So far there was no mechanism of action offered for how vaccines could cause so many deaths of different types. We'll address it if one is offered.”
The mechanism of action to cause a multitude of deaths from varying mechanisms and various temporal distances from the shots is protein production within the cells:
Comment 1:
Proteins made by the cells of the human body provide for every process such as proper processing of glucose, the electrical signals within the heart, or even transport of oxygen to the cells. Fetuses create organs and limbs based on the correct protein being present at the proper point during gestation. The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) protein misfunction causes thick, sticky mucus to be produced in every organ of the body that makes mucus causing blockages and trapping germs, leading to infections. Some people with Marfan syndrome make too little fibrillin-1 protein.
Protein mis-folding is believed to be the primary cause of Alzheimer's disease, Parkinson's disease, Huntington's disease, Creutzfeldt-Jakob disease, cystic fibrosis, Gaucher's disease and many other degenerative and neurodegenerative disorders. Amyloidosis is a rare disease that occurs when a protein called amyloid builds up in organs. This amyloid buildup can make the organs not work properly. Organs that may be affected include the heart, kidneys, liver, spleen, nervous system and digestive tract. Protein mis-folding resulting in intracellular pre-amyloid oligomer (PAO) accumulation is sufficient to cause cardiomyocyte death and heart failure.
The harms of altering protein production within cells was well known.
Covid19 shots alter protein production in cells. So, how long will depend on the composition and potency of the exact shot taken, the amount of cells which up-took the mRNA, the exact proteins actually created by the human cells, the quantity of those foreign proteins, and the proteins’ levels of toxicity, and finally the immune response of that specific human body. All of these variables will vary the type of illness and the time distance from the shot in which a catastrophic outcome will occur. And still there may be other variables at work here.
The mechanism of action within the C19 shots IS (& I cannot emphasis this enough IS) the mechanism of harm that will create a variety of illnesses at varying time distance from the shot. This is just one example of how protein production cause healthy functioning of the human body, there are tons of other articles and research papers that support the knowledge that each cell must produce the correct protein at the correct time which folds into the correct shape for the body to function in a healthy, life-sustaining way.
Here is just one article discussing the need for the right proteins in the right cells at the right time:
Causing cells to stop doing the work of health and wellness and begin producing a toxin never leads to health and wellness and makes no sense. Once the world finally grasps that fact, honest assessments and real solutions can be found.
Proteins made by the cells of the human body provide for every process such as proper processing of glucose, the electrical signals within the heart, or even transport of oxygen to the cells. Fetuses create organs and limbs based on the correct protein being present at the proper point during gestation. The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) protein misfunction causes thick, sticky mucus to be produced in every organ of the body that makes mucus causing blockages and trapping germs, leading to infections. Some people with Marfan syndrome make too little fibrillin-1 protein.
Protein mis-folding is believed to be the primary cause of Alzheimer's disease, Parkinson's disease, Huntington's disease, Creutzfeldt-Jakob disease, cystic fibrosis, Gaucher's disease and many other degenerative and neurodegenerative disorders. Amyloidosis is a rare disease that occurs when a protein called amyloid builds up in organs. This amyloid buildup can make the organs not work properly. Organs that may be affected include the heart, kidneys, liver, spleen, nervous system and digestive tract. Protein mis-folding resulting in intracellular pre-amyloid oligomer (PAO) accumulation is sufficient to cause cardiomyocyte death and heart failure.
The harms of altering protein production within cells was well known.
Covid19 shots alter protein production in cells. So, how long will depend on the composition and potency of the exact shot taken, the amount of cells which up-took the mRNA, the exact proteins actually created by the human cells, the quantity of those foreign proteins, and the proteins’ levels of toxicity, and finally the immune response of that specific human body. All of these variables will vary the type of illness and the time distance from the shot in which a catastrophic outcome will occur. And still there may be other variables at work here.
The mechanism of action within the C19 shots IS (& I cannot emphasis this enough IS) the mechanism of harm that will create a variety of illnesses at varying time distance from the shot.
Each cell must produce the correct protein at the correct time which folds into the correct shape for the body to function in a healthy, life-sustaining way.
Here a few articles discussing the need for the right proteins in the right cells at the right time:
And here are articles showing that the wrong protein causes harms:
Protein misfolding is believed to be the primary cause of Alzheimer's disease, Parkinson's disease, Huntington's disease, Creutzfeldt-Jakob disease, cystic fibrosis, Gaucher's disease and many other degenerative and neurodegenerative disorders.
Covid19 shots alter protein production in cells. The harms of altering protein production in cells was known. Causing cells to stop doing the work of health and wellness and begin producing a toxin never leads to health and wellness and never will.
An important point is that the only way to explain that people are still producing spike protein is that the cell nucleus was hacked by the vaccines, proving that they are not vaccines but haccines.
Nobody, not even Wilf, could be in favor of haccines! Even more, if they reached the germline: the problem is passed to future generations and the genepool!
The Swedish study proved that the DNA was hacked in vitro.
