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Ben Profile picture
@USMortality
Jan 11, 2022 • 19 tweets • 9 min read • Read on X
Scrolly
JUST IN: Final Germany Age-Adjusted Mortality Update for 2021!
> 2020: Excess of +1.6%
> 2021: Excess of +1.8%

1/n
 #Covid #Covid19 #Corona #Coronavirus
Here's the time series:
By quarter:
> Q4/2020: Excess +9.3%
> Q4/2021: Excess +10.6%
Covid-19 matches excess mortality pretty well, however in the sum it replaced flu almost 1:1!
If there weren't any COVID-19 deaths, this is what the mortality figures would look like!

To get to exactly 0% excess mortality, Germany would have still to have 87% of it's COVID-19 deaths.
Sources & Calculations: docs.google.com/spreadsheets/d…
By age groups 0-44:
By age groups 45-64:
By age groups 65-84:
By age groups 85+:
Sheet: docs.google.com/spreadsheets/d…
Matrix for each German state (up to week 49/2021):
Difference Matrix for each German state (up to week 49/2021):
Sheet: docs.google.com/spreadsheets/d…
For each individual state, see the Toolbox here: docs.google.com/spreadsheets/d…

E.g. here Saxony/Sachsen which has the highest excess mortality in Germany so far!
Two things to keep in mind for the German state comparison, though!

> Age bins provided by @destatis are too coarse! 0-65, etc.
> Excess mortality correlates very well with obesity levels by German state:
Also based on the above Difference Matrix, we can look how the states are doing this year and correlate this to the vaccination levels!

There's no correlation R2=0.02, p=0.93!
Ultimately we must look at all-cause deaths by vaccination status in order to assess any effect!
Updated Obesity map, h/t @orwell2022

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More from @USMortality

Ben Profile picture
Aug 20
💥💥💥 An official CDC FOIA response confirms that the validation of the SARS-CoV-2 genome has not been completed to scientific standards! 💥💥💥

CDC Unable to Scientifically Verify Full SARS-CoV-2 Genome, Leaving Potential for Semi-Random Construct.

🧵 A thread...Image
The response:

CDC has responded to my FOIA request, in which I have asked for records related to these four points:

1. Records on single virion sequencing of SARS-CoV-2 that ensured the virion was physically isolated from any other genetic material before sequencing.
2. Records of a single sequencing (long-)read from the first position [..] to the last position [..] of the genome. [..]
Read 17 tweets
Ben Profile picture
Jun 5
This may as well be part of the script/disinformation campaign after all:

>> This is important to understand <<

Hypothetical Disinformation Campaign Scenario

1. Initial Denial:
• Key Players: Military, secret agencies, health authorities, virologists, philanthropists, etc.
• Action: Strongly deny any allegations of a secret operation involving a lab-manufactured virus leak (commonly referred to as the “Lab Leak Theory”).
• Narrative: Label the lab leak theory as a baseless conspiracy, dismissing it without thorough investigation.

2. Diversion:
• Media Strategy: Shift the focus of the media to alternative explanations, such as the “Zoonosis Theory” (natural transmission from animals to humans).
• Examples: Highlight potential sources such as bats and pangolins to distract and redirect public attention.
• Impact: This redirection aims to convince the majority of the population (~70%) to believe in a "viral spillover", thus novelty of the virus.

3. False Confirmation:
• Controlled Leaks: Release unverifiable “evidence” that appears to confirm the lab leak theory through credible sources.
• Staged Reports: Media outlets present findings like the Furin Cleavage Site or HIV inserts as proof of the lab-manufactured origin.
• Public Reaction: Skeptics (~25%) quickly adopt this narrative, now able to direct their frustration towards those seemingly responsible.

4. Framing:
• Agenda Alignment: Shape the lab leak confirmation to justify specific actions or policies that stakeholders wish to implement.
• Justifications: Use this narrative to defend the necessity of questionable virological surveillance, mass testing, lockdowns, masking, and mass vaccinations as preventive measures.

