Connect with us
[the_ad id="89560"]

COVID-19

Will We Fall For The Same Old PCR Tricks Again?

Published

8 minute read

From the Frontier Centre for Public Policy

By John Carpay

As with the number of COVID-19 “cases,” the number of “Covid deaths” proclaimed by politicians, government health officials and government-funded media is also based on highly unreliable PCR testing, using an undisclosed number of cycles.

Fool me once, shame on you. Fool me twice, shame on me. How long will Canadians continue falling for the same media tricks that they fell for during the years of lockdowns and vaccine passports?

“Alberta’s COVID-19 death toll more than 4 times higher than flu over past year,” exclaimed the CBC on September 9. This was followed two days later by Global News exclaiming: “New Alberta COVID data highlights value of getting newly formulated vaccine once available: expert.”

These media stories claim there were 23,933 COVID-19 “cases” in the past year, with 6,070 people hospitalized “for COVID.” Media claim that 732 Albertans died of COVID-19 during the past year, compared to 177 from the flu. University of Calgary professor Craig Jenne describes this as “continual evidence that COVID-19 is not just another flu” and laments that viruses “continue to take lives at a really unacceptable rate.”

It’s the same narrative that we were fed in 2020 and the years that followed: creating and then maintaining unfounded fear of COVID-19. This unnecessarily high level of fear, in turn, generated support for the violations of our Charter freedoms of association, expression, religion, conscience, mobility, and peaceful assembly, and the right to choose freely what will or will not be injected into our bodies.

What is missing from these stories by government-funded media is significant and relevant.

Firstly, government-funded media make no mention of the number of cycles used in the PCR (polymerase chain reaction) testing that was used to generate these 23,933 so-called “cases” of COVID-19.

The percentage of people testing “positive” for COVID-19 by way of the PCR test depends on the number of times that a viral remnant in a person’s nose or throat is doubled (amplified). If a COVID-19 viral remnant is amplified 40 times, almost everyone will test positive for COVID-19. Conversely, if that very same viral remnant is amplified only 20 times, very few people will test positive for COVID-19. The PCR test does not and cannot determine whether someone is sick with COVID-19, or a spreader of COVID-19.

As explained by expert witness Dr. Joel Kettner in Gateway v. Manitoba:[1] “the outcome of a PCR test depends on Cycle thresholds (Ct), which is the number of cycles of amplification needed to strengthen a weak signal, so as to enable the identification of the amino acid sequence of the virus being tested for. The higher the Ct to obtain a positive signal, the lower the volume of genetic material in the sample.”[2]

In the same court case, expert witness Dr. Jay Bhattacharya explained that the unavoidable errors in PCR testing render the PCR test unfit for public health decision-making: “A reliance on a test that is run up to 40 cycles, (or any number of cycles higher than 30) — is certain to produce a very large proportion of false positive outcomes. Lockdowns that are imposed on the basis of ‘case’ counts derived from PCR tests will be only marginally related to the threat posed by the spread of the SARS-CoV-2 virus.”

Neither Alberta Health Services nor the media will inform the public about how many times a viral remnant was doubled to generate these 23,933 “cases” of COVID-19. A large but willfully undisclosed number of these COVID-19 “cases” pertain to people who are not sick with COVID-19 and not spreading COVID-19. This includes large numbers of people who have had COVID-19 and who have fully recovered, acquiring natural immunity along the way. Governments which claim to love science should freely and readily disclose this information to the public, as well as to each individual receiving her or his PCR test result. And yet, since 2020, Canada’s federal and provincial governments have kept this information a state secret, typically divulged only under duress in court, when governments get sued by Justice Centre lawyers who defend Charter freedoms.

In Gateway v. Manitoba, for example, government officials admitted under oath that at least 40% of their “Covid cases” were people who were not sick with COVID-19 and not spreading it. Governments and their health authorities can easily generate high numbers of “Covid cases” simply by running PCR tests at 40 (or more) cycles, and encouraging (or requiring) large numbers of people to take the PCR test.

As with the number of COVID-19 “cases,” the number of “Covid deaths” proclaimed by politicians, government health officials and government-funded media is also based on highly unreliable PCR testing, using an undisclosed number of cycles.

The second glaring omission from government-funded media reports is the relevant context. Over 33,000 Albertans die each year, which is what you might expect in a province of 4.8 million people. The leading causes of death in Canada are cancer, heart diseases, lung diseases and strokes. This fact did not change with the arrival of COVID-19 and lockdowns in 2020. If it’s true that 732 Albertans died of COVID-19 (and thanks to PCR testing we really don’t know) that would be just over 2% of deaths in Alberta, with 87% of these deaths among people 70 and over. Compare this 2% with the more than 10% of deaths in Alberta from “ill-defined and unknown” causes in 2021. Professor Craig Jenne states that viruses “continue to take lives at a really unacceptable rate.” The same could be said of cancer, heart diseases, lung diseases and strokes, not to mention suicides, alcoholism, obesity and car accidents.

The omission of relevant facts, combined with a blind and erroneous faith in the accuracy of PCR testing, is what government-funded media used in 2020 to spread unfounded fear. They are trying to do the same thing now. Will we fall for it again?

First published in the Western Standard here.

John Carpay, B.A., LL.B. is president of the Justice Centre for Constitutional Freedoms.

International

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

Published on

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.

Continue Reading

Business

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

Published on

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.

Continue Reading

Trending

X