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Brownstone Institute

How Did a Small Group Do This?

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From the Brownstone Institute

By JEFFREY A. TUCKER

“You know, it’s kind of our own science experiment that we’re doing in real time.”

A very interesting study appeared last week by two researchers looking into the pandemic policy response around the world. They are Drs. Eran Bendavid and Chirag Patel of Stanford and Harvard, respectively. Their ambition was straightforward. They wanted to examine the effects of government policy on the virus.

In this ambition, after all, researchers have access to an unprecedented amount of information. We have global data on strategies and stringencies. We have global data on infections and mortality. We can look at it all according to the timeline. We have precise dating of stay-at-home orders, business closures, meeting bans, masking, and every other physical intervention you can imagine.

The researchers merely wanted to track what worked and what did not, as a way of informing future responses to viral outbreaks so that public health can learn lessons and do better next time. They presumed from the outset they would discover that at least some mitigation tactics achieved the aim.

It is hardly the first such study. I’ve seen dozens of such efforts, and there are probably hundreds or thousands of these. The data is like catnip to anyone in this field who is empirically minded. So far, not even one empirical examination has shown any effect of anything but that seems like a hard conclusion to swallow. So these two decided to take a look for themselves.

They even went to the next step. They assembled and reassembled all existing data in every conceivable way, running fully 100,000 possible combinations of tests that all future researchers could run. They found some correlations in some policies but the problem is that every time they found one, they found another instance in which the reverse seemed to be true.

You cannot infer causation if the effects are not stable.

After vast data manipulation and looking at every conceivable policy and outcome, the researchers reluctantly come to an incredible conclusion. They conclude that nothing that governments did had any effect. There was only cost, no benefit. Everywhere in the world.

Please just let that sink in.

The policy response destroyed countless millions of small businesses, ruined a generation in learning losses, spread ill health with substance abuse, wrecked churches that could not hold holiday services, decimated arts and cultural institutions, broke trade, unleashed inflation that is nowhere near done with us yet, provoked new forms of online censorship, built government power in a way without precedent, led to new levels of surveillance, spread vaccine injury and death, and otherwise shattered liberties and laws the world over, not to mention leading to frightening levels of political instability.

And for what?

Apparently, it was all for nought.

Nor has there been any sort of serious reckoning. The European Commission elections are perhaps a start, and heavily influenced by public opposition to Covid controls, in addition to other policies that are robbing nations of their histories and identities. The major media can call the victors “far right” all they want but this is really about common people simply wanting their lives back.

It’s interesting to speculate about precisely how many people were involved in setting the world on fire. We know the paradigm was tried first in Wuhan, then blessed by the World Health Organization. As regards the rest of the world, we know some names, and there were many cohorts in public health and gain-of-function research.

Let’s say there are 300 of them, plus many national security and intelligence officials plus their sister agencies around the world. Let’s just add a zero plus multiply that by the large countries, presuming that so many others were copycats.

What are we talking about here? Maybe 3,000 to 5,000 people total in a decision-making capacity? That might be far too high. Regardless, compared with the sheer number of people around the world affected, we are talking about a tiny number, a mico-percent of the world’s population or less making new rules for the whole of humanity.

The experiment was without precedent on this scale. Even Deborah Birx admitted it. “You know, it’s kind of our own science experiment that we’re doing in real time.” The experiment was on whole societies.

How in the world did this come to be? There are explanations that rely on mass psychology, the influence of pharma, the role of the intelligence services, and other theories of cabals and conspiracies. Even with every explanation, the whole thing seems wildly implausible. Surely it would have been impossible without global communications and media, which amplified the entire agenda in every respect.

Because of this, kids could not go to school. People in public parks had to stay within circles. Businesses could not open at full capacity. We developed insane rituals like masking when walking and unmasking when sitting. Oceans of sanitizer would be dumped on all people and things. People were made to be afraid of leaving their homes and clicked buttons to make groceries arrive on their doorsteps.

It was a global science experiment without any foundation in evidence. And the experience utterly transformed our legal systems and lives, introducing uncertainties and anxieties as never before and unleashing a level of crime in major cities that provoked residential, business, and capital flight.

This is a scandal for the ages. And yet hardly anyone in major media seems to be interested in getting to the bottom of it. That’s because, for bizarre reasons, looking too carefully at the culprits and policies here is regarded as being for Trump. And the hate and fear of Trump is so beyond reason at this point that whole institutions have decided to sit back and watch the world burn rather than be curious about what provoked this in the first place.