Many studies proved the existence of DNA plasmids designed to hack the nucleus, which were not informed by the manufacturers. Even Health Canada and Australian authorities recognized this!
This is a draft of an article I'm writing:
Plasmid-Gate: DNA haccines
Nov 2017. Dr. Tal Zaks, Chief Medical Officer at Moderna, TED talk:
“We are actually hacking the software of life. … In every cell there’s this thing called messenger RNA or mRNA for short, that transmits the critical information from the DNA in our genes to the protein, which is really the stuff we’re all made out of. This is the critical information that determines what the cell will do. So we think about it as an operating system.
So if you could change that, which we call the software of life, if you could introduce a line of code, or change a line of code, it turns out, that has profound implications for everything, from the flu to cancer.
If you think about what it is we’re trying to do. We’ve taken information and our understanding of that information and how that information is transmitted in a cell, and we’ve taken our understanding of medicine and how to make drugs, and we’re fusing the two. We think of it as information therapy.”
” 1
3 Sep 2018. Moderna President Stephen Hoge: “Why are we so passionate about messenger RNA? ... In our language, mRNA is the software of life.” 2
20 Aug 2021. A Swedish study proved that, within 6 hours, “by using an in vitro cell line, we report that the SARS–CoV–2 spike protein significantly inhibits DNA damage repair, which is required for effective V(D)J recombination in adaptive immunity. Mechanistically, we found that the spike protein localizes in the nucleus and inhibits DNA damage repair by impeding key DNA repair protein BRCA1 and 53BP1 recruitment to the damage site. Our findings reveal a potential molecular mechanism by which the spike protein might impede adaptive immunity and underscore the potential side effects of full-length spike-based vaccines.” 3
Eight months after being peer-reviewed, the study was retracted without any scientific explanation, possibly due to enormous pressures, typically bribes and extortion on the authors or journal, on one of the two authors and possibly the journal: “One of the authors has raised concerns regarding the methodology employed in the study, the conclusions drawn and the insufficient consideration of laboratory staff and resources.” 4
Suspiciously, the Expression of Concern was super-fast tracked, published in 6 days since reception, including a weekend5, unlike the study, which took 2 months.6
Oct 2021. Dr. Craig Paardekooper with Team Enigma found in VAERS data:
• 1 in 200 of the batches have been found to be extremely toxic and lethal (0.5%). Each of these batches produced a consistently high number–1000 to 5000 times the base rate of 1–of adverse reaction reports, hospitalizations, and deaths across every US state. A 1 in 200 chance of death or disability.
• 1 in 20 (5%) of the batches accounted for 90% of the adverse reactions and deaths. This means 5% of the batches have caused nearly 100% of the harm from the vaccines recorded. This concurs with V-Safe: 7.8% of vaccinated people had a serious adverse reaction.7
• 70% of the batches have been found to be harmless or relatively harmless–with one or two adverse reaction reports associated.
The higher toxicity of the lethal batches could be explained by one or several possibilities:
a) Higher concentration of the same or different toxic ingredients: the concentration varies not only between vials but inside the vials (not a uniform suspension)8, proving that there’s little or no quality control, by both the manufacturer and governments.9
b) Different toxic substances (as proven by different analysis, for example of toxic metals, graphene),
c) Less degraded or zero10 RNA/DNA (for example, in manufacturing and cold chain). “The greater the stability of the envelope of lipid nanoparticles, the more frequent are vaccine side effects. …
Ribose in RNA contains a hydroxyl group … , which destabilises the phosphodiester bond. This ... can intramolecularly attack the phosphate group … of the nucleotide. This leads to autohydrolysis of the RNA even in the absence of decomposing enzymes. … DNA does not autohydrolyse and DNA fragments can remain stable for hundreds or even thousands of years. …
Moderna's mRNA LNPs are frozen in two buffers, Tris and acetate, while Pfizer/BioNTech's vaccine uses only one phosphate buffer. Phosphate buffers are known to be suboptimal for freezing as they tend to precipitate and cause abrupt pH changes at the onset of ice crystallisation.” 11 For instance, Pfizer had a degradation of 50% of the RNA12 from production to filling of vials:
d) different RNA/DNA coding:
10 Apr 2023. Kevin McKernan US study. “DNA contamination that exceeds the European Medicines Agency (EMA) 330ng/mg requirement and the FDAs 10ng/dose requirements. ...
These vectors contain an SV40 Promoter, SV40 Enhancer, S40 Origin, and an SV40 polyA signal. …
The assembly of Pfizer vial 1 contains a 72bp insertion not present in the assembly of Pfizer vial 2.
Note: an assembly is a computational representation, created by piecing together many short DNA sequences. The process of assembly involves sequencing the fragments and putting the sequences back together.
This indel is known for its enhancement to the SV40 promoter and its nuclear targeting signal.13 ...
Correct and thus the cells within their bodies are not producing health and wellness proteins that each tissue type needs for the body to work properly
For that matter how many cells of which tissue type uptake the mRNA and begin making spike protein? No one knows. Is different within each human body.
