Outbreak Simulation—Echoing Pre-COVID Pandemic Exercises

Patients refusing to use personal protective equipment, like masks, defined as "threats."

Why This Exercise Draws Attention

Although the simulation occurred in early 2025, the study was submitted in July 2025, accepted in December, and published online January 8, 2026, placing it into the medical literature at a time when international concern over bird flu preparedness is intensifying.

The timing and structure of the exercise are notable.

In the years preceding COVID-19, global health institutions conducted high-level pandemic simulations—including SPARS Pandemic 2025–2028 and Event 201—that modeled coronavirus outbreaks, public messaging challenges, and emergency countermeasures shortly before those scenarios became reality.

This Lisbon exercise follows the same pattern:

a named pathogen,

a simulated outbreak,

documented preparedness gaps,

and publication after the fact to formalize the response framework.

The study documents preparedness planning.

It confirms that bird flu is now being actively rehearsed as a plausible next pandemic scenario, not only in abstract policy discussions, but through operational simulations involving frontline civilian healthcare systems.

Was the exercise solely for preparedness, or does it function as early-stage coordination for future response architectures?

Op-Ed in THE HILL on Bayer and Big Ag's "Get Out of Jail Free" scheme. Lots of links. Great comparison to the vaccine liability shield. Wonderful discussion of this issue.

The game Monopoly was patented in 1904, updated in 1935. Unregulated monopolies and near-monopolies like Bayer are nothing new in America.

Almost 40 years ago, the federal government granted vaccine manufacturers immunity from people who might otherwise like to sue those companies for vaccine injuries. Now pesticide companies are trying to secure similar legal shields.

It’s easy to see why. After the National Childhood Vaccine Injury Act became law, the vaccine market began growing at a rapid clip and has never been the same since. More than 40 shots for double the amount of diseases have been added to the childhood vaccine schedule in the U.S. — more than in any other developed nation.

In 1986, the pharmaceutical lobby claimed drug companies needed a liability shield to make the market for vaccines viable. They invest many years and many millions of dollars on research and development for new vaccines and patents. Costly lawsuits signal to markets that the risks of a vaccine might outweigh the rewards. That could suppress demand, forcing companies to leave the vaccine market altogether. Such a departure, they argued, would harm public health.

In lieu of legal recourse, the bill established the National Vaccine Injury Compensation Program as an “alternative remedy to judicial action for specified vaccine-related injuries.”

Whatever its intentions, the compensation program has too often added insult to injury for victims of vaccine injury. Payouts are limited to $250,000 for “actual and projected pain and suffering and emotional distress,” but few ever receive that much. Reporting methodologies are shoddy, and those who have tried to receive compensation through the program say the meager payout — usually amounting to a few hundred dollars — isn’t worth the hassle and headache.

Experts estimate that only between 1 percent and 10 percent of cases are even recorded in the Vaccine Adverse Event Reporting System. Under Health and Human Services Secretary Robert F. Kennedy Jr., Make America Healthy Again advocates have called out the vaccine carve-out act for distorting incentives in the vaccine market. Amid growing public awareness, Rep. Paul Gosar (R-Ariz.) has filed a bill with 31 sponsors that would repeal it.

In their quest for similar liability shields, producers of agrichemical products — often known as Big Ag — know they can’t be as transparent as the pharma lobby was in 1986. So, they tried to sneak the provision into a house appropriations bill, with language that obscured the obvious. According to Meryl Nass, a former doctor and physician researcher, Section 453 of the Interior and Environment House Appropriations Bill “grants pesticide manufacturers de facto immunity from liability for injuries caused by exposure to their products, shielding them from accountability.”

Thanks to pushback from activists, including Nass, Section 453 was defeated in both the House and the Senate.

Big Ag has therefore shifted tactics, setting its sights instead on the new farm bill. According to sources inside the Agriculture Department, the same language for the immunity provision from 2024 is planned to be included in this year’s bill. Section 10204 would grant pesticide manufacturers de facto immunity and erect a liability shield for all chemicals regulated under the Federal Insecticide, Fungicide, and Rodenticide Act; Section 10205 would remove states’ power to create local regulations.