Instead of an honest accounting of the global upheaval, we are getting the truth in dribs and drabs. Anthony Fauci continues to testify for Congressional hearings and this extremely clever man threw his longtime collaborator under the bus, acting like David Morens was a rogue employee. That action seemed to provoke ex-CDC director Robert Redfield to go public, saying that it was a lab leak from a US-funded lab doing “dual purpose” research into vaccines and viruses, and strongly suggesting that Fauci himself was involved in the cover-up.

Among this group, we are quickly approaching the point of “Every man for himself.” It is fascinating to watch, for those of us who are deeply interested in this question. But for the mainstream media, none of this gets any coverage at all. They act like we should just accept what happened and not think anything about it.

This great game of pretend is not sustainable. To be sure, maybe the world is more broken than we know but something about cosmic justice suggests that when a global policy this egregious, this damaging, this preposterously wrongheaded, does all harm and no good, there are going to be consequences.

Not immediately but eventually.

When will the whole truth emerge? It could be decades from now but we already know this much for sure. Nothing we were promised about the great mitigation efforts by governments turned out to achieve anything remotely what they promised. And yet even now, the World Health Organization continues to uphold such interventions as the only way forward.

Meanwhile, the paradigm of bad science backed by force pervades nearly everything these days, from climate change to medical services to information controls.

When will evidence matter again?


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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  • Jeffrey A. Tucker

    Jeffrey Tucker is Founder, Author, and President at Brownstone Institute. He is also Senior Economics Columnist for Epoch Times, author of 10 books, including Life After Lockdown, and many thousands of articles in the scholarly and popular press. He speaks widely on topics of economics, technology, social philosophy, and culture.

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Brownstone Institute

Net Zero: The Mystery of the Falling Fertility

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From the Brownstone Institute

By Tomas FurstTomas Fürst  

If you want to argue that a mysterious factor X is responsible for the drop in fertility, you will have to explain (1) why the factor affected only the vaccinated, and (2) why it started affecting them at about the time of vaccination.

In January 2022, the number of children born in the Czech Republic suddenly decreased by about 10%. By the end of 2022, it had become clear that this was a signal: All the monthly numbers of newborns were mysteriously low.

In April 2023, I wrote a piece for a Czech investigative platform InFakta and suggested that this unexpected phenomenon might be connected to the aggressive vaccination campaign that had started approximately 9 months before the drop in natality. Denik N – a Czech equivalent of the New York Times – immediately came forward with a “devastating takedown” of my article, labeled me a liar and claimed that the pattern can be explained by demographics: There were fewer women in the population and they were getting older.

To compare fertility across countries (and time), the so-called Total Fertility Rate (TFR) is used. Roughly speaking, it is the average number of children that are born to a woman over her lifetime. TFR is independent of the number of women and of their age structure. Figure 1 below shows the evolution of TFR in several European countries between 2001 and 2023. I selected countries that experienced a similar drop in TFR in 2022 as the Czech Republic.

Figure 1. The evolution of Total Fertility Rate in selected European countries between 2000 and 2023. The data corresponding to a particular year are plotted at the end of the column representing that year.

So, by the end of 2023, the following two points were clear:

  1. The drop in natality in the Czech Republic in 2022 could not be explained by demographic factors. Total fertility rate – which is independent of the number of women and their age structure – dropped sharply in 2022 and has been decreasing ever since. The data for 2024 show that the Czech TFR has decreased further to 1.37.
  1. Many other European countries experienced the same dramatic and unexpected decrease in fertility that started at the beginning of 2022. I have selected some of them for Figure 1 but there are more: The Netherlands, Norway, Slovakia, Slovenia, and Sweden. On the other hand, there are some countries that do not show a sudden drop in TFR, but rather a steady decline over a longer period (e.g. Belgium, France, UK, Greece, or Italy). Notable exceptions are Bulgaria, Spain, and Portugal where fertility has increased (albeit from very low numbers). The Human Fertility Project database has all the numbers.

This data pattern is so amazing and unexpected that even the mainstream media in Europe cannot avoid the problem completely. From time to time, talking heads with many academic titles appear and push one of the politically correct narratives: It’s Putin! (Spoiler alert: The war started in February 2022; however, children not born in 2022 were not conceived in 2021). It’s the inflation caused by Putin! (Sorry, that was even later). It’s the demographics! (Nope, see above, TFR is independent of the demographics).

