- Excess Mortality 3,834 (+21.4%) in week 46/2021 vs median 16-20 (not age/pop. corrected)
- Covid deaths in week 46: (1,129) which only makes up 1/4 of the excess; if covid was the only excess that'd make up +6.4%
So we can see something "strange" might be happening in Germany, majority of excess deaths (75%) are not from covid anymore...
Covid deaths are practically at the same level as last year though:
Because cases are so much higher, CFR is also lower.
Prevalence is likely the same, as latest RKI sentinel showed still 6% prevalence of SARS-CoV-2 for week 46.
Now let's look at excess death correlation vs vaccination for last 4 weeks available.
Including all states we can see a weak correlation in favor of the vaccinated states. Correl -0.47; R2=0.22; p>0.0649.
However, if we exclude the city states, which likely skew the analysis due to their different characteristics, it allows for a more fair comparison.
Here we can see no significant correlation. Correl=-0.18, R2=0.03; p=0.56
This means we'll have to wait an see how it plays out in the full season, especially since the vaccine efficacy is known to fade fast.
Finally let's look at some models:
Model 1, shows that Germany has peaked, the model still does not pick up the peak...
Model 2, shows that a peak is near.
If we adjust the fit of model 2 to the last 4 days, we can see that Germany likely has peaked.
Now, we still need to see if the curve will actually start declining, or if we'll see other outbreaks, happening, like last year...
Great work by @jens_140081 shows that even with age and population corrected baseline, Germany is looking at +18% excess mortality for week 46/2021. In contrast covid only makes up for about 1/3 of that.
My twitter buddy @jens_140081 just told me that the age and population adjusted excess mortality for week 46 was:
- All-cause excess: +2,673
- Covid19: 1,129
Hence, even after adjusting for population and age changes, Covid19 mortality makes up only 42% of excess --> 58% other!!!
One thing to note here, is that we are comparing "deaths by reported date" in contrast to "date of death"..
However if we compare the actual values for the latest week available, we can see that also only 36.5% of excess deaths are from covid!
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Evaluating the safety and effectiveness of vaccines requires careful scrutiny of clinical trial methodologies. Here are five essential steps to identify potential flaws or fraud in vaccine studies.
1. Double-Blinded, Placebo-Controlled Randomized Trials
These trials are the gold standard for eliminating bias and ensuring reliable results. Participants and researchers don’t know who receives the vaccine or placebo, reducing the influence of expectations on outcomes.
💥💥💥 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...
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. [..]
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.
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:
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.
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?