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Reports came in. Let’s crunch some numbers!

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All calculations below use death statistics.  These calculations use data from government sources.  Some analyses are being done using numbers from all-cause deaths, which have increased significantly.  One of these analyses is shown in Statistics and Calculation #5.  Under Statistics and Calculation #4, I also show a chart of relative risks compared to other causes of death.

Were we to do the same with statistics for those suffering from life-changing adverse events, there would be much greater cause for concern.  Unfortunately, those statistics are not as readily available.

It is probably at least as important to check statistics for life-changing adverse events as well, since they affect quality of life, but those are not as readily available.

It is difficult to know how these numbers might have been different had early treatment been part of the standard protocols.  Early treatment protocols do exist, but they are generally shunned by mainstream doctors.  Given the success reported by those who use early treatment protocols, failure to provide care according to these early treatment protocols is medical negligence at best and possibly criminal.

It is also difficult to know how many of the “unvaccinated” in these statistics are actually freshly vaccinated people who suffered an adverse event.  In a statistical sleight of hand, those who received their first dose within 14 days of death are reported as “unvaccinated.”

Statistics and Calculation #1

Calculations someone did based on Technical Briefing 21

The case numbers come from page 22 of Technical Briefing 21, “Delta cases” block, “All cases” line, last two columns.  The death numbers come from page 23 of Technical Briefing 21, last line of chart, last two columns.

Vaccine status Cases Deaths Ratio Deaths per 100,000
>14 days post dose 2 73,372 679 679 ÷ 73,372 = 0.00925421 925
Unvaccinated 183,133 390 390 ÷ 183,133 = 0.00212959 213

925 ÷ 213 = 4.34

These numbers show that vaccinated COVID-19 patients are more than 4 times more likely to die than unvaccinated COVID-19 patients.

It appears that England is using the same 14-day qualifier for COVID-19 death classifications. If so, then some of the deaths in the unvaccinated row had just gotten the jab.

Source for Statistics and Calculation #1:

Statistics and Calculation #2

The video linked below explains how the calculations are done.  The numbers come from the last two columns of the chart on page 14 in the Week 36 report.

Age Group Cases among
vaccinated
per 100,000		 Cases among
unvaccinated
per 100,000		 Cases among
vaccinated
per 100,000		 Cases among
unvaccinated
per 100,000
Under 18 476 1,192.9 1,969.3
33.80%		 3,857.6
66.20%
18 – 29 711.1 1,520.8
30 – 39 782.2 1,143.9
40 – 49 1,116.2 880.4 3,622.1
55.60%		 2,892.5
44.40%
50 – 59 962 729.7
60 – 69 672.3 487.5
70 – 79 480.5 367.5
80 and over 391.1 427.4
5,591.4
45.31%		 6,750.1
54.69%

It would appear that people older than 40 are less likely to get sick if they have not been vaccinated.

It appears that England is using the same 14-day qualifier for COVID-19 death classifications. If so, then some of the deaths in the unvaccinated columns had just gotten the jab.

Sources for Statistics and Calculation #2:

Statistics and Calculation #3

The following is based on Infection Fatality Rate Scenario #5 in the CDC’s COVID-19 Pandemic Planning Scenarios.  These are PROJECTIONS, not actual numbers.  Actuals are shown in Statistics #4.

Age Group Deaths in
1,000,000		 Survival
Rate		 Death
Ratio
0 – 17 years 20 99.998% 1 in 50,000
Teens at NSW stadium jab event, on the spot1 125 99.988% 1 in 8,000
18 – 49 years 500 99.950% 1 in 2,000
Teens at NSW stadium jab event, estimate over time2 625 99.938% 1 in 1,600
50 – 64 years 6,000 99.400% 1 in 167
65 years and older 90,000 91.000% 1 in 11
  1. Numbers extrapolated to the rate per 1,000,000 so that they can be properly compared with other numbers in this chart.  And these teens could still become infected with COVID-19 later.
  2. Numbers extrapolated to the rate per 1,000,000.  This is a conservative estimate based on 5 times the number who died at the event.  The multiplier was obtained by eye-balling a “death curve” from an analysis of VAERS numbers.  The multiplier could be accomplished in less than a week, according to the numbers on the “death curve.”

Sources for Statistics and Calculation #3:

Statistics #4

Generally, elderly people who live in the general community have a high survival rate.  Oddly, the IFR in UK was much higher than anywhere else, both for the community-dwelling and institutionalized.  UK has one of the highest jab rates in the world with the rate among institutionalized elderly virtually 100%.

