Federal legal challenges have temporarily enjoined the Biden Administration’s sweeping large business, health care worker, and federal contractor covid-19 vaccine mandates. Notwithstanding these injunctions staying primary covid-19 vaccine mandates, “amendments” mandating booster covid-19 vaccinations have already been issued, as examples, for New Mexico healthcare workers, and University of Massachusetts-Amherst students.
Dr. Allon Friedman’s recent Brownstone essay, citing randomized, controlled trial data on primary covid-19 vaccination, demonstrated, “The Pfizer and Moderna trials show that in lower risk populations (which account for most of society) COVID-19 vaccines do not reduce mortality.” Friedman concluded, “Therefore, [covid-19] vaccine mandates, which are enormously costly and terribly divisive, are a cure worse than the disease.”
Why did Dr. Friedman rely exclusively—and appositely—upon randomized, controlled trial data to justify his conclusion? Almost sixty years ago (in 1963) Campbell and Stanley published their seminal monograph on research methodology entitled “Experimental and Quasi-Experimental Designs for Research.” This work, which shaped research designs ever since highlighted the major threats to validity that are avoided, uniquely, by the randomized controlled trial—a true experimental design.
Observational studies and all other non-randomized designs lacking parallel control groups, which they referred to as “quasi-experimental,” are fraught with known biases investigators attempt to control for, after the fact, with limited success. Worse still are intractable, unknown biases which the randomization process, alone, accounts for. Guyatt and colleagues, in their 2008 British Medical Journal paper “GRADE: an emerging consensus on rating quality of evidence and strength of recommendations”, updated and reinforced these ideas, appropriately assigning highest priority to randomized, controlled trial evidence.
On Friday, November 19, 2021, CDC Director Dr. Walensky endorsed the expanded recommendations of the CDC Advisory Committee on Immunization Practices (ACIP) that booster (third dose) shots be provided to all adults 18 years of age, and older, who received their second Pfizer or Moderna mRNA vaccine second doses, at least 6-months earlier.
What randomized, controlled trial evidence were the basis for this “unanimous decision,” touted by Dr. Walensky?
Although two small, published, randomized, placebo-controlled trials—one in kidney transplant recipients, and another in a general population—revealed enhanced immune responses to boosters, CDC’s recommendation clearly hinged upon a large, unpublished Pfizer randomized, placebo-controlled clinical trial.
A month before the CDC expanded booster recommendation was announced, Pfizer’s “randomized trial results by press release” were issued (10/21/21). The ~10,000 person, placebo-controlled randomized covid-19 vaccine booster trial, yielded a 95.6% reduction in symptomatic covid-19 infections (i.e., 109 in the placebo group; 9 in the boosted group), after a median 2.5 months of follow-up. The press release also included this important caveat:
“The observed relative vaccine efficacy of 95.6% (95% CI: 89.3, 98.6) reflects the reduction in disease occurrence in the boosted group versus the non-boosted group in those without evidence of prior SARS-CoV-2 infection.”
The November 19, 2021, ACIP presentation of Pfizer’s Dr. John Perez included enough data about prior infection to conclude boosters did not reduce covid-19 infections relative to placebo in this clinically relevant, ever burgeoning subgroup. Simple calculations (based upon the slides from pages 16 and 17) indicate there were only 2 symptomatic covid-19 infections among the 524 trial participants with a history of prior SARS-CoV-2 infection, 1/275 who received boosters, and 1/249 given placebo injections (p=0.944 for incidence rate difference of 0.038%).
Moreover, CDC’s Dr. Oliver, in her ACIP review (p. 25) of Pfizer’s booster trial data, acknowledged that within the full cohort of ~10,000 there were no covid-19 hospitalizations or deaths, and no data to assess any impact on SARS-CoV-2 transmission.
These findings comprise a striking paucity of randomized trial evidence on the “efficacy” of boosters—literally none on the most clinically relevant outcomes of serious covid-19 morbidity and mortality. Even the potential effect of boosters on SARS-CoV-2 transmission remains unaddressed.
Rapidly accumulating data strongly suggest prior covid-19 infection, “natural immunity,” is more robust, flexible, and enduring than exclusive covid-19 vaccine-acquired immunity. Pfizer’s covid-19 booster trial data confirm boosters afford no benefit in preventing covid-19 infections among those with natural immunity.
Given these overall randomized trial findings regarding covid-19 vaccine boosters—absence of even a short- term reduction in mild covid-19 infections in those with natural immunity, and no data establishing that boosters prevent covid-19 hospitalizations, deaths, or SARS-CoV-2 transmission—there is no rational, evidence-based justification for covid-19 vaccine “booster mandates.”
Author:
Andrew Bostom, M.D. MS, is an academic clinical trialist and epidemiologist, who is currently a Research Physician at the Brown University Center For Primary Care and Prevention of Kent-Memorial Hospital in Rhode Island.
Image via CalMatters. Article cross-posted from Brownstone Institute.
One Sick Day Proves We Need More Voices in Truthful Media
On October 19, I was sick. It crossed my mind that I had finally gotten the ‘rona, but my wife’s cream of chicken soup and a few extra hours of sleep into mid-afternoon had be back up and running after a sleepless night before.
When I finally stumbled over to my computer in the evening, I was met with a deluge of concern from readers. They asked what had happened as only one article had been posted that day. Generally, we post between 10-20 daily between all of the sites, not included curated and aggregated content. Seeing that we’d only posted my super-early morning article before taking the rest of the day off had readers assuming the worst.
We have a wonderful and talented group of writers who volunteer their time for the sites and their readers. Sharing their amazing perspectives has always been a blessing to us because we cannot afford to hire anyone at this time. But having great writers is meaningless if we don’t have great editors, or at least one additional. My wife helps me read and edit stories from time to time, but I’m a one-man show when it comes to getting the stories posted.
Whenever I highlight our desperate need for donations, I note that we do not receive money from Google ads even though most in conservative media are beholden. I often ambiguously note that the money donated will help us grow. Today, I’m highlighting a specific need. We must get an editor to help take some of the load and to expand on our mission of spreading the truth to the world. One sick day proved that.
The great news is that there is no shortage of people who CAN help. I am emailed variations of resumes every week by people who are much smarter than I am. As much as I’d love to hire some of them, we simply cannot. That takes money and as blessed as we’ve been to receive donations and collect ad money (though not from Google or Facebook), we have still fallen short.
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Looks to me like they’re basically trying to claim that all else is essentially equal to a variance of less than 1%. (109-9)/10000
I’m not familiar with how these studies are done, nor am I any sort of expert, but it seems to me there are many possible variables. One being exposure. In order for their numbers to be correct, the variance of exposure from the placebo group to test group would have to be less than 1% – which I’m not sure could be achieved in the real world – or even known, for that matter. It’s entirely possible something like 3000 out of 5000 could’ve been exposed in the placebo group, and 2900 out of 5000 exposed in the test group.
They have no idea who or how many were exposed in each group, and just based on that one factor alone, have no idea whether or not the drug is effective. Let the difference between placebo and test groups be greater than 100, which would be entirely possible, and the “booster” would actually increase the chances of infection.