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Post Fauci NIH can’t help itself. Still misleading public about severity of COVID

Published

11 months ago

8 minute read

From the Brownstone Institute

By Ian Miller

NIH’s Latest Desperate Attempt to Incite Fear

The response to the Covid-19 pandemic revealed many concerning aspects of how government functions and how committed individuals and institutions are to maintaining their preferred narratives.

Truth, data, science, evidence…apparently none of those matter relative to the importance of ensuring the public complies with their desired behavior. Perhaps no single individual has been a better representation of the symbiotic relationship between government officials and media members, as well as their ceaseless commitment to ideological priorities, than Dr. Anthony Fauci.

Fauci’s NIAID and its parent organization, the National Institutes of Health, have been two of the most prolific spreaders of ideologically motivated misinformation ever during the pandemic. But Fauci is no longer part of NIH, having departed for the considerable financial rewards available from the private sector.

So as a result of his timely exit, we must finally be witnessing improvements regarding government studies and communication, right? Right?

Not exactly.

Government Covid Misinformation Continues Unabated

A triumphant, breathless press release from the National Institutes of Health was just released in the past week covering a new study that claimed a horrifying new conclusion. Contracting Covid-19 once is bad, but God forbid you experience two bouts of the virus…It’s terrifying.

That’s their claim resulting from utilizing massive volumes of “health data” on over 200,000 Americans who they believe had Covid at least once over a two-and-a-half-year period from 2020-2022.

“Those individuals were originally infected between March 1, 2020-Dec. 31, 2022, and experienced a second infection by March 2023. Most participants (203,735) had Covid-19 twice, but a small number (478) had it three times or more,” the study says.

The conclusion, is at first glance, concerning.

“Using health data from almost 213,000 Americans who experienced reinfections, researchers have found that severe infections from the virus that causes COVID-19 tend to foreshadow similar severity of infection the next time a person contracts the disease. Additionally, scientists discovered that long COVID was more likely to occur after a first infection compared to a reinfection,” the NIH summary claims.

That sounds pretty bad. If you get infected a second time, you’re likely to experience a severe case of Covid. Right?

Except that is a completely inaccurate conclusion based on the limited data presented.

“About 27% of those with severe cases, defined as receiving hospital care for a coronavirus infection, also received hospital care for a reinfection. Adults with severe cases were more likely to have underlying health conditions and be ages 60 or older. In contrast, about 87% of those who had mild Covid cases that did not require hospital care the first time also had mild cases of reinfections,” the researchers write.

And there’s the real story, hidden in plain sight.

We know from years of experience that Covid significantly impacts those who are in poor health, have underlying conditions, or are older AND in poor health. We also know that a very small percentage of Covid cases require treatment in a hospital setting.

All this study shows is that those who are in poor health, have underlying conditions, or are older, are more likely to need additional care if they get Covid a second time. Even then, 73% of those who had a second infection and were hospitalized the first time did not need hospitalization for the second infection. Sure enough, the vast, vast majority of those who had mild Covid cases the first time had mild Covid cases the second time.

The protection from natural immunity is highly important and generally durable, though less so when an individual with poor underlying health has contracted the virus. This is nothing new. But that didn’t stop the new head of the NIH from spouting some impressive fear-mongering and bad science.

NIH Can’t Stop Getting Things Wrong

Dr. Monica Bertagnolli posted a link to the study on X, and a short summary. She repeated the same line about the severity of Covid reinfections, which were intended to undermine the importance of natural immunity.

And more importantly, she claimed that the results underscore “the importance of preventing infection.”

After analyzing data from 200K Americans who had #COVID19 twice, researchers found that a severe #COVID case tended to foreshadow a similarly severe infection the second time, underscoring the importance of preventing infection[.]

Except that’s an impossibility. SARS-CoV-2 is an endemic virus. It will never be eliminated. It will never be stopped. Infection cannot be avoided. Vaccinations don’t prevent it, masks surely are ineffective, and any public interaction may result in an infection.

There simply is no way to prevent infection, which is why some countries have now reported that roughly 70% of their population, even with masking and vaccination, have tested positive. Telling those at risk to try to avoid infection is irresponsible and inaccurate. So why is this coming from the NIH?

Sure enough, these researchers also accidentally made the case for natural immunity. When studying the nonexistent phenomenon of “long Covid,” they found that those who had typical, longer-lasting effects from viral infections had bigger reactions after their first infection.

“Scientists also discovered that regardless of the variant, long Covid cases were more likely to occur after a first infection compared to a reinfection,” the study says.

Why is that? Because of natural immunity.

