British Medical Journal: The FDA and CDC Used a Faulty Algorithm to Understate Vaccine Injuries. When One Researcher Pointed Out the Flaw, She Was Told to Mind Her Own Business.

I'm not willing to assume "just an accidental oversight."

In fact, I'm very much assuming enemy action.

Adam Urato, MD @AdamUrato1

Must-read investigative article in The BMJ.

Clear safety signals of Covid vaccine harms (in red below) were missed by FDA & CDC by using a flawed method where the harms went undetected.

"The agency's PRR analyses--examined by The BMJ--show that hundreds of types of adverse events met the agency's criteria for a signal" (including myocarditis, pericarditis, Bell's palsy, and tinnitus.)

The FDA doctor who alerted them to the flawed safety system was muzzled. "She was told, with diplomatic flourish, to back off."

Above, the images show a correct analysis of vaccine harms, showing lots of red flags.

The images on the right show the FDA's and CDC's "accidental" understatement of vaccine injuries -- all green flags.

Whoops!

Whoopsie!

From the BMJ:

US officials knew covid vaccine safety system was flawed--but turned aside the FDA doctor who alerted them

US officials embraced an algorithm for detecting signals of harm from mRNA covid-19 vaccines that they knew was broken and suppressed efforts to fix it.

David Willman reports:

Before covid-19 vaccines were rolled out to Americans in December 2020, the US Centers for Disease Control and Prevention (CDC) assured healthcare providers that the agency was on the lookout for any harmful reactions. A key part of the CDC's strategy was its Vaccine Adverse Event Reporting System (VAERS), which receives such reports after vaccination.

"It is the nation's frontline system for monitoring vaccine safety and the early warning system for detecting possible vaccine safety problems," said Tom Shimabukuro, deputy director of CDC's Immunization Safety Office, on 30 October 2020.

Millions of people were to be vaccinated each week, and the CDC would rely on statistical "data mining" of the VAERS database to quickly identify any safety signals in need of further probing.

Two well recognised, separate algorithms were to be used. The first involved calculating "proportional reporting ratios" (PRRs), which sought to identify types of reactions reported to VAERS disproportionately or more frequently than background rates. The second data mining technique, called "empirical bayesian," was to be provided by the Food and Drug Administration (FDA), which operated VAERS jointly with the CDC, and the two agencies planned to share and discuss results.

But in a little noticed September 2022 letter, CDC director Rochelle Walensky said that the agency did not perform PRR analyses for signals until 2022. This was more than a year into the vaccine rollout and was intended, she wrote, "to corroborate" the FDA's approach. Instead of using the PRR and empirical bayesian methods jointly during the pandemic, Walensky explained that both the CDC and FDA instead "chose to rely" on empirical bayesian, which she characterised as "a more robust technique."

It doesn't appear to be "more robust." What it appears to be is deliberately crippled to hide vaccine injuries.

The BMJ, however, has found that the FDA's algorithm was mathematically compromised by the deluge of covid vaccine adverse event reports--resulting in a near total loss of signal detection sensitivity for the new mRNA vaccines made by Pfizer and Moderna. Top FDA officials were warned internally of this problem in early 2021, and the official who headed its pharmacovigilance division for vaccines commented more than two years later to his CDC and FDA colleagues: "We were aware of this [data mining] limitation before and during the pandemic." Government documents also show that CDC officials were informed during rollout of the vaccines--on multiple occasions.

Yet instead of fixing the safety deficiency--or shutting down the unreliable signal detection system--officials continued to rely on the FDA's broken algorithm. The officials also cited the absence of signals when assuring clinicians and the public of the vaccines' safety.

At the FDA, managers went a step further by silencing the career drug safety officer who had repeatedly brought the deficiency to their attention and had offered an updated algorithm intended to fix it. As a result, Americans received unfounded assurances of the safety of the most widely used covid vaccines and were denied prompt warnings of potential harms, The BMJ's investigation found.

...

"I'm perplexed that myocarditis isn't alerting"

In late February 2021, CDC and FDA officials received notice of "a large number of reports of myocarditis, particularly in young people," after vaccination. The warnings of myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the pericardium) came from the Israeli Ministry of Health. In a private meeting five weeks later, the Israelis informed a CDC convened covid vaccine safety committee that two of the 77 vaccinated people with myocarditis or pericarditis had died.

The next week, the same committee heard from the Pentagon's Defense Health Agency, which reported a "cluster of cases" of myocarditis among male US military members.

US public health officials remained sceptical of a link to the new mRNA vaccines. "We have not seen a signal [for myocarditis], and we've actually looked intentionally for the signal in the over 200 million doses we've given," CDC director Walensky told reporters.

By May 2021, VAERS had received hundreds of reports of myocarditis and pericarditis after covid vaccinations, and the CDC began alerting healthcare professionals. While the agency was still unsure of a causal relationship, it decided to alert physicians more broadly through a "clinical considerations" web posting.