Thus, the “v” word keeps creeping back into people’s minds and the Web’s Wild West is ripe with speculation. We decided not to speculate but to wrestle some more data from the Czech government. For many months, we were trying to acquire the number of newborns in each month, broken down by age and vaccination status of the mother. The post-socialist health-care system of our country is a double-edged sword: On one hand, the state collects much more data about citizens than an American would believe. On the other hand, we have an equivalent of the FOIA, and we are not afraid to use it. After many months of fruitless correspondence with the authorities, we turned to Jitka Chalankova – a Czech Ron Johnson in skirts – who finally managed to obtain an invaluable data sheet.

To my knowledge, the datasheet (now publicly available with an English translation here) is the only officially released dataset containing a breakdown of newborns by the Covid-19 vaccination status of the mother. We requested much more detailed data, but this is all we got. The data contains the number of births per month between January 2021 and December 2023 given by women (aged 18-39) who were vaccinated, i.e., had received at least one Covid vaccine dose by the date of delivery, and by women who were unvaccinated, i.e., had not received any dose of any Covid vaccine by the date of delivery.

Furthermore, the numbers of births per month by women vaccinated by one or more doses during pregnancy were provided. This enabled us to estimate the number of women who were vaccinated before conception. Then, we used open data on the Czech population structure by age, and open data on Covid vaccination by day, sex, and age.

Combining these three datasets, we were able to estimate the rates of successful conceptions (i.e., conceptions that led to births nine months later) by preconception vaccination status of the mother. Those interested in the technical details of the procedure may read Methods in the newly released paper. It is worth mentioning that the paper had been rejected without review in six high-ranking scientific journals. In Figure 2, we reprint the main finding of our analysis.

Figure 2A. Histogram showing the percentage of women in the Czech Republic aged 18–39 years who were vaccinated with at least one dose of a Covid-19 vaccine by the end of the respective month. Figure 2B. Estimates of the number of successful conceptions (SCs) per 1,000 women aged 18–39 years according to their pre-conception Covid vaccination status. The blue-shaded areas in Figure 1B show the intervals between the lower and upper estimates of the true SC rates for women vaccinated (dark blue) and unvaccinated (light blue) before conception.

Figure 2 reveals several interesting patterns that I list here in order of importance:

  1. Vaccinated women conceived about a third fewer children than would be expected from their share of the population. Unvaccinated women conceived at about the same rate as all women before the pandemic. Thus, a strong association between Covid vaccination status and successful conceptions has been established.
  2. In the second half of 2021, there was a peak in the rate of conceptions of the unvaccinated (and a corresponding trough in the vaccinated). This points to rather intelligent behavior of Czech women, who – contrary to the official advice – probably avoided vaccination if they wanted to get pregnant. This concentrated the pregnancies in the unvaccinated group and produced the peak.
  3. In the first half of 2021, there was significant uncertainty in the estimates of the conception rates. The lower estimate of the conception rate in the vaccinated was produced by assuming that all women vaccinated (by at least one dose) during pregnancy were unvaccinated before conception. This was almost certainly true in the first half of 2021 because the vaccines were not available prior to 2021. The upper estimate was produced by assuming that all women vaccinated (by at least one dose) during pregnancy also received at least one dose before conception. This was probably closer to the truth in the second part of 2021. Thus, we think that the true conception rates for the vaccinated start close to the lower bound in early 2021 and end close to the upper bound in early 2022. Once again, we would like to be much more precise, but we have to work with what we have got.

Now that the association between Covid-19 vaccination and lower rates of conception has been established, the one important question looms: Is this association causal? In other words, did the Covid-19 vaccines really prevent women from getting pregnant?

The guardians of the official narrative brush off our findings and say that the difference is easily explained by confounding: The vaccinated tend to be older, more educated, city-dwelling, more climate change aware…you name it. That all may well be true, but in early 2022, the TFR of the whole population dropped sharply and has been decreasing ever since.

So, something must have happened in the spring of 2021. Had the population of women just spontaneously separated into two groups – rednecks who wanted kids and didn’t want the jab, and city slickers who didn’t want kids and wanted the jab – the fertility rate of the unvaccinated would indeed be much higher than that of the vaccinated. In that respect, such a selection bias could explain the observed pattern. However, had this been true, the total TFR of the whole population would have remained constant.