Again, my point is that the cells within the human body either make proteins for health and wellness or they don’t and when the cells within the body stop making health and wellness proteins disease and death occur.
The vaccines could not save more lives, simply because "official Covid-19 deaths" are fallacy-data, proven by the fact the average number of conditions being unincreased, while it should reach an average of 10 of CCW ones amongst true Covid-19 deaths: https://zenodo.org/record/8312871
There are two different analyses, the second one is much quicker and a bit simpler (is pasted as Shortened Supplement)
Oct 2023. More DNA plasmids found. “The amount of residual DNA varied substantially between lots. … a high fraction of the DNA is under the size range of the qPCR amplicons”
15
Residual DNA concentration for spike (red) and ori (blue) determined by qPCR and total residual DNA concentration in individual vials as determined by Qubit. In panel A both Pfizer and Moderna data are plotted on the same scale. The Moderna data are enclosed in a red box and displayed separately with an enlarged scale in panel B, to display detail.
Longest Oxford Nanopore (ONT) read aligns to the vector region shown in blue. ori and spike primer locations are annotated on the innermost circle. Open reading frames (ORFs) are annotated in gold and green arrows. Kanamycin resistance genes were detected in a very shallow sequencing survey of the vaccine.
8 May 2024. König and Kirchner German study: “DNA impurities are also encased in lipid nanoparticles and are therefore difficult to quantify. … Pfizer) only measures DNA impurities in the active substance by means of … (qPCR), whose DNA target sequence is less than just 1% of the originally added DNA template. … no direct DNA quantification takes place, and compliance with the limit value for DNA contamination is only estimated from the qPCR data using mathematical extrapolation methods. However, it is also possible to dissolve the lipid nanoparticles with a detergent to directly measure DNA contamination in the final product by using fluorescence spectroscopic methods. 17
1000% variation in toxicity between vaccine batches of the vaccines points to inconsistency, FDA Good Manufacturing Practices violations, and grounds for legal nullification of any authorization by the FDA, even EUA.
The production of mRNA vaccines at scale do not use any animal cells, but is done through in vitro transcription (IVT). The enzyme DNase is then used to destroy the DNA template and polymerase used in the reaction, and further filtration can be performed to reduce the amount of DNA fragments.
Health Canada actually wrote a detailed explanation (archive) of why DNA fragments are expected in mRNA vaccine manufacturing, and why the quantity in the vaccines is not a concern.
“Plasmids are an essential starting material for the production of mRNA vaccines. During the downstream process in mRNA vaccine manufacturing, the plasmid DNA is digested with enzymes to small fragments, and further removed to a level of not more than 10 ng/human dose, which is in line with the World Health Organization’s recommendation concerning residual DNA in biological drugs. The DNA is digested with enzymes post-transcription.”
We would also like to point out that during the manufacturing process, this sequence and other plasmid DNA sequences are broken down and removed. Fragments of the SV40 sequence may only be present as residual impurities at very low levels that are routinely controlled.
“The plasmid DNA is likely inside the LNPs and is protected from nucleases… data demonstrate the presence of billions to hundreds of billions of DNA molecules per dose in these vaccines. Using fluorometry, all vaccines exceed the guidelines for residual DNA set by FDA and WHO of 10 ng/dose by 188 – 509-fold. ” 18
For those following the plasmid DNA contamination issue, Dr Philip Buckhaults, self described 'genome jock' from SC, has begun asking for samples of tissues (tumours etc) from those who believe they are vaccine injured. ( Or in the case of those deceased, from pathologists.) He intends to qPCR sequence these tissues to look for integration of the foreign plasmid DNA, which I firmly believe he is going to find, even on just an odds basis: millions of DNA fragments per injection, into billions of arms, 2 or more times each. This would/ will be seismic. Is the world ready to accept billions of people were injected , many by coercion, with something which has integrated foreign DNA into their genome and is causing disease and injury? 2024 will continue to be a very interesting year.
2023. Dr. Speicher's testing revealed DNA levels between 7 to 145 times higher than the 10ng per dose Australian FDA (Therapeutic Goods Administration TGA) limit.19 TGA rejected this by only looking at naked DNA, not the all the DNA encapsulated in the lipid nano-particles20, only targeting fragments over 200 base pairs (lowest risk)21, failing to detect the bulk of the contamination, by using qPCR which under-measures synthetic DNA22 and not disclosing their test methods.