In addition, under the guise of the Modern Ag Alliance, chemical companies are working to pass liability shield laws at the state level. They have already succeeded in Georgia and North Dakota, and state efforts will likely continue in future legislative cycles. Their website claims that glyphosate-based pesticides are the “backbone of modern farming” and that lawsuits against the manufacturers of the products have been “scientifically unsound.”

However, several courts have disagreed. Three initial lawsuits against Monsanto (Johnson v. Monsanto, Hardeman v. Monsanto, and Pilliod et al. v. Monsanto) ruled in favor of the plaintiffs, to the tune of $289 million, $80 million and $2 billion, respectively.

Bayer has already spent a huge amount of money — almost $11 billion — to settle almost 100,000 lawsuits involving Roundup. The most recent judgment against Bayer, in Missouri for just over $600 million, brings the company’s total loss closer to $12 billion.

Shielding private companies from liability blunts the strong market incentives companies otherwise receive to make their products and services as safe as they can. If injured customers can sue them, any business, whether that be a restaurant or car manufacturer, has strong reasons to create products and services that do not endanger their customers. Successful lawsuits also send a signal to other potential customers: proceed with caution.

The agri-chemical industry prefers to operate under cover of opaque legalese. And while many niche public interest groups have caught on to their tricks and have been diligently ringing the alarm, it will take more than a few activists to win this fight. The chemical companies have been relentless in their pursuit to maintain legal protections despite the potential hazards to consumers, particularly American farmers, whose persistent exposure to agrichemical products puts them at great risk.

If the most recent liability shields succeed, safety incentives for powerful industries will collapse while injuries mount and taxpayers foot the bill for the fallout via increasing rates of chronic disease. Unless the public demands transparency and defeats these hidden immunity clauses once and for all, the next generation will inherit a government that fails to offer just recourse and a food system that poisons them.

Jennifer Galardi is senior policy analyst for restoring American wellness in the Heritage Foundation’s DeVos Center.

UPDATE: Dementia & Alzheimer's Disease Cure Protocol

Dementia & Alzheimer’s Disease Cure Protocol

Fenbendazole 150mg every other day with dinner for 30 days, and repeat every 4 months

Ivermectin 12mg every evening with dinner indefinitely

Low dose lithium orotate 4.8mg capsule in the morning with breakfast and in the evening with dinner indefinitely

VIR-X immune support 2 capsules in the morning with breakfast indefinitely (Quercetin is a critical ingredient in VIR-X, and as per research studies similar to Ivermectin it displayed capabilities against tauopathy by inhibiting the hyperphosphorylation of the tau protein, thus its anti-prion activity helps to reverse Alzheimer’s Disease)

Removal of sugars and carbohydrates, and replacing table sugar with a zero glycemic index, zero calorie, keto friendly rare sugar like FLAV-X

Creatine Monohydrate 4 x 500mg capsules every evening with dinner indefinitely

Longtime readers know the full backstory of my mother’s AD and her battles with a deranged NYC gerontologist, so I am reposting the updated article here for all of this Substack’s newest subscribers.

BREAKING: CDC SHRINKS ROUTINE CHILDHOOD VACCINE SCHEDULE BY ~55 DOSES

The largest rollback of routine childhood vaccination in U.S. history.

Today, the CDC formally adopted a revised childhood and adolescent immunization schedule, following a Presidential Memorandum directing alignment with international best practices.

This marks the largest rollback of routine childhood vaccination in U.S. history.

After reviewing peer-country schedules and the scientific evidence underlying them, federal health leadership acknowledged that we are hyper-vaccinating our children.

The result is a dramatically smaller routine childhood vaccine schedule, cutting approximately 55 routine doses.

This is a major victory — even as serious safety concerns remain for the vaccines that continue to be recommended.

