Dr Clare Craig Profile picture
Feb 7, 2023 18 tweets 6 min read Read on X
This graph is a lie.

It is very easy to show you why.

It is claiming to show a cumulative death rate by vaccination status in a population with heart failure.

onlinejcf.com/action/showPdf…
Let's unpick it bit by bit.

They measured deaths from 1st Jan '21 to 24th Jan '22.
A total of 389 days.

Let's check, the last value on the graph.

They give us the size of the population in each group at the end of the study.
Using the deaths in the table, the cumulative incidence curve for mortality should peak at:

unvac = 599/3196 = 0.19
partially = 75/645 = 0.12
fully = 195/2200 = 0.09
boosted = 36/1053 = 0.03

Hmm - that's not what the graph shows.

Let's dig a bit deeper.
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.

Eventually it all evens out as time catches up.
The ONS have described it here:
ons.gov.uk/peoplepopulati…
It is not evidence that the vaccine saved lives.

The claims that vaccine would impact on death outcomes beyond covid has always been a bizarre one.
There were 904 deaths in this population during the study period.

Nowhere do they say how many were deaths with a mention of covid.

Now, isn't that a bit odd for a paper on deaths after covid vaccination?
Note that the data for hospitalisation for the unvaccinated is not shown but is instead merged with the partially vaccinated.

People who didn't complete the initial course may represent those who became very unwell after vaccination, coincidentally or through injury.
Please feel free to try and squeeze a vaccine favourable picture out of the raw data by altering the population sizes that I estimated.

You will struggle to.
One author has responded with the excuse that I did not account for censoring.

I have redone the graphs having removed those who had died from the denominator.

They look almost identical.

The message remains the same.

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More from @ClareCraigPath

Feb 29
Here's the UN strategy to manipulate what you thought:

30mins
Image
It goes on... Image
Absolutely explicit in their role in censorship. Image
Read 4 tweets
Feb 24
1/9 🧵

ONS aren’t the only gov agency to model expected deaths.

OHID do too.

Their method is simpler:
1. Take average from 2015-2019
2. Adjust for subsequent population growth
3. Adjust for subsequent ageing

The difference between these models is stark. Image
2/9

The ONS have not released their data for England by age only for the UK as a whole.

To compare with OHID I took the ratio of expected deaths in 2020 and 2021 and used that to scale the OHID England estimate to all of UK.

It goes off the rails in mid 2022. Image
3/9
The difference is ~ 7.5K extra deaths in 2023 that the ONS “expect” compared to OHID.

12% more than the OHID expectation!

For every 8 people that OHID expects to die, ONS will ignore another death and call it “expected”.

The dotted line shows the trend over time. Image
Read 10 tweets
Feb 24
I have buried myself deep in the ONS data today in an attempt to redeem myself after my mistake with accidentally including Wales in my sums earlier this week.

In brief, ONS have moved from predicting deaths based on previous years to modelling them.
It look complex but... Image
it is mostly justifiable.

Each zigzag sigma symbol just means "add them all up".

The modelling calculates an estimate for lots of small groups and then adds them together.
That way each of

· 19 age groups,
· sex,
· 8 regions,
· the preceding trend in an age group (i.e. were deaths increasing or decreasing recently),
· the time of year (although they forgot the 12th month!),
· the day of the week

contribute to expected number of deaths. Image
Read 8 tweets
Feb 22
This large hike in numbers is from the baby boomers feeding through and is evident when they switched categories before.

This is what it looks like over time for old and new methodology.

Let me explain in a couple more tweets. 🧵
Image
ONS have just expanded pop by ~5% for every age group since 2005.

A bigger population means a lower mortality rate (deaths per 100k people_.

This is what the mortality rates look like for each age group now.

Hard to see any impact from covid.

Here are over 90 yr olds: Image
80-89 yr olds: Image
Read 13 tweets
Feb 18
White blood clots occurred pre-covid panic in the arterial system.

They are white because there are few red blood cells in them - it's a sign they were made in a high flow environment.

Vaccine injury can contribute.

Here's how. 🧵

ncbi.nlm.nih.gov/pmc/articles/P…
Image
1. The mRNA platform results in foreign protein expression in endothelial cells and their consequent death. This creates a pro-thrombotic surface.

ncbi.nlm.nih.gov/pmc/articles/P…
2. Spike results in platelet activation.

The receptor binding domain (included intact in the vaccine) alone “could bind platelets, cause platelet activation, and potentiate platelet aggregation.”

in mice.



and here spj.science.org/doi/10.34133/r…
pesquisa.bvsalud.org/global-literat…
Read 17 tweets
Dec 9, 2023
Here's an interesting accusation.

1. I have never, ever promoted these products in any way.

2. I do not promote them now.

It all comes down to understanding the two biggest lies you were told about the virus.

The Tsunami Lie.

🧵
The lie we were told was that there was a novel virus and that everyone would catch it.

We were ALL susceptible, you see.

The lie was based on believing in the measles model of transmission. Image
When a population is naive to measles, it spreads and everyone will catch it.

This was seen in the Faroe Islands in 1846 where there hadn't been an outbreak for 65 years.

But it NOT true for influenza. Image
Read 31 tweets

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