Still, the 10 ng limit was copied from the FDA, which was not based on science but on a meeting of “experts” based on “opinions”, and was applicable only to residual DNA, not DNA-plasmid bio-weapons:
2024. Dr. Konig also proved DNA plasmid “contamination”.23
Pfizer’s mRNA injections are for gene-editing. “In collaboration with biotech company Beam Therapeutics, Pfizer scientists are developing mRNA technology as a new approach to gene editing … lipid nanoparticles ... have the potential to add, remove, ... faulty genes”. 24
3 Jan 2024. Florida Surgeon Genral warned of cancer and other side effects:
“discovery of billions of DNA fragments per dose of the Pfizer and Moderna COVID-19 mRNA vaccines … concerns regarding nucleic acid contaminants in the approved Pfizer and Moderna COVID-19 mRNA vaccines, particularly in the presence of lipid nanoparticle complexes, and Simian Virus 40 (SV40) promoter/enhancer DNA. Lipid nanoparticles are an efficient vehicle for delivery of the mRNA in the COVID-19 vaccines into human cells and may therefore be an equally efficient vehicle for delivering contaminant DNA into human cells. The presence of SV40 promoter/enhancer DNA may also pose a unique and heightened risk of DNA integration into human cells.” 25
12 Sep 2024. “Florida Surgeon General Calls for Halt of Covid-19 Vaccine for Safety Reasons”:
“Potential DNA integration26 from the mRNA COVID-19 vaccines pose unique and elevated risk to human health and to the integrity of the human genome, including the risk that DNA integrated into sperm or egg gametes could be passed onto offspring of mRNA COVID-19 vaccine recipients.” 27
3 Jan 2024. Florida Surgeon General: Pfizer’s and the FDA’s lack of proper animal and human testing (bona fide research) is beyond reckless as the mRNA nanoparticle technologies have the capability of introducing oncogenes (genes that cause cancer) as well as making transgenerational changes to the human species. 28
8 May 2024. First published peer reviewed study found synthetic DNA wrapped in LNPs:
“very high DNA values were measurable in all batches after Triton-X-100 treatment, with these values ranging from 360 to 534 times the permissible DNA limit or 3600 to 5340 ng DNA per dose.
“… to dissolve the lipid nanoparticles with a detergent to directly measure DNA contamination in the final product by using fluorescence spectroscopic methods” 29 a $10 test would have been enough to detect the DNA presence!
wonder if they could be sent a sample of GMO jab SpikoGen to detect foreign genetic material?
QuBit Fluorescence was used by my friend Kevin McKernan to detect Endotoxin in Pfizer jab.
Deliberately, COVID Pifzer and Moderna vaccines had and still have SV40 DNA organized fragments (plasmids). Was it really added as a promoter in the DNA plasmid to drag DNA into the nucleus? No rational argument is provided to justify the use of that dangerous viral sequence and to hide it to the health authorities.
Another position states that it was deliberately added to induce cancer. It’s no coincidence that both Pfizer and Moderna also added undisclosed DNA plasmids to hack the cell nucleus and that turbo-cancers appeared after COVID shots.
it appears that DNA from the pfizer vaccine may be replicating in mammalian cells and that even small amounts of shedded plasmids can expand to become large amounts.
Kevin McKernan, who has just reported new research, explains at the link below. Here's an excerpt:
"Pfizer vaccine sequence can be detected 1 year after vaccination in a spike positive IHC colon cancer biopsy ... we are finding tissues that have similar CTs to the naked vaccine a year later. That can only happen if the vaccine DNA is integrating and amplifying or if the DNA is being replicated by these origins of replication as episomal plasmids ... If the DNA is replicating in mammalian cells, then we don’t need self amplifying mRNA vaccines as the population was already given them with Pfizer vaccines ... small amounts of shedded plasmids could expand in the [shedding] recipients ..."
SV40 origin of replication in mammalian cells in absence of SV40 Large T-Antigen
Positive tumor biopsy qPCR one year after vaccination
Outstanding comment. A kind of anecdotal supplement to that...We know that the body is effected in some way from literally every single thing we do to it, or put in it. Time is the other component. Over time we can do small things, which always affect outcomes. We run every day, we get slimmed and gain endurance, we drink soda every day, we get a belly, we lift small weights every day we get toned. We lift heavy weights we get muscle we smoke, we wear out our lungs, we drink, our liver changes....small things creeping over time, produce a result. Now we are instructing our cells to alter their shape and function, daily for an extended time ( months if not years, if not permanently). I wonder if Mr Wilf can explain the mechanism that causes this product to be the first and only thing that exists in the world which doesn't create change over time. ...and just like with the masks, no study or person ever calculated at what point during use that they transition from help to harm...can Mr. Wilf identify the circumstance and point in time in which the mechanisms of this product, while continuing to alter cells, stops effecting bodily change over time, and how is it doing it?
What caught my eye from a very preliminary, fast, initial skim was the assertion that each Covid death represented 10 YALL (i.e., 10 years of actual life lost). That relies on Covid being indiscriminate in the underlying state of health of those dying with it – not unreasonable an assumption in say January 2020.
However, by mid-2020 we already had data that showed YALL was 12-16 MONTHS (or 1.00 to 1.25 Years – not 10 Years) in England & Wales. Italy was similar. Based on the profile of deaths by underlying prior state of health, I would expect similar YALL in most other countries.
Given treatment mis-steps early on, and dubious measures implemented that adversely affected (in particular) the elderly, a more appropriate YALL would be lower still.
That means:
1. ED, excess deaths (assuming that the “excess” is in excess of genuine expected) actually receive very little contribution at all from “Covid”
2. Vaccination against Covid – even should it significantly reduce the risk of catching or dying from Covid – saves at most a few months of life and only for the most vulnerable. So, little benefit as all.