But this is not what happened. For some reason, the TFR of the whole population jumped down in January 2022 and has been decreasing ever since. And we have just shown that, for some reason, this decrease in fertility affected only the vaccinated. So, if you want to argue that a mysterious factor X is responsible for the drop in fertility, you will have to explain (1) why the factor affected only the vaccinated, and (2) why it started affecting them at about the time of vaccination. That is a tall order. Mr. Occam and I both think that X = the vaccine is the simplest explanation.

What really puzzles me is the continuation of the trend. If the vaccines really prevented conception, shouldn’t the effect have been transient? It’s been more than three years since the mass vaccination event, but fertility rates still keep falling. If this trend continues for another five years, we may as well stop arguing about pensions, defense spending, healthcare reform, and education – because we are done. 

We are in the middle of what may be the biggest fertility crisis in the history of mankind. The reason for the collapse in fertility is not known. The governments of many European countries have the data that would unlock the mystery. Yet, it seems that no one wants to know.


Author

Tomas Furst

Tomas Fürst teaches applied mathematics at Palacky University, Czech Republic. His background is in mathematical modelling and Data Science. He is a co-founder of the Association of Microbiologists, Immunologists, and Statisticians (SMIS) which has been providing the Czech public with data-based and honest information about the coronavirus epidemic. He is also a co-founder of a “samizdat” journal dZurnal which focuses on uncovering scientific misconduct in Czech Science.

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Brownstone Institute

FDA Exposed: Hundreds of Drugs Approved without Proof They Work

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From the Brownstone Institute

By Maryanne Demasi

The US Food and Drug Administration (FDA) has approved hundreds of drugs without proof that they work—and in some cases, despite evidence that they cause harm.

That’s the finding of a blistering two-year investigation by medical journalists Jeanne Lenzer and Shannon Brownleepublished by The Lever.

Reviewing more than 400 drug approvals between 2013 and 2022, the authors found the agency repeatedly ignored its own scientific standards.

One expert put it bluntly—the FDA’s threshold for evidence “can’t go any lower because it’s already in the dirt.”

A System Built on Weak Evidence

The findings were damning—73% of drugs approved by the FDA during the study period failed to meet all four basic criteria for demonstrating “substantial evidence” of effectiveness.

Those four criteria—presence of a control group, replication in two well-conducted trials, blinding of participants and investigators, and the use of clinical endpoints like symptom relief or extended survival—are supposed to be the bedrock of drug evaluation.

Yet only 28% of drugs met all four criteria—40 drugs met none.

These aren’t obscure technicalities—they are the most basic safeguards to protect patients from ineffective or dangerous treatments.

But under political and industry pressure, the FDA has increasingly abandoned them in favour of speed and so-called “regulatory flexibility.”

Since the early 1990s, the agency has relied heavily on expedited pathways that fast-track drugs to market.

In theory, this balances urgency with scientific rigour. In practice, it has flipped the process. Companies can now get drugs approved before proving that they work, with the promise of follow-up trials later.

But, as Lenzer and Brownlee revealed, “Nearly half of the required follow-up studies are never completed—and those that are often fail to show the drugs work, even while they remain on the market.”

“This represents a seismic shift in FDA regulation that has been quietly accomplished with virtually no awareness by doctors or the public,” they added.

More than half the approvals examined relied on preliminary data—not solid evidence that patients lived longer, felt better, or functioned more effectively.

And even when follow-up studies are conducted, many rely on the same flawed surrogate measures rather than hard clinical outcomes.

The result: a regulatory system where the FDA no longer acts as a gatekeeper—but as a passive observer.

Cancer Drugs: High Stakes, Low Standards

Nowhere is this failure more visible than in oncology.

Only 3 out of 123 cancer drugs approved between 2013 and 2022 met all four of the FDA’s basic scientific standards.

Most—81%—were approved based on surrogate endpoints like tumour shrinkage, without any evidence that they improved survival or quality of life.

Take Copiktra, for example—a drug approved in 2018 for blood cancers. The FDA gave it the green light based on improved “progression-free survival,” a measure of how long a tumour stays stable.

But a review of post-marketing data showed that patients taking Copiktra died 11 months earlier than those on a comparator drug.

It took six years after those studies showed the drug reduced patients’ survival for the FDA to warn the public that Copiktra should not be used as a first- or second-line treatment for certain types of leukaemia and lymphoma, citing “an increased risk of treatment-related mortality.”