Under Anthony Fauci, they spent years downplaying it. They continue to undermine it in 2024. But the reality and the science continue to prove that natural immunity is protective and durable, and this is especially true for those in good health and younger age groups. Imagine if government agencies had been willing to admit this in 2020 instead of pointlessly locking down all of society in order to somehow prevent a virus that cannot be prevented.

That would have been the correct evaluation and communication.

But since when have government agencies handled a single aspect of Covid correctly?

Republished from the author’s Substack

Author

Ian Miller

Ian Miller is the author of “Unmasked: The Global Failure of COVID Mask Mandates.” His work has been featured on national television broadcasts, national and international news publications and referenced in multiple best selling books covering the pandemic. He writes a Substack newsletter, also titled “Unmasked.”

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Pentagon agency to simulate lockdowns, mass vaccinations, public compliance messaging

Published on June 12, 2025

By

From LifeSiteNews

By Tim Hinchliffe

With lockdowns, mass vaccination campaigns, and social distancing still on the table from the last around, it appears that AI and Machine Learning will play a much bigger role in the next.

DARPA is getting into the business of simulating disease outbreaks, including modeling interventions such as mass vaccination campaigns, lockdowns, and communication strategies.

At the end of May, the U.S. Defense Advanced Research Projects Agency (DARPA) put out a Request for Information (RFI) seeking information regarding “state-of-the-art capabilities in the simulation of disease outbreaks.”

The Pentagon’s research and development funding arm wants to hear from academic, industry, commercial, and startup communities on how to develop “advanced capabilities that drive technical innovation and identify critical gaps in bio-surveillance, diagnostics, and medical countermeasures” in order to “improve preparedness for future public health emergencies.”

As if masks, social distancing, lockdowns, and vaccination mandates under the unscientific guise of slowing the spread and preventing the transmission of COVID weren’t harmful enough, the U.S. military wants to model the effects of these exact same countermeasures for future outbreaks.

The RFI also asks participants “Fatality Rate & Immune Status: How are fatality rates and varying levels of population immunity (natural or vaccine-induced) incorporated into your simulations?“

Does “natural or vaccine-induced” relate to “population immunity” or “fatality rates” or both?

Moving on, the RFI gets into modeling lockdowns, social distancing, and mass vaccination campaigns, along with communication strategies:

Intervention Strategies: Detail the range of intervention strategies that can be modeled, including (but not limited to) vaccination campaigns, social distancing measures, quarantine protocols, treatments, and public health communication strategies. Specifically, describe the ability to model early intervention and its impact on outbreak trajectory.

The fact that DARPA wants to model these so-called intervention strategies just after the entire world experienced them suggests that these exact same measures will most likely be used again in the future:

“We are committed to developing advanced modeling capabilities to optimize response strategies and inform the next generation of (bio)technology innovations to protect the population from biological threats. We are particularly focused on understanding the complex interplay of factors that drive outbreak spread and evaluating the effectiveness of potential interventions.” — DARPA, Advanced Disease Outbreak Simulation Capabilities RFI, May 2025.

“Identification of optimal timelines and capabilities to detect, identify, attribute, and respond to disease outbreaks, including but not limited to biosensor density deployment achieving optimal detection timelines, are of interest.” ­— DARPA, Advanced Disease Outbreak Simulation Capabilities RFI, May 2025.

With lockdowns, mass vaccination campaigns, and social distancing still on the table from the last around, it appears that AI and Machine Learning will play a much bigger role in the next.

For future innovation, the DARPA RFI asks applicants to: “Please describe any novel technical approaches – or applications of diverse technical fields (e.g., machine learning, artificial intelligence, complex systems theory, behavioral science) – that you believe would significantly enhance the state-of-the-art capabilities in this field or simulation of biological systems wholistically.”

Instead of putting a Dr. Fauci, a Dr. Birx, a replaceable CDC director, a TV doctor, a big pharma CEO, or a Cuomo brother out there to lie to your face about how they were all just following The ScienceTM, why not use AI and ML and combine them with behavioral sciences in order to concoct your “public health communications strategies?”

When you look at recently announced DARPA programs like Kallisti and MAGICS, which are aimed at creating an algorithmic Theory of Mind to model, predict, and influence collective human behavior, you start to get a sense of how all these programs can interweave:

“The MAGICS ARC calls for paradigm-shifting approaches for modeling complex, dynamic systems for predicting collective human behaviour.” — DARPA, MAGICS ARC, April 2025

On April 8, DARPA issued an Advanced Research Concepts (ARC) opportunity for a new program called “Methodological Advancements for Generalizable Insights into Complex Systems (MAGICS)” that seeks “new methods and paradigms for modeling collective human behavior.”

Nowhere in the MAGICS description does it mention modeling or predicting the behavior of “adversaries,” as is DARPA’s custom.

Instead, it talks at length about “modeling human systems,” along with anticipating, predicting, understanding, and forecasting “collective human behavior” and “complex social phenomena” derived from “sociotechnical data sets.”