3. ED in 2020 were caused by other factors than Covid.
4. Expected deaths in 2021 (before calculating any excess) and onwards also need to allow for the consequences of measures taken in 2020 (and - if persisting beyond 2020 - later).
In England & Wales, ED in 2020 was circa 8% of total deaths. The majority of that is attributable to measures taken e.g., mortality will be higher if dread diseases diagnosed later than would otherwise be the case, treatment commencing at later stage than would otherwise be the case, and treatment being deferred for new and existing cases.
It would be nice to have a clean copy of Wilf's remarks the same way I read yours - can't tell what's really his anymore b/c of the invite to make comments of Wilf's - some people clearly don't know how to do that only on the side and it's in the body. Steve, would you post his non-marked up version? Thanks.
Paul Cullen uses simple math to show that the gene therapies could at most have saved 200k lives globally. Far less than they shortened and took:
Inzwischen ist klar, dass die Wirksamkeit der Impfpräparate im Laufe der Zeit stark nachließ. Wir wollen aber diese Tatsache außer Acht lassen und die Daten aus der Pfizer-Zulassungsstudie übernehmen (auch wenn immer mehr Mängel dieser Studie bekannt werden), wonach 100 Menschen behandelt werden mussten, um einen Covid-Fall zu verhindern. Als nächstes machen wir die pessimistische Annahme, dass wie in Heinsberg vier von 1.000 SARS-CoV-2-Infizierten an Covid sterben. Wie viele Menschen muss man dann impfen, um einen Todesfall zu verhindern? Die Antwort lautet: 1.000/4 = 250 x 100 = 25.000 Menschen. Weltweit sind ca. 5 Milliarden Menschen gegen Covid geimpft worden. Somit hätten maximal weltweit etwa 200.000 Menschenleben durch die Impfung gerettet werden können, fernab der Zahl von 20 Millionen, die immer wieder in den Medien kolportiert wird.
You wrote: "And then there is miscategorization bias. Engler (2024) points out that every single study with the words (covid, vaccine, efficacy, safety) that Neil and Fenton (2024) could locate had one or more types of miscategorization errors."
Neil and Fenton's cheap trick paper was recently demolished by Peter Hegarty, who is a professor of mathematics at the University of Gothenburg: https://x.com/PeterHegarty17/status/1869784526395978142. He found that only about a quarter of the 39 papers listed by Neil and Fenton actually employed the classification delay which Neil and Fenton have dubbed the cheap trick, and none of them only applied the form of the cheap trick postulated by Neil and Fenton where the classification delay was only applied to the numerator but not to the denominator.
The abstract of Neil and Fenton's paper said: "Simulation demonstrates that this miscategorisation bias artificially boosts vaccine efficacy and infection rates even when a vaccine has zero or negative efficacy." But in their simulation the 1-to-3-week classification delay was only applied to the numerator for cases but not to the denominator for the population size. When I modified their simulation so that I also applied the classification delay to the numerator, unvaccinated and vaccinated people had an identical rate of cases: https://sars2.net/uk.html#Martin_Neil_and_Norman_Fenton_March_2024_preprint_about_the_cheap_trick. Neil, Fenton, Crawford, and Lyons-Weiler have all failed to cite a single study where the classification delay was only applied to the numerator but not to the denominator. It wouldn't make any sense because it would introduce such an obvious bias, so it should at least be documented in the methods section of the study.
However the response said: "In your paper you also state that the number of deaths reported within the first 21 days of receiving the first dose of the Covid-19 vaccination is below that which could be expected in the general population, and that this difference is evidence of systematic undercounting of deaths by ONS. Our view of this question starts with the consideration that the population included is not representative of the general population, and it is therefore likely that any pattern you observe is attributable to the 'healthy vaccinee' effect. This happens when people who are ill (either due to COVID-19 or another relevant illness) are likely to delay vaccination. The result of this effect is a lower-than-average mortality rate within the first 21 days of receiving a vaccination. This effect is described by ONS in their Deaths by Vaccination Status publication."
The response said that the misclasfification hypothesis by Fenton et al. was likely wrong because the low number of deaths in the first few weeks after vaccination was explained by the HVE instead (as your record-level datasets have also shown is the case in other countries).
The response was an answer to a question by Craig, Neil, Fenton, and McLachlan relating to a preprint they published in March 2022 titled "Official mortality data for England reveal systematic undercounting of deaths occurring within first two weeks of Covid-19 vaccination": https://www.researchgate.net/publication/358979921. In the preprint Craig et al. speculated that because the ONS dataset for deaths by vaccination status had a low number of non-COVID deaths in the first two weeks after vaccination, deaths that occurred soon after vaccination were somehow systematically omitted or misclassified, but they discounted HVE as an explanation for the low number of deaths.
Craig et al. wrote: "The healthy vaccinee hypothesis, that those close to death will postpone or decline vaccination might hypothetically account for a lower rate of death in the first two weeks. But as an explanation it is only plausible if every possible death that might occur in the first two weeks, after the offer of vaccination, was foreknown whilst those deaths in the third week were not, and hence those dying in the third week did not postpone or decline vaccination."
