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 focused 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. This is the first of a three-part metacritique of six influential studies on the COVID-19 vaccines, with similar problems identified throughout. The same criticisms would apply to many more studies.
- I start by noting that this study (and these studies in general) have received very little scrutiny. One wonders why the Universe left this vitally important task to me, a sole former pharmacist and misinformation researcher/philosopher 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 contrarian side’, 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 “utilised 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 perhaps 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 since Omicron, the old with/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, say, 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 were 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 (e.g. 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.
Hellbound and Down 