Let's ignore the vaccinations for a moment and see how many people died over time.
Here we see two spikes in the death curve.
Why would that be?
It is not a good match for covid deaths in USA at the time.
I have tried to reverese engineer the calculation of the rates. We have the deaths and we have the starting and final population sizes for each group.
The rest is estimated.
There is only a small range of possibilities for the population size of each group each week.
This is what the cumulative incidence chart looks more like in reality:
But cumulative charts can hide a lot of interesting information so I also plotted it as the actual number of deaths ocurring in each period.
e.g. Subtracting the penultimate column from the last column shows deaths in last 49 days of the study gives
32
9
27
12 deaths.
Plotting the deaths that occured in each period as a mortality rate gives this.
The high yellow point was only 2 deaths in a small population - it can be ignored.
What we see is that in the early period the deaths were seen in the unvaccinated population but as time went on deaths started in the vaccinated population.
By the end the death rate was the same in all groups.
This is evidence of what is called a "healthy vaccinee effect."
It is the phenomenon of the dying rejecting a vaccine. They then die unvaccinated while the apparent death rate of the vaccinated population seems low for a while.
All the vaccines ever did was make people immune suppressed for two weeks.
The consequence was that those who were susceptible to a particular variant had their infections earlier than they would have.
You can measure after that point and get an illusion of benefit.
This trick only works if you vaccinate during a wave.
For the UK - we were fast getting to those most susceptible to dying. Our death wave looks like a witch's hat on top of Europe's because of the earlier infections.
The last 4 years has been a period of modelling based on assumptions laundered through the medical literature and called "The Science".
If you thought the "real world" evidence was more reliable think again. 🧵
@Jikkyleaks has exposed a massive fraud at the heart of the covid literature.
Instead of using the difficult, fragmented and hard to collate data from the actual real world, pharma sponsored datasets which contain modelled synthetic data were used.
Like all models this synthetic data will have been based on prior assumptions:
assumptions like vaccines preventing 96% of infections.
The consequent results stand out ludicrous disprovable claims.