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New Study Confirms CDC and Other ‘Experts’ Hurt Children for Nothing

Published

1 year ago

10 minute read

From the Brownstone Institute

BY Ian MillerIAN MILLER

The CDC funds a study with what it expects are pre-determined results, the media reports the results of that study – despite being misleading, expert researchers reassess using conventional methods, and the supposed benefit disappears.

But the correction receives none of the attention of the original, because it shows a result the CDC deems unacceptable.

There have clearly been many, MANY aspects of our Covid response that were and remain inexcusable.

Vaccine passports and mandates, the nonsensical curfews and capacity limits, general mask mandates, and of course, closing beaches, should never been forgotten.

But few, if any of our pointless, ineffective Covid-era restrictions were as indefensible as child masking. And thanks to the awe-inspiring incompetence of the CDC and Dr. Anthony Fauci, the United States was a global outlier; obsessively dedicated to forcing toddlers as young as 2-years-old to wear masks.

Schools, youth programs, camps, on airplanes…anywhere children gathered, they were forcibly masked. Horrifying videos emerged of teachers or flight attendants putting masks on crying children.

YouTube video

Calls to mask children in schools have disturbingly continued into late 2023 in certain parts of the country.

But new research has confirmed what was obvious to anyone who studied the data and evidence over the past few years: it was all for nothing.

Child Masking is Ineffective, New Study Finds

“Trust the science,” “Follow the data,” “Listen to the experts.”

Starting in 2020, those phrases became a relentless mantra of an oppressive government/pharma/media playbook. Instead of examining the actual evidence, data, and pre-Covid consensus, politicians, administrators, and huge swaths of the public put their faith and trust in a few unreliable, self-interested individuals. And with disastrous results.

Following the actual evidence would, in theory, have meant using evidence-based methods as espoused by experts in that field, such as Carl Heneghan from Oxford University. Primarily, that means using a hierarchy of studies, based on quality, to create systematic reviews of well-conducted research.

Instead, we were fed the CDC’s reporting of non-statistically significant results based on phone surveys, and we watched as those results were included in pro-masking reviews designed to promote an ineffective policy.

But a new systematic review from Tracy Beth Høeg and a number of other researchers has just been released on mask mandates for children. And unlike the pro-mask propaganda, it actually attempts to use high-quality evidence to come to its conclusion.

Background Mask mandates for children during the Covid-19 pandemic varied in different locations. A risk-benefit analysis of this intervention has not yet been performed. In this study, we performed a systematic review to assess research on the effectiveness of mask wearing in children.

They even used independent reviewers to ensure that there was no bias involved in the study selection criteria.

Methods We performed database searches up to February 2023. The studies were screened by title and abstract, and included studies were further screened as full-text references. A risk-of-bias analysis was performed by two independent reviewers and adjudicated by a third reviewer.

That meant that out of 597 studies screened, just 22 were included after meeting the criteria. And in a sign of how the CDC abdicated their responsibility, none were randomized controlled trials. Sure enough, when filtering out information at a risk of serious bias or confounding, there was no association between forcing kids to wear masks and infection or transmission.

Results There were no randomised controlled trials in children assessing the benefits of mask wearing to reduce SARS-CoV-2 infection or transmission. The six observational studies reporting an association between child masking and lower infection rate or antibody seropositivity had critical (n=5) or serious (n=1) risk of bias; all six were potentially confounded by important differences between masked and unmasked groups and two were shown to have non-significant results when reanalysed. Sixteen other observational studies found no association between mask wearing and infection or transmission.

As every intellectually honest scientist, researcher, or expert would admit, their inescapable conclusion is that the “current body of scientific data does not support masking children for protection against COVID-19.”

Conclusions Real-world effectiveness of child mask mandates against SARS-CoV-2 transmission or infection has not been demonstrated with high-quality evidence. The current body of scientific data does not support masking children for protection against Covid-19.

Who would have guessed?

Low-Quality Research Used to Create Low-Efficacy Policy

The details of the studies involved in this systematic review are even more damning.

Of the six observational studies that supposedly showed a benefit to masking kids, all were fatally flawed in important ways. Specifically, there were significant confounding differences between unmasked and masked children that undermine any of the reported results.

Differences included the “number of instructional school days, differences in school size, systematic baseline differences in case rates in all phases of the pandemic, testing policies, contact-tracing policy differences and teacher vaccination rates.” With differences that substantial, it’s impossible to determine whether or not the claimed reduction in infection or transmission is due to masks or one or many of those other factors.

This is why randomized controlled trials are so important. And why the CDC should have conducted them during the pandemic years. Yet at the same time, considering the results of masking RCT’s conducted on adults, it’s pretty obvious why they didn’t. Because they knew it would show that masks didn’t work.

The researchers also touched on the fact that some of the studies promoted by the CDC saw their effects vanish upon re-analysis. Specifically, one of the “observational CDC funded study” in the US claimed to show an association between county-wide mask mandates and pediatric case counts.

Yet when subjected to “expanded reanalysis,” that association disappeared.

That initial result though, is how you use low-quality studies to launder low-quality information. The CDC funds a study with what it expects are pre-determined results, the media reports the results of that study – despite being misleading, expert researchers reassess using conventional methods, and the supposed benefit disappears.

But the correction receives none of the attention of the original, because it shows a result the CDC deems unacceptable.

Even observational reporting has shown masks don’t matter at a population level for younger aged individuals. Virginia faced massive criticism for ending school mask mandates early in 2022, only to see cases collapse after a massive surge with mask mandates in place.

Similarly, cases in Philadelphia schools dropped two weeks after the mask mandate was lifted in 2022, and rose substantially for two weeks after the mask mandate in January 2023 came into effect.

As often discussed, in a sane world, this systematic review would permanently shut the door on further discussions of forced child masking. Higher quality research has confirmed that there is no evidence masks are effective and eliminating bias and confounders unsurprisingly shows the same result with children.

But sanity is dead. Therefore the current CDC director defiantly refuses to admit that masking toddlers was a mistake.

She doesn’t have to.

Høeg and the other researchers who conducted this review said it for her.

Republished from the author’s Substack

Published under a Creative Commons Attribution 4.0 International License
For reprints, please set the canonical link back to the original Brownstone Institute Article and Author.

 

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International

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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