However Craig et al. didn't take into account that the temporal healthy vaccinee effect actually lasts longer than 2 weeks, but if you plot deaths by weeks since the first dose in England, the increasing trend in mortality caused by the waning out of the temporal HVE is counteracted by the decreasing trend in the background mortality rate, because many first doses in England were given during the first three months of 2021 when the mortality rate was falling rapidly because the COVID wave in the winter of 2020-2021 was passing by. A similar effect can also be seen in the Czech record-level data and in your Connecticut Medicare data: https://sars2.net/connecticut.html#Deaths_by_weeks_since_vaccination. And I believe it explains why the temporal HVE only appears to last for about 3 weeks in your old Medicare data.
I guess Clare Craig may have later come to the conclusion that the low number of deaths during the first two weeks might be explained by the HVE, because in 2024 when someone asked her what she meant by the healthy vaccinee effect, she answered that "Studies show that the first few weeks after vaccination are outliers because people who are feeling ill postpone." (https://x.com/ClareCraigPath/status/1844085783365550508)
In 2022 Martin Neil tweeted: "The ONS's December report claims anomalies we identified are caused by healthy vaccinee effect. We examined the new ONS data and found NO evidence to support this claim". (https://x.com/MartinNeil9/status/1481561698792267779) And in March 2024 Neil tweeted: "There is no evidence of a healthy vaccinee effect. You are signing up to an assumption usually exploited to pretend vaccines are effective. We demonstrated this using the ONS's own data." (https://x.com/MartinNeil9/status/1767991047940907318) However by April 2024 he seems to have changed his opinion about HVE based on the Czech study which said that HVE explained why unvaccinated people had elevated mortality: https://x.com/MartinNeil9/status/1780163490247791002.
So the old letter by Craig and Neil et al. might no longer represent their current views regarding the HVE.
The article was about excess deaths in 2022 and not 2023, and it said that Australia had about 20,000 excess deaths in 2022. At first I thought they might have exaggerated excess deaths if they used a prepandemic average baseline like the Australian Bureau of Statistics, but at Mortality Watch a 2010-2019 linear baseline also gave me 19,135 excess deaths in 2022: https://www.mortality.watch/explorer/?c=AUS&t=deaths&e=1&bf=2010&p=0. However as a percentage it was only about 11% excess deaths, and as a whole Australia has had low excess mortality since 2020 compared to countries that were not able to keep the virus out with lockdowns until the population was vaccinated.
And if the excess deaths were caused by the vaccines, then why wasn't there already high excess mortality in 2021?
Most regions of Australia had negative seasonality-adjusted mortality around the time in 2021 when people got the primary course doses. But then most regions had a sudden spike up in excess deaths around January 2022 which coincided with a similarly sharp spike in PCR positivity rate, except in Western Australia where the PCR positivity remained close to 0% in January 2022, there was also no clear increase in excess deaths in January 2022: sars2.net/i/nopandemic-australia-smaller.png.
You also wrote: "An excess deaths inquiry was held to investigate Australia's excess of nearly 30,000 deaths throughout 2021-2023." However if you use a 2010-2019 linear baseline at Mortality Watch, the number of excess deaths in Australia is 2,223 in 2021, 19,135 in 2022, and 7,846 in 2023, so almost none of the excess deaths were in 2021. And the total excess mortality in 2021-2023 is only about 5.7%.
---
You wrote: "Ed Dowd's book 'Cause Unknown' documents 500 people who died unexpectedly (that was the sole criteria). They have something in common: as far as we know, only one of the 500 was unvaccinated."
Dowd's book has a couple of alternate cover images. One version features Alex Apolinario, Josh Downie, Emmanuel Antwi, who all were not eligible for vaccination at the time of their death, and it features Logan Luker who died by suicide: https://x.com/WaitingForPerot/status/1739655583450517957.
Anothre version of the cover image features Brandon Fahey who was not vaccinated and who died from a malformed blood vessel in his brain, and it featured Aaron Vasquez who died from a congenital heart defect: https://x.com/Truth_in_Number/status/1743327152685085159. An article about Vasquez said that one of his coronary arteries "was in a place that, left surgically uncorrected, could result in death", and that he "was neither under the effects of the coronavirus nor of any vaccine against the coronavirus" (even though I don't know if it means he was unvaccinated) (https://parentheartwatch.org/dumont-student-athlete-who-suddenly-died-14-had-undetected-heart-condition-dad-says/).
You posted a plot from Mortality Watch and wrote: "This is a stunning chart because after such a huge mortality increase in 2020, we've 'pulled forward' the deaths of the weakest so excess death rates should turn into deficit death rates and the cumulative excess mortality bars should have gone down in 2021, down further in 2022, etc."
You compared total ASMR in 2021 against total ASMR in 2020, but 2020 also includes the months before COVID which reduces the total ASMR for 2020. And a lot of the excess deaths in 2021 were in January when there weren't yet that many people vaccinated.