BREAKING: Study Identifies Over 300 Peer-Reviewed COVID-19 "Vaccine" Cancer Cases Across 27 Countries — Journal Hit With Cyberattacks

Major cancer journal confirms global turbo cancer safety signal as criminal cyberattacks possibly linked to PubPeer disrupt access to the study.

For several years now, clinicians, pathologists, and independent researchers have been documenting turbo cancers following COVID-19 vaccination: sudden relapses, explosive disease acceleration, rare malignancies appearing out of nowhere, and tumors localizing to injection sites or draining lymph nodes. These signals have been visible for some time — but deliberately fragmented, dismissed as coincidence, or buried under claims that “case reports don’t count.”

That excuse has now completely collapsed.

A newly published peer-reviewed systematic review in Oncotarget — authored by Charlotte Kuperwasser, PhD, and Wafik S. El-Deiry, MD, PhD — is the first to formally assemble and analyze the entire published literature on cancer temporally associated with COVID-19 vaccination and SARS-CoV-2 infection.

Importantly, while this article has been accepted, published, and assigned a publication date, the journal has disclosed that it is currently unable to add the paper to its live journal index due to an ongoing malicious cyberattack on its servers. According to a statement now posted on Oncotarget’s website — and relayed directly to us by Dr. El-Deiry — the journal experienced sustained cyber intrusions in December 2025 and January 2026, which were reported to the FBI, with attacks continuing into the present. In the meantime, Dr. El-Deiry has provided a link to access this important paper. You can read it here.

The journal further states that it is investigating whether individuals associated with PubPeer (PubSmear Mob) may have engaged in or facilitated cybercriminal activity, including server hacking, taking journal websites offline, and manipulating Google search results to suppress journals and scientists. Oncotarget reports that it is currently in contact with federal law-enforcement agencies regarding identified suspects.

DMED and CDC COVID Data Scandals

Inconvenient Truths? Just change the data. That's the way you do it.

DMED and CDC COVID Data Scandals
The initial report published by malone.news published Jan 03, 2026 0800h relied on an AI system (alter.systems) that generated links and information which later could not be verified. After further investigation, it became clear that the AI had fabricated some of those links and associated information. Therefore, some of the conclusions drawn were incorrect. This report has been updated to reflect those errors.

Executive Summary
The DMED (Defense Medical Epidemiology Database) scandal, or, more accurately, data manipulation revelation, was one of the most consequential disclosures of the entire COVID era. It cut to the core of how epidemiological data was curated, “corrected,” and used to sustain the official safety narrative during the COVID crisis.

DMED is the U.S. military’s central medical surveillance database, maintained by the Defense Health Agency (DHA). It contains decades of anonymized medical records for active-duty personnel, tracking everything from injuries and illnesses to vaccinations. Because service members undergo regular medical exams, DMED offers a cleaner epidemiological dataset than civilian databases.

During 2021–2022, several Department of Defense whistleblowers (notably including Drs. Theresa Long, Samuel Sigoloff, and Peter Chambers) identified anomalous spikes in numerous diagnostic categories starting in 2021, precisely coinciding with the mass COVID vaccination campaign among active-duty troops.

Since Secretary Kennedy was confirmed, there have been reviews of CDC's information, data-gathering, and management practices. The HHS Office of the Inspector General (OIG) announced in Nov 2025 that it anticipates auditing “CDC’s Compliance With Federal Records Management Requirement”. An audit of VAERS COVID vaccine-associated mortality data has also been performed.

Findings to date lead to the same undeniable conclusion: The CDC’s internal data system was fundamentally unable to differentiate objective science from its own public relations narrative.

They didn’t merely mishandle health data; they rewrote medical history to protect institutional credibility. For the first time, these admissions exist in official federal documents, not whistleblower leaks. This gives them legal and historical permanence: a bureaucratic confession that data manipulation occurred by design, not by accident.

The Public Health Data COVID Fraud Engine
Three key forces drove the COVID data fraud at both the DoD and CDC.

