Further evidence of mRNA injections associated with both COVID deaths and excess non-COVID deaths.
Re-analysis of deaths of 18 to 55 year olds in the USA
Inspired by the stellar work of the intrepid John Dee, I have re-analysed the SSA mortality data I have been working with:
Out of curiosity, I wanted to test John’s modelling approach and validate his results using a different dataset. Based on England data, he concluded that the mRNA experiment could be held accountable for one-third of non-COVID excess deaths based on results showing a statistically significant relationship between mRNA dosing rates and deaths 23 weeks later. Of course, this corroborates the work of Steve Kirsch as well.
First, I plotted COVID deaths for 18 to 55 year-olds against my calculation of excess deaths (see previous articles for methodology).
Evidently, there is a very clear relationship between excess deaths and COVID deaths (my excess deaths model is good ✅). We can confirm our eyes do not deceive us by doing a simple linear regression and we find that more than 95% of the excess deaths can be explained by COVID with a p-value of 0.00%, i.e. statistically significant.
However, we can also clearly see that there are more excess deaths than COVID deaths, so we have non-COVID excess deaths to explain. I’d say 8% of the excess deaths given that the COVID co-efficient is 1.08.
The burning question recently is - are these non-COVID excess deaths due to the mRNA experiment, lockdowns and everything associated with them, or something else? Perhaps, even under-diagnosed COVID deaths?
The pro-vax camp have done everything they can to pin it on interventions (without actually putting forward any evidence to support the presumption). I guess it’s easier to maintain that this is just the collateral damage of all the millions of lives they saved from COVID? It also means, they can carry on milking the mRNA cow (until her udders bleed).
Given that the sacred cow doesn’t feed me, I have no constraints in investigating any possible relationship between the mRNA and excess deaths so here goes…
If we plot non-COVID excess deaths against VAERS reports (my proxy for mRNA jabbing activity) 22 weeks later, we can observe some sort of pattern there too. John’s model generated 23 weeks as the optimal lag so we we’re only one week apart and we are looking at different countries and different age cohorts. That's pretty compelling!
Non-COVID excess deaths appear to peak when the mRNA experiment is at its most active, decrease as jabbing subsides, have a little resurgence at the start of 2022 (concomitant with boosters?) and then decline to much less significant levels as virtually no-one is taking part in the experiment any more.
In terms of raw statistics, we have increased the explanatory power of our model from 95% to 98% and our new variable also has a p-value of 0.00%, again highly significant in statistical terms.
The COVID co-efficient has dropped to 0.94 so with 98% explanatory power, would it be unreasonable to say that almost 6% of the excess deaths are caused by the mRNA experiment?
We could leave it there and conclude that the evidence shows that the mRNA experiment is associated with non-COVID excess deaths materialising 22 weeks later, just like John and Steve.
However, I cannot just leave it there.
These deaths should be considered in the context of risk benefit. If the lives saved by the mRNA experiment are substantially higher than the deaths caused then this should be taken into consideration.
Alas, much like we observed in my own previous analyses of the English data, by the time everyone is “protected”, COVID (and excess deaths) have already subsided, so it’s impossible to determine if they were protected from COVID at all.
Moreover, by the time COVID returns in the summer, its death toll is much higher than it was during the usual high mortality season in the winter. Wait, what?! Did I actually just say that with a straight face? The seasonal pathogen returned out of season and wreaked more havoc than it did in the high season? **Shakes head incredulously. How could this be so?
Well, of course, I have hypothesised many times that the only plausible explanation for this is because the host (the human) has been compromised - not because the virus has mutated to become more virulent. **Shakes head again.
Can we test this hypothesis with our new tools? For sure, we could regress COVID deaths on their own against the lagged VAERS reports, couldn’t we?
Mmm… unless my eyes deceive me, I’m thinking there’s a pattern emerging there too? I can’t make sense of that first VAERS distribution. Perhaps, they were the ones who suffered acute adverse reactions, whereas the second main distribution are the chronic developments?
At any rate, the data is telling us that in statistical terms, almost 40% of the COVID deaths can be explained by the COVID VAERS reports and once again, we’ve got a highly significant p-value of 0.00%.
If nothing else, this is surely a lead that public health authorities would do well to follow and rule out?
But if I were you, I wouldn’t hold my breath. Do what you think is right, which by the looks of things is exactly what the young Americans have done, judging by the fact that no-one is taking part in the experiment any more.
For further reading on this topic, I recommend:
I modelled every lag from 0 to 26 weeks and 22 weeks was the lag that produced the best fit and lowest p-value.