But anyway I think Ethical Skeptic exaggerates the magnitude of the PFE: sars2.net/ethical2.html#Should_the_PFE_adjustment_last_for_only_6_6_years. He applies the PFE adjustment to the baseline for only 6.6 years, because he calculated that at some point the average age of people who died from COVID in Florida was 82 years, and he got a life expectancy of 6.6 years for age 82 for males from a calculator at seniorliving.com. However the life expectancy for females of age 82 was about 8.2 years on the same website, so I don't know why he didn't even take the average life expectancy for both males and females. And in the 2019 US life table the life expectancy at age 82 was about 8.2 years for both sexes combined. And at CDC WONDER the average age of UCD COVID deaths was about 73.8 in Florida and about 73.9 in the whole US, so both are about 8 years lower than Ethical Skeptic's figure of 82 years.
When I took the life expectancies for each age from the 2019 US life table and I calculated their average weighted by the number of UCD COVID deaths for each age at CDC WONDER, the resulting life expectancy was about 14.5 years. And if we assume that 14.5 years was the average life expectancy of people who died from COVID, then even 14.5 years later there would still be many people who would be alive if they hadn't died of COVID. So the duration of the PFE adjustment should probably be much longer than 6.6 years, which would also cause the average magnitude of the PFE adjustment to be much lower because the adjustment would be spread out over a longer period.
I did a simulation with two scenarios, where in both scenarios the population size for each age started out as one tenth of the mid-2018 US resident population estimates. I otherwise used a 2011-2019 linear trend in CMR for each age in both scenarios, except in the other scenario I multiplied the mortality rates in 2020-2021 to match the actual pattern of excess deaths in the United States. But in the scenario with elevated mortality in 2020-2021 I got only about 1.5% less deaths in 2022-2024. (All of this is described under my previous link.)
If you calculate ASMR then it already accounts for the reduction in population size after excess deaths in a straightforward and objective way. But Ethical Skeptic thinks ASMR is some kind of black magic and he usually plots raw deaths without even adjusting for population size, and he seems to have made up the shape of his PFE adjustment curve based on some arbitrary subjective criteria. I have been telling him to use a method where he would calculate the prepandemic trend in CMR for each age and then multiply the population size of each age by the projection of the trend, but so far I haven't seen him use that method either. That method would also account for the reduction in population size in a straightforward and objective way like ASMR, but neither method produces nearly as heavy reduction in the expected deaths as his PFE adjustment.
You wrote: "Right after corporate America started requiring COVID vaccinations, the CEO of the OneAmerica insurance company publicly disclosed that during the third and fourth quarters of 2021, death in people of working age (18–64) was 40 percent higher than it was before the pandemic. Significantly, the majority of the deaths were not attributed to COVID."
In July to December of 2021, ages 18-64 had 87677 deaths with UCD COVID and 97630 deaths with MCD COVID. So deaths with UCD COVID account for about 61% of the difference between 2021 and 2019 (from 87677/(495284-351102)). The number of deaths with UCD related to recreational drug use also increased from 34240 in the second half of 2019 to 49196 in the second half of 2021, so it's about 10% of the increase in total deaths between 2019 and 2021: `v=fread("curl -Ls sars2.net/f/vital.csv.xz|xz -dc");v[month>=7&age%in%18:64][cause%like%"X4[0-4]|X6[0-4]|Y1[0-4]",.(ucd=sum(ucd),mcd=sum(mcd)),year]`. If I would've looked at MCD instead of UCD, the percentages would've increased to about 68% for COVID deaths and 11% for drug deaths.
---
On CDC WONDER if you calculate a ratio of deaths with UCD COVID in 2021 divided by 2020, it's about 1.97 in ages 18-64 but about 1.00 in ages 65 and above: `v[cause=="U071"&age%in%18:64,sum(ucd),year][,V1[2]/V1[1]]`. So why did working-age people have such a high percentage of COVID deaths in 2021 relative to 2020? I think it's because in 2021 working-age people were less likely to be vaccinated than elderly people.
In the winter of 2020-2021 the Czech Republic had a pattern of mortality with three distinct humps, where in ages 80+ the first hump was the highest and the third hump was the lowest, but ages 40-59 followed an opposite pattern. I think it's because by the time of the third hump, the percentage of vaccinated people was over 50% in ages 80+ but less than 10% in ages 40-59: sars2.net/czech.html#Daily_deaths_and_vaccine_doses_by_age_group.
Compared to elderly people, working-age people in the Czech Republic also had a high age-standardized rate of COVID hospitalization in 2021 relative to 2020, but it's explained by a lower percentage of vaccinated people among working-age people: sars2.net/czech3.html#Hospitalizations_by_age_group_and_vaccination_status.
---
Another problem with blaming vaccines for the excess deaths in working-age people in the second half of 2021 is that there were low excess deaths in northeastern states which had a high percentage of vaccinated people, but there were high excess deaths in southern states which had a low percentage of vaccinated people: sars2.net/statistic.html#Fabian_Spieker_US_summer_of_deaths_in_2021. A large part of the deaths also occurred during the Delta wave in August to September 2021, even though there weren't that many new people getting vaccinated at the time. And in some northeastern states like Connecticut where the PCR positivity rate remained low in August to September of 2021, there were also low excess deaths. If the wave of excess deaths was due to vaccines then why did occur in some states but not others even though all states got vaccinated?