Pressure:
The military side faced existential pressure; any admission of mass injury would mean admitting combat unfitness and massive disability liabilities.

The civilian/HHS/FDA/CDC side experienced both internal and external pressure to maintain the “safe and effective” narrative, under the justification that any data contradicting it would increase vaccine hesitancy and thereby cause avoidable deaths.
Data rewriting removed the pressure signal.

Opportunity:
The administrators and oversight apparatus sat at the nexus, with full access to financial levers and data pipelines. Weak internal controls created the opportunity gap: the breach through which truth evaporated.

Rationalization:
The CDC and DoD’s communications divisions crafted the justificatory narratives, which were that “misinterpretation of preliminary data” would harm public trust, legitimizing suppression and editing.

As these forces and opportunities aligned, they formed an autonomous fraud engine:

Institutional Pressure + Unsupervised Access + Ethical Justification → Systemic Deception

The fraud triangle then evolved into a permanent engine of denial:

Pressure fueled the development of a censorship-industrial complex (fear of panic or liability).

Opportunity ensured manipulability (lack of immutable data logs, so that data could be changed later on).

Rationalization re‑branded corruption as benevolence (“no need to alarm the public”).

Thus, the bureaucratic corruption perpetuated itself, immune to correction, until it was overwhelmed by whistleblowers, audits, and external political disruption.

Pathogenic Priming and Influenza Vaccination

Otherwise known as "Original Antigenic Sin" or immune imprinting

Pathogenic Priming and Influenza Vaccination
Pathogenic or Pathologic priming refers to a situation where prior exposure, through infection or vaccination, alters future immune responses in a maladaptive way. Rather than preparing the immune system to respond effectively to a new but related strain, that earlier exposure “locks in” an outdated immune blueprint.

Result: the immune system preferentially reactivates old antibodies and T cells tuned to the priming strain, instead of generating new, strain‑specific defenses.
In simple terms: your immune system becomes trained to fight the last flu, not the current one.

Other terminology: Original Antigenic Sin, immunological imprinting, antigenic imprinting, back-boosting, negative interference, primary addiction, antigenic seniority, viral interference, immune interference, antigenic fixation, and immune imprinting.

So what is pathogenic priming, immune imprinting or “original antigenic sin”? Here is one explanation from a group of influenza virus researchers, investigating differently immunologically biased age groups in their responses to different influenza virus groups (clades):

“We define immune imprinting as a lifelong bias in immune memory of, and protection against, the strains encountered in childhood. Such biases most likely become entrenched as subsequent exposures back-boost existing memory responses, rather than stimulating de novo responses [1]. By providing particularly robust protection against certain antigenic subtypes, or clades, imprinting can provide immunological benefits, but perhaps at the cost of equally strong protection against variants encountered later in life.”

Here is the reference [1] that is being cited above, for those who are passionate about following all the leads down the various rabbit holes. This reference nicely addresses the use and limitations of the two terms “immune imprinting” and “original antigenic sin”, finding the former term a generally better fit to the actual data than the latter:

From Original Antigenic Sin to the Universal Influenza Virus Vaccine. Henry C, Palm A-KE, Krammer F, Wilson PC. Trends Immunol. 2018;39: 70–79.

The authors of this article provide a very nice summary of the issues at hand, which are also directly applicable to coronavirus vaccines and evolved SARS-CoV-2 variants:

“Antibody responses are essential for protection against influenza virus infection. Humans are exposed to a multitude of influenza viruses throughout their lifetime and it is clear that immune history influences the magnitude and quality of the antibody response. The ‘original antigenic sin’ concept refers to the impact of the first influenza virus variant encounter on lifelong immunity. Although this model has been challenged since its discovery, past exposure, and likely one’s first exposure, clearly affects the epitopes targeted in subsequent responses. Understanding how previous exposure to influenza virus shapes antibody responses to vaccination and infection is critical, especially with the prospect of future pandemics and for the effective development of a universal influenza vaccine.”