Could DARPA’s MAGICS program be applied to simulating collective human behavior when it comes to the next public health emergency, be it real or perceived?

“The goal of an upcoming program will be to develop an algorithmic theory of mind to model adversaries’ situational awareness and predict future behaviour.” — DARPA, Theory of Mind Special Notice, December 2024.

In December 2024, DARPA launched a similar program called Theory of Mind, which was renamed Kallisti a month later.

The goal of Theory of Mind is to develop “new capabilities to enable national security decisionmakers to optimize strategies for deterring or incentivizing actions by adversaries,” according to a very brief special announcement.

DARPA never mentions who those “adversaries” are. In the case of a public health emergency, an adversary could be anyone who questions authoritative messaging.

The Theory of Mind program will also:

… seek to combine algorithms with human expertise to explore, in a modeling and simulation environment, potential courses of action in national security scenarios with far greater breadth and efficiency than is currently possible.

This would provide decisionmakers with more options for incentive frameworks while preventing unwanted escalation.

We are interested in a comprehensive overview of current and emerging technologies for disease outbreak simulation, how simulation approaches could be extended beyond standard modeling methods, and to understand how diseases spread within and between individuals including population level dynamics.

They say that all the modeling and simulating across programs is for “national security,” but that is a very broad term.

DARPA is in the business of research and development for national security purposes, so why is the Pentagon modeling disease outbreaks and intervention strategies while simultaneously looking to predict and manipulate collective human behavior?

If and when the next outbreak occurs, the same draconian and Orwellian measures that governments and corporations deployed in the name of combating COVID are still on the table.

And AI, Machine Learning, and the military will play an even bigger role than the last time around.

From analyzing wastewater to learning about disease spread; from developing pharmaceuticals to measuring the effects of lockdowns and vaccine passports, from modeling and predicting human behavior to coming up with messaging strategies to keep everyone in compliance – “improving preparedness for future public health emergencies” is becoming more militaristically algorithmic by the day.

“We are exploring innovative solutions to enhance our understanding of outbreak dynamics and to improve preparedness for future public health emergencies.” — DARPA, Advanced Disease Outbreak Simulation Capabilities RFI, May 2025.

Reprinted with permission from The Sociable.

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Business

Audit report reveals Canada’s controversial COVID travel app violated multiple rules

Published on June 11, 2025

By

From LifeSiteNews

By Anthony Murdoch

Canada’s Auditor General found that government procurement rules were not followed in creating the ArriveCAN app.

Canada’s Auditor General revealed that the former Liberal government under Prime Minister Justin Trudeau failed multiple times by violating contract procurement rules to create ArriveCAN, its controversial COVID travel app.

In a report released Tuesday, Auditor General Karen Hogan noted that between April 2015 to March 2024, the Trudeau government gave out 106 professional service contracts to GC Strategies Inc. This is the same company that made the ArriveCAN app.

The contracts were worth $92.7 million, with $64.5 million being paid out.

According to Hogan, Canada’s Border Services Agency gave four contracts to GC Strategies valued at $49.9 million. She noted that only 54 percent of the contracts delivered any goods.

“We concluded that professional services contracts awarded and payments made by federal organizations to GC Strategies and other companies incorporated by its co-founders were not in accordance with applicable policy instruments and that value for money for these contracts was not obtained,” Hogan said.

She continued, “Despite this, federal government officials consistently authorized payments.”

The report concluded that “Federal organizations need to ensure that public funds are spent with due regard for value for money, including in decisions about the procurement of professional services contracts.”

Hogan announced an investigation of ArriveCAN in November 2022 after the House of Commons voted 173-149 for a full audit of the controversial app.

Last year, Hogan published an audit of ArriveCAN and on Tuesday published a larger audit of the 106 contracts awarded to GC Strategies by 31 federal organizations under Trudeau’s watch.

‘Massive scandal,’ says Conservative leader Pierre Poilievre

Conservative Party leader Pierre Poilievre said Hogan’s report on the audit exposed multiple improprieties.

“This is a massive scandal,” he told reporters Tuesday.

“The facts are extraordinary. There was no evidence of added value. In a case where you see no added value, why are you paying the bill?”

ArriveCAN was introduced in April 2020 by the Trudeau government and made mandatory in November 2020. The app was used by the federal government to track the COVID jab status of those entering the country and enforce quarantines when deemed necessary.

ArriveCAN was supposed to have cost $80,000, but the number quickly ballooned to $54 million, with the latest figures showing it cost $59.5 million.

As for the app itself, it was riddled with technical glitches along with privacy concerns from users.

LifeSiteNews has published a wide variety of reports related to the ArriveCAN travel app.

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