Among the vaccinated people who are included in your "Medicare all states subset" spreadsheet, there was also very little increase in deaths in August to September of 2021 relative to the general population of the US which also includes unvaccinated people, so the bump in deaths during the Delta wave is almost flat (ibid.). Your old Medicare spreadsheet also shows that among people in southeastern states who got vaccinated in the second half of 2021, the number of deaths was not clearly elevated during the first few months from vaccination (ibid.).
---
The number of additional working-age people who got vaccinated in the third quarter of 2021 after the mandates is also fairly low compared to the number of people who got vaccinated in the first half of 2021: sars2.net/statistic.html#Pierre_Kory_Excess_deaths_in_young_age_groups_in_the_fall_of_2021. So if the mandates caused a massive wave of deaths then why weren't people also dropping like flies around March to May 2021 when a larger number of people got vaccinated?
You wrote: "Hulscher (2024) looks at highly vaccinated King County. 'We found a 25.7% increase in total cardiopulmonary arrests and a 25.4% increase in cardiopulmonary arrest mortality from 2020 to 2023. Applying our model from these data to the entire United States yielded 49,240 excess fatal cardiopulmonary arrests from 2021-2023' (due to the COVID vaccine)."
However Hulscher et al. simply included all cardiac arrest deaths and they didn't exclude deaths due to COVID. Washington State had a low number of COVID deaths in 2020. Based on CDC WONDER's data for King County, deaths with MCD COVID explain a large part of excess MCD cardiac deaths since 2020, and there's a low number of excess UCD cardiac deaths since 2020: sars2.net/statistic2.html#McCullough_Foundation_Paper_about_cardiac_arrests_in_King_County_EMS_data.
Hulscher's figure for 2023 was not even real data but a linear projection of the figures for 2021 and 2022. The real figure for 2023 ended up being only slightly lower than their projection, but I think the authors should've just excluded 2023 from their paper instead of making up projected data for 2023.
The authors only showed data going back to 2015 even though the source where they took the deaths extended back to 2003. The authors might have omitted earlier years because there was a big drop in the number of deaths between 2014 and 2015.
The 2015-2019 linear baseline they used might have been too low especially by 2023, because the long-term trend in deaths going back to 2003 seemed to be curved upwards. But you couldn't tell it from their paper which only included data going back to 2015. At CDC WONDER the long-term trend in all-cause deaths in King County is similarly curved upwards.
McCullough's Substack article about the paper was titled "Peer-Reviewed Study Reveals 1,236% Surge in Excess Cardiac Arrest Deaths Among 2 Million COVID-19 Vaccinated Individuals". But the paper didn't include information about the vaccination status of the people who died, and it might be that unvaccinated people were overrepresented among the people who died in excess since many of the excess deaths seem to have been due to COVID.
And the 1236% increase was actually an increase from about 1.0% excess deaths in 2020 to about 11.6% excess deaths in 2023, so it was only an increase of about 10.6 percentage points. McCullough's people seem to have intentionally chosen a misleading headline, because they probably knew their followers would misinterpret the headline figure of a 1236% increase.
Hulscher et al. wrote: "Specifically, the number of cardiopulmonary arrest deaths increased from 891 in 2015 to 1,110 in 2020, representing a 24.6% increase. In 2021, deaths jumped to 1,229 and continued to rise to 1,310 in 2022. The projection for 2023 suggests 1,392 cardiopulmonary arrest deaths in King County, WA, indicating a sharp 25.4% increase since the onset of COVID-19 vaccination campaigns"
However in Hulscher's Table 1 the number of deaths in 2020 was 1121 and not 1110. But 1110 was his baseline value for 2020, so he seems to have accidentally calculated the increase between 2020 and 2023 using the baseline value instead of the number of deaths for 2020.
Hulscher even calculated the number of deaths wrong because he multiplied the number of patients with the rounded percentage of patients who didn't survive, even though he could've derived the exact number of deaths by subtracting the number of patients who didn't survive instead. The real number of deaths in 2020 was 1116.
But anyway, Hulscher's number of deaths actually increased from 1121 in 2020 to 1392 in 2023, so it was an increase of about about 24.2% and not 24.6%. But his baseline also increased by about 12% from 1110 in 2020 to 1245 in 2023. So the excess deaths only increased by about 10.8 percentage points: (1392/1245)-(1121/1110).
However his figure for 2023 wasn't even the real number of deaths but a linear projection of the deaths in 2021 and 2022. The real number of deaths in 2023 was published in September 2024 and it was 1358, so the excess deaths between 2020 and 2023 increased by only about 8.1 percentage points relative to Hulscher's baseline: (1358/1245)-(1121/1110).
But his linear baseline might have also been too low in 2023 because the long-term trend in deaths seemed to be curved upwards. And he also didn't