Elmiron: Ineffective, Dangerous—And Still on the Market

Another striking case is Elmiron, approved in 1996 for interstitial cystitis—a painful bladder condition.

The FDA authorized it based on “close to zero data,” on the condition that the company conduct a follow-up study to determine whether it actually worked.

That study wasn’t completed for 18 years—and when it was, it showed Elmiron was no better than placebo.

In the meantime, hundreds of patients suffered vision loss or blindness. Others were hospitalized with colitis. Some died.

Yet Elmiron is still on the market today. Doctors continue to prescribe it.

“Hundreds of thousands of patients have been exposed to the drug, and the American Urological Association lists it as the only FDA-approved medication for interstitial cystitis,” Lenzer and Brownlee reported.

“Dangling Approvals” and Regulatory Paralysis

The FDA even has a term—”dangling approvals”—for drugs that remain on the market despite failed or missing follow-up trials.

One notorious case is Avastin, approved in 2008 for metastatic breast cancer.

It was fast-tracked, again, based on ‘progression-free survival.’ But after five clinical trials showed no improvement in overall survival—and raised serious safety concerns—the FDA moved to revoke its approval for metastatic breast cancer.

The backlash was intense.

Drug companies and patient advocacy groups launched a campaign to keep Avastin on the market. FDA staff received violent threats. Police were posted outside the agency’s building.

The fallout was so severe that for more than two decades afterwards, the FDA did not initiate another involuntary drug withdrawal in the face of industry opposition.

Billions Wasted, Thousands Harmed

Between 2018 and 2021, US taxpayers—through Medicare and Medicaid—paid $18 billion for drugs approved under the condition that follow-up studies would be conducted. Many never were.

The cost in lives is even higher.

A 2015 study found that 86% of cancer drugs approved between 2008 and 2012 based on surrogate outcomes showed no evidence that they helped patients live longer.

An estimated 128,000 Americans die each year from the effects of properly prescribed medications—excluding opioid overdoses. That’s more than all deaths from illegal drugs combined.

A 2024 analysis by Danish physician Peter Gøtzsche found that adverse effects from prescription medicines now rank among the top three causes of death globally.

Doctors Misled by the Drug Labels

Despite the scale of the problem, most patients—and most doctors—have no idea.

A 2016 survey published in JAMA asked practising physicians a simple question—what does FDA approval actually mean?

Only 6% got it right.

The rest assumed that it meant the drug had shown clear, clinically meaningful benefits—such as helping patients live longer or feel better—and that the data was statistically sound.

But the FDA requires none of that.

Drugs can be approved based on a single small study, a surrogate endpoint, or marginal statistical findings. Labels are often based on limited data, yet many doctors take them at face value.

Harvard researcher Aaron Kesselheim, who led the survey, said the results were “disappointing, but not entirely surprising,” noting that few doctors are taught about how the FDA’s regulatory process actually works.

Instead, physicians often rely on labels, marketing, or assumptions—believing that if the FDA has authorized a drug, it must be both safe and effective.

But as The Lever investigation shows, that is not a safe assumption.

And without that knowledge, even well-meaning physicians may prescribe drugs that do little good—and cause real harm.

Who Is the FDA Working for?

In interviews with more than 100 experts, patients, and former regulators, Lenzer and Brownlee found widespread concern that the FDA has lost its way.

Many pointed to the agency’s dependence on industry money. A BMJ investigation in 2022 found that user fees now fund two-thirds of the FDA’s drug review budget—raising serious questions about independence.

Yale physician and regulatory expert Reshma Ramachandran said the system is in urgent need of reform.

“We need an agency that’s independent from the industry it regulates and that uses high-quality science to assess the safety and efficacy of new drugs,” she told The Lever. “Without that, we might as well go back to the days of snake oil and patent medicines.”

For now, patients remain unwitting participants in a vast, unspoken experiment—taking drugs that may never have been properly tested, trusting a regulator that too often fails to protect them.

And as Lenzer and Brownlee conclude, that trust is increasingly misplaced.

Republished from the author’s Substack

 

Author

Maryanne Demasi, 2023 Brownstone Fellow, is an investigative medical reporter with a PhD in rheumatology, who writes for online media and top tiered medical journals. For over a decade, she produced TV documentaries for the Australian Broadcasting Corporation (ABC) and has worked as a speechwriter and political advisor for the South Australian Science Minister.

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