Debunked: The Study That Claimed COVID Vaccines Saved 20 Million Lives

A Canary Special: How One Flawed Study Misled the World

Watson et al.’s paper shaped global policy—now experts say the math was fiction.

What if one of the most cited COVID vaccine studies—the one used to justify global mandates—was built on fiction?

In this Canary Special guest post, we revisit the Watson et al. paper that claimed vaccines saved up to 20 million lives. Now, independent experts have torn it apart—exposing flawed assumptions, missing data, and deep conflicts of interest. It’s a reminder of how easily narrative can overtake truth when science becomes a tool of policy.

Guest post by Raphael Lataster (BPharm, PhD) - OkayThenNews - Follow his excellent Substack:

The hugely influential study on COVID-19 vaccines, Watson et al, which was used by experts throughout the pandemic to show that the jabs saved tens of millions of lives in one year, has been thoroughly debunked, by yours truly (a misinformation researcher now primarily focussed on COVID-19, not least because of being fired for refusing the jab and winning subsequent legal cases), with the critique finally published in a peer-reviewed medical journal. Source. This is the 1st of a 3-part metacritique of 6 influential studies on the COVID-19 vaccines, with similar problems identified throughout. The same criticisms would apply to many more studies.

Lataster explains:

• I start by noting that such studies have received very little scrutiny. One wonders why the Universe left this vitally important task to me, a sole former pharmacist and misinformation researcher/philsopher who was more interested in issues like the meaning of existence, with no funding, and struggling at life since being (and continuing to be) persecuted for refusing the jab. Perhaps understandable if you consider who is paying most of the medical researchers out there (and we will get to that), but still baffling when considering the amount of talent on ‘our contrarianside’, the side filled with experts who bucked the trend on the pandemic and pretty much got everything right. A little serendipity involved, too, as I partly did this because US Senator Ron Johnson pretty much asked me to.

• On to the study. Firstly, Watson et al “revolves around a model which, by definition, is not truly representative of reality”. Remember, people, the map is not the territory. And models are beholden to the GIGO principle. Garbage in, garbage out. And when it comes to these studies like Watson et al, there’s a lot of garbage to sift through.

• Then I note that their vaccine efficacy/effectiveness estimates are dodgy, bringing in ‘JECP4’, the published research I did alongside BMJ senior editor (and one of my intellectual heroes) Peter Doshi. They have been exaggerating efficacy/effectiveness (and safety) in a really big way by doing things like ignoring incidents in the ‘partially vaccinated’, or even counting them as happening in the ‘unvaccinated’. Collectively, Doshi’s team and I mathematically demonstrated: “Such methodology can make a completely ineffective vaccine appear 48% effective, or even around 65% effective, if cases in the "partially vaccinated" are ascribed to the "unvaccinated." In fact, even a negatively effective vaccine can, in this way, be made to appear moderately effective.”

• It is unclear how the authors “determined the effectiveness of the vaccines in

  preventing death”. If they “utilized the original clinical trials of the mRNA COVID-19 vaccines, along with recently published reanalyses, they would have noted no statistically significant decrease in COVID-19 deaths among the vaccinated groups, a statistically significant increase in serious adverse events of special interest, and a non-statistically significant increase in total deaths”.

• Another big problem is static vaccine effectiveness estimates, with the researchers assuming that the vaccine happily continues being as effective as ever, for ‘simplicity’, which we now know is complete nonsense. They’re literally spruiking boosters every few months! Remember the GIGO principle. Opt for nice things like ‘simplicity’ in your models, and this is the trash you will get in return.

• I note that not only do the jabs become ineffective really quickly they even seem to become negatively effective - yeah you heard me, apparently increasing your chance of COVID-19 infection, and even death.

• They also made big assumptions on “infection fatality rates (IFRs)”. They didn’t even bother to justify (or even disclose?) their preferred figures. If you’re exaggerating COVID-19 deaths, and they do, as they all do, you’re eventually going to be exaggerating the benefits of the jabs. A super important study came out just as this critique was in publishing. Looks like they’ve been (at least) doubling COVID-deaths, the old with COVID/from COVID debate.

• Did the benefits outweigh the risks? Surprisingly, from this hugely influential study, you’d never know. They don’t seem to care about “the deaths and injuries

  caused by the vaccines”. What’s the point of saving 14 million lives if you’ve killed 28 million? Bit of a missed opportunity, don’t you think? It does appear the jabs do injure and kill people, which was obvious even from the beginning, from their own clinical trials. Perhaps there was more in the Pfizer trial, with (published) questions over potentially fraudulent activity. Later studies show way more side effects, and I’ve argued in a BMJ journal that the myocarditis risk alone outweighs the ‘benefits’ of the jab in young healthy people.

• They also did things like using ‘estimates’ of “all-cause excess mortality” because they didn’t actually have the data. And note the assumption that excess mortality is all due to COVID-19, rather than, oh I don’t know… the jabs. They don’t even acknowledge the possibility, even though we know for a fact that the vaccines have killed people - what we can dispute is the number.

• With unjustified figures, made-up data, omitted data (China, which has a huge chunk of the world’s population), and even data collected from non-academic sources (like an economics magazine!), the authors actually admit to “wide uncertainty”. Somehow that wasn’t expressed when all the experts, politicians, and newsreaders were proclaiming the study’s earth-shattering conclusions.

• Funnily enough, their own charts “reveal that deaths were already

  declining before widespread vaccination (January–February 2021), only to rise again after significant vaccine uptake (August 2021)”. While we’re on excess mortality, a few researchers have noted that this is occurring even though the pandemic is over, and some (hi there) have even noted a correlation with the… COVID-19 vaccines. [I have another excess deaths article coming out later that definitively shows it isn’t COVID-19, it isn’t the lockdowns, it’s the jab. Just waiting on publishing.]