5. Public Manipulation:
• Perceived Investigation: Convince the public that the origin of the virus has been thoroughly investigated and validated, creating a false sense of certainty.
• Acceptance: The public now either believes in the perpetual risk of natural spillover or lab leak pandemics, leading to widespread acceptance of continuous countermeasures.
• Focus Shift: Rather than calling for the cessation of Gain-of-Function (GoF) research, the narrative shifts to the inevitability of such research due to its international nature, emphasizing the need for ongoing measures like viral surveillance, mass testing and vaccinations.

Summary: Stakeholders deny the “Lab Leak Theory,” redirect media to natural origins, then release false evidence supporting the lab leak to win over skeptics. This frames their original techniques and countermeasures as necessary, manipulating the public into accepting any future measures.Image
Instead, people like Dr. Binder have pointed out since 2020, that the use of mass PCR testing, is entirely responsible for this phenomenon:
In addition, Dr. Rancourt has shown strong epidemiological evidence, that the mass casualties that were observed in some regions cannot be caused by a novel risk-additive pathogen:
Read 4 tweets
Ben Profile picture
May 7
🧵Thread of posts showing no COVID-19 vaccine efficacy!

Read 17 tweets
Ben Profile picture
Apr 25
There are several problems with the reference genome (b) published by Wu et al. 2020 (a):

1. The sequenced patient sample contained genetic material from different sources: human, bacterial, viral, etc. Although known sequences were filtered out after sequencing, there is no guarantee that all non-novel-viral sequences were actually removed.

2. The patient's human genome was not sequenced for control.

3. Reassembly of the dataset published by Wu using Megahit does not provide the exact or complete sequence as published.

4. Trinity, the second program used for de novo sequencing, is unable to generate the identical contig.

5. When using untrimmed or protocol-trimmed reads (Takara), no reads are found that perfectly match both ends of the genome. This is unusual because, according to a theoretical simulation, several ends should be found in the sample. (c)

6. It has not yet been proven that the entire sequence (~30 KB) actually occurs in this form in the samples, e.g. by agarose gel electrophoresis or (Sanger/whole genome) sequencing.

7. Wu et al. published three versions of the reference genome, the first of which contained known sequences from the human reference genome. The fact that the first version contained human sequences suggests possible problems with sequencing or analysis.

8. The amplicons, i.e. the sequences of the ends found using RACE, have not been published. The non-publication of the amplicon sequences raises questions about the transparency and reproducibility of the study.

9. The only non-Chinese author of this paper, Eddie Holmes, confirmed to me by email that he had no detailed knowledge of these issues. There was silence from the Chinese side, although questions were asked via Holmes. (d)

These clear scientific problems therefore clearly call into question the validity of the SARS-CoV-2 sequence.

(a)
(b)
(c)
(d) ncbi.nlm.nih.gov/pmc/articles/P…
ncbi.nlm.nih.gov/labs/virus/vss…
usmortality.substack.com/p/why-the-ends…
usmortality.substack.com/p/why-do-wu-et…
10. Wu et al., only published a single run, which is supposed to prove the sequence.
11. Wu claims they found a complete sequence before they actually knew its true length - they were just missing the ends, which they then added manually via RACE.
That's a fallacy - because how can one determine the length of a new sequence without first finding the ends, and thus the true length?
Read 7 tweets
Ben Profile picture
Mar 17
There's a large pharma funded Measles Scare Campaign ongoing.
The actual data doesn't support this.Image
ecdc.europa.eu/sites/default/…
World:
Read 8 tweets
Ben Profile picture
Mar 7
‼️ Phantom Vaccine Efficacy!

A list of statistical tricks, that can be used to calculate an illusion of vaccine efficacy with a placebo alone.

For this exercise, I have used a sine wave to simulate weekly deaths:Image
... and a logistic growth function to simulate placebo vaccination from 0 to 75% of the population.
By the green/red dots, we can see no difference/effect, as no statistical tricks are applied yet. Image
Trick 1: Unknown Vaccination Status --> Unvaccinated.

If 50% of Unknown vaccination status is treated as unvaccinated, almost 3x higher mortality rates appear for unvaccinated. This is entirely an illusion. Image
Read 6 tweets

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