But oncologist Peter Marks, who as director of the FDA's Center for Biologics Evaluation and Research was the agency's top covid vaccine regulator, objected. He questioned the CDC's imminent website announcement, emailing Walensky directly, highlighting the lack of any safety signal from the government's own surveillance: "We still have concerns here [at the FDA] if myocarditis and pericarditis have not actually signaled . . . Can you help me understand why we are doing this when pediatricians and others in the community already seem to be aware?"

...

Still, VAERS reports continued to mount, with myocarditis attracting the greatest attention. In a June 2021 public presentation, the CDC's Shimabukuro showed that, for young males (age 12-24), VAERS had received between 29 and 347 times more myocarditis and pericarditis reports than the agency expected based on background incidence rates. In a public statement that day, the CDC dubbed myocarditis an "extremely rare side effect."

Government records show that, the day before his presentation, Shimabukuro had received the FDA's latest data mining report--and it continued to show no signal. "I'm perplexed that myocarditis isn't alerting for either of the mRNA vaccines," Shimabukuro emailed a colleague.

Early warnings

The BMJ can reveal that the FDA's algorithm failed to signal a potential relationship between mRNA covid vaccination and myocarditis, pericarditis, Bell's palsy, tinnitus, and other reported disorders owing to a flaw in the detection methodology--a flaw that senior officials declined to rectify.

If I understand the next section, I believe they are saying the FDA's and CDC's faulty algorithm compared covid "vaccine" VAERS reports to all VAERS reports, and would only flag the "vaccines" as problematic if they showed many more VAERS reports than all other reports.

But the problem is -- and this should have been obvious -- that 90% of the public was "vaccinated" with the covid "vaccines," so if you compared "vaccine" incident rates to all reported incident rates -- they were practically the same number. The FDA and CDC used an algorithm to detect a covid "vaccine" signal against the sea of all other incidents, but covid "vaccines" were so common, numbering the many tens of millions, that covid "vaccine" incidents were the sea they were checking against.

It's like a Venn diagram where the circles almost completely overlap. If you're comparing "vaccine" incidents to "background" incidents but "vaccine" incidents make up 90% of the background, everytime you check, you'll find that "vaccine" incidents are very similar to "background" incidents, because "background" incidents are made up mostly of vaccine "incidents."

And thus, they kept claiming: We don't see any pronounced spike of "vaccine" incidents compared to all other incidents, without telling you that the background data they were checking against was mostly covid "vaccine" data.

The problem arose because, in the first year of the rollout, almost all the reports coming into VAERS--more than 90% of 1.1 million--were for the mRNA covid shots, dwarfing vaccines for all other diseases. This meant that analysing the safety of one vaccine, for example Pfizer's product, involved comparing it to other vaccines, which were overwhelmingly limited to Moderna's product. But if both mRNA vaccines elevated the risk of an adverse event like myocarditis in roughly equal amounts, the "observed" frequency and "expected" frequency would be similar, resulting in no automated alert. The statistical phenomenon is known as "masking."

And I wonder if this "masking" effect was accidental, or intended.

Imagine if you wanted to see if covid was affecting ethnic Chinese people more than non-ethnic Chinese people. In China. So you compare the rates of ethnic Chinese people in China to all people in China, and find that there is no difference between ethnic Chinese people and all people in China.

But your data for "all" people in China is 95% ethnic Chinese! Of course you found no difference in the rates of infection! You're comparing Data Set A to Data Set A + 5% other data and finding the two are barely different at all!

No more than 5% different, in fact! Not statistically significant!

Szarfman and DuMouchel, who earned his PhD at Yale and by 2010 became chief statistician at Oracle Health Sciences, judged that the unique circumstances of the pandemic meant that the FDA's approach was missing safety signals...

"Regarding the NYT article, I am quite concerned," Szarfman emailed Marks two days later. She wrote that the agency should be "clamoring to fix this problem." < Szarfman concluded, "Let me know if you want Bill DuMouchel and I to discuss our proposal for more effective monitoring, including the need to use an updated algorithm by DuMouchel for data mining spontaneous reports."

...

Marks and his staff, however, declined to alter the FDA's existing approach--and agency officials did not publicly warn of the deficiency with finding safety signals. When Szarfman continued to press the matter, she was told, with diplomatic flourish, to back off.

That email, sent on 7 May 2021, by Craig Zinderman, associate director for medical policy in FDA's Office of Biostatistics and Epidemiology, began: "Good Afternoon Ana, Thank you again for talking with us back in March about your work exploring new data mining approaches . . . We are writing to kindly ask you to please hold off on creating and sending data mining reports and analyses using covid-19 vaccine AE [adverse event] data."

I would say "incredible" but we have seen again and again that 90% of the output from government, from NGOs, from academia, from corporations is pure fraud on the public.

posted by Disinformation Expert Ace at 12:04 PM

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