• Finally, we move on to financial and political conflicts of interest. Read every word of this bit. The study’s authors have financial links to vaccine manufacturers, WHO, the Wellcome Trust, and our old friend, the one expert we all had to see as an expert despite him not having a single earned academic degree, Bill Gates. Politically, the boss of the research team is none other than Neil Ferguson, “Professor Lockdown”, also known as the moron that was wrong about everything, and who “was caught violating the very lockdown measures he had advocated by having an affair with a married woman during the restrictions”. Not a righteous dude. This is going to be a theme in this 3-part series. The people behind the research on the jabs tend to be funded by the manufacturers and/or the governments that approved, encouraged, and even mandated the vaccines. I even go a little further, explaining that Big Pharma, the mainstream media, and just about everything else, is effectively owned/controlled by a handful of very rich people.

• I also summarise some of the research demonstrating that “the

  pharmaceutical industry funds and arguably influences major medical journals that publish favorable studies by these same scientists, as well as the peer reviewers for these journals—just as it sponsors clinical trials of its own products, which predictably yield results more favorable to its interests compared with independent studies”. Oh, and don’t forget that they fund their own regulators. What fun!

• I end with the customary recommendations: “To accurately assess the number of lives truly saved by these vaccines, Watson et al and others should repeat their analysis using more rigorous and transparent methods: incorporating conservative estimates of vaccine effectiveness, given recent concerns about counting-window methodologies; accounting for rapidly waning and potentially negative effectiveness; using accurate, clearly disclosed IFRs and CFRs; giving preference to available evidence over speculative estimates; and ideally, conducting the research independently, without financial ties to vaccine manufacturers, their shareholders, or organizations that promote and mandate these vaccines.”

Well, there you have it. Make sure you, um, Trust the Science, and all that… Especially when that dodgy science spreads everywhere in a heartbeat and takes a good 3 years to be debunked. Somehow I don’t think this takedown will be featuring in the big journals and the nightly news - they’ve already said ‘no’.

The FDA/US government is now aware of my critique. It’s time for action.

And now the US Senate is aware, adding it to the record.

Christof Plothe, DO. at the World Council for Health (Follow their excellent Substack) also published this critique on Raphael Lataster’s study:

For three years, governments, media, and pharmaceutical giants wielded one "unassailable" fact: COVID-19 vaccines saved 14.4 million lives in 2021 alone. This claim—from the infamous Lancet study by Watson et al.—justified mandates, silenced dissent, and shielded manufacturers from liability.

Today, that narrative lies in tatters.

In a landmark meta-critique published in the Journal of Independent Medicine, researcher Dr. Raphael Lataster dismantles the Watson study brick by brick, exposing it as a house of cards built on flawed assumptions, hidden conflicts, and statistical sleight-of-hand. Even more damning? Real-world mortality data proves the claim is mathematically impossible.

How Watson et al. Got It Catastrophically Wrong

Lataster’s forensic analysis reveals seven fatal flaws in the "14 million saved" model:

"Garbage In, Gospel Out" Modeling

Watson et al. relied on speculative inputs—not real-world outcomes. Their model assumed:

• Permanently high vaccine efficacy (90%), ignoring rapid waning and negative effectiveness (where vaccines increase infection/death risk months post-injection).

• Inflated COVID fatality rates, sourced opaquely to exaggerate the virus’s deadliness.

• No accounting for vaccine injuries (myocarditis, deaths, or long-term damage).

The "Counting Window" Scam

• The study used efficacy data from trials that excluded infections in the "partially vaccinated"—a trick Lataster and BMJ editor Peter Doshi proved can make a harmful vaccine appear 65% effective.

• Real-world data? Ignored.

While Watson’s model spun fairy tales, hard statistics screamed the opposite:

• 6.08 million MORE people died in 2021 than in 2020—despite global vaccine rollout

• Mortality rates were 14.5% higher among the vaccinated vs. unvaccinated.

Translation: If vaccines "saved 14 million," why did total deaths RISE?

The Neil Ferguson Factor

The study was led by Neil "Professor Lockdown" Ferguson—whose prior pandemic models collapsed under scrutiny—and funded by Gates-linked entities (WHO, GAVI). Peer reviewers were most likely Pharma-funded.

Meanwhile, a new study which I co-authored was published

Download

The objective was to evaluate validity of models estimating deaths averted by COVID-19 vaccines. Its core findings were concerning:

• Constant high vaccine efficacy (ignoring waning immunity).

• Exclusion of vaccine adverse events (e.g., myocarditis fatalities).

• No adjustment for age (most "averted deaths" were elderly, yielding few life-years saved).

Transparency issues:

• Account for waning immunity, adverse events, and age-stratified outcomes.

• Use metrics like life-years saved (not just deaths averted).

• Ensure full transparency (code/parameters accessible).

The papers also noted that current models risked misallocating public health resources by overstating vaccine benefits.

Why This Matters Beyond Science

The Watson study wasn’t just wrong—it was a tool:

• Prominent scientist Peter Hotez cited it to smear vaccine critics as "killers."

• Regulators used it to block early treatments.

• Governments invoked it to impose mandates.

Yet as Lataster’s work reached the US Senate (

Lataster’s challenge to authorities:

"You have the data. Retract Watson et al. Halt mandates. Compensate victims. Or admit science bows to Pharma."

The Bottom Line

The "14 million saved" myth was never science—it was mathematical propaganda crafted by conflicted modelers. Real-world data, mortality statistics, and new research by scientists like Lataster and Plothe reveal the truth:

The COVID-19 vaccines failed their risk-benefit test—especially for the young and healthy.