We could extract data and calculate IFR on another 84 age-strata observations from 19/23 seroprevalence surveys (three had no mortality data for any eligible non-elderly age stratum (25, 30, 35) and one sampled no individuals <65 years of age (44)). The 19 surveys came from 11 countries. For the age group 0-19 years, only five studies had sampled participants for seroprevalence in the corresponding age group (24, 29, 31, 38, 41); for the other studies, the closest available age group was used. Across all countries (Figure 3), the median IFR was 0.0027%, 0.014%, 0.031%, 0.082%, 0.27%, and 0.59%, at 0-19, 20-29, 30-39, 40-49, 50-59, and 60-69 years, using data from 9, 9, 10, 9, 11, and 6 countries, respectively.

Just for fun and comparison, I’m going to mix some general death statistics into this next chart.  We will all die of something.  How do our odds of dying of COVID-19 stack up to other causes of death?  When we look at the numbers this way, it doesn’t look so grim.  The added statistics will be marked with  this background .

Age Group Deaths in 1,000,000 Survival Rate Death Ratio
Struck by lightening 12 99.9988% 1 in 84,079
Dog attack 12 99.9988% 1 in 86,781
COVID-19, 0 – 19 years 27 99.9973% 1 in 37,037
Sharp objects 34 99.9966% 1 in 29,334
Sunstroke 121 99.9879% 1 in 8,248
Teens at NSW stadium jab event, on the spot1 125 99.9875% 1 in 8,000
COVID-19, 20 – 29 years 140 99.9860% 1 in 7,143
Airplane crash 142 99.9858% 1 in 7,032
COVID-19, 30 – 39 years 310 99.9690% 1 in 3,226
Teens at NSW stadium jab event, estimate over time2 625 99.9375% 1 in 1,600
Fire or smoke 646 99.9354% 1 in 1,547
COVID-19, 40 – 49 years 820 99.9180% 1 in 1,220
Drowning 887 99.9113% 1 in 1,128
Motorcyclist 1,112 99.8888% 1 in 899
Pedestrian incident 1,842 99.8158% 1 in 543
COVID-19, 50 – 59 years 2,700 99.7300% 1 in 370
Gun assault 3,460 99.6540% 1 in 289
COVID-19, 60 – 69 years 5,900 99.4100% 1 in 169
Motor vehicle crash 9,346 99.0654% 1 in 107
Falls 9,434 99.0566% 1 in 106
Opioid drug overdose 10,870 98.9130% 1 in 92
Suicide 11,364 98.8636% 1 in 88
COVID-19, Community-dwelling elderly, all locations 24,000 97.6000% 1 in 42
COVID-19, All elderly, all locations 55,000 94.5000% 1 in 18
COVID-19, Community-dwelling elderly, Public Health England 85,900 91.4100% 1 in 12
COVID-19, All elderly, Public Health England 140,300 85.9700% 1 in 7
Cancer 142,857 85.7143% 1 in 7
Heart disease 166,667 83,333% 1 in 6
  1. Numbers extrapolated to the rate per 1,000,000.  And they could still become infected with COVID-19 later.
  2. Numbers extrapolated to the rate per 1,000,000.  This is a conservative estimate based on 5 times the number who died at the event.  The multiplier was obtained by eye-balling a “death curve” from an analysis of VAERS numbers.  The multiplier could be accomplished in less than a week, according to the numbers on the “death curve.”  The actual number of deaths resulting from this event are likely to be higher.

Sources for Statistics #4:

Statistics #5

Here is a novel idea.  Don’t be so concerned for whether the injections actually killed the people.  Just look at all-cause mortality and whether the person had ever taken a COVID-19 vaccine.  Fortunately, England has the data needed for this one. Please see the article for details of how the authors came up with these graphs.  They state:

It turns out that, even using this age adjusted mortality rate, the death rate is currently higher among the vaccinated than the unvaccinated.

Sources for Statistics #5:

It appears that England is using the same 14-day qualifier for COVID-19 death classifications. If so, there actually could be far more deaths among the vaccinated than at first it appears.

Extra source:

  • Video
    October 10, 2021. Simple Statistical Analysis Showing the INSANITY of Taking the CV19 “Vaccine.” Jim Fetzer. Runtime: 2:56.
    https://www.bitchute.com/video/BlxdEzTTWDaI/.
    Video.
    “Once you’ve applied a moment of critical thinking, you’ll find that anyone advocating these requests (‘mandates’) is either uninformed, irrational or has an ulterior motive for suggesting that everyone should be vaccinated.”

See also, on this site:

The following is the “death curve” from an analysis of VAERS numbers.  I used this to estimate how many actually died over time as a result of the NSW stadium jab event.

Screen print from Tim Truth: Deaths by Day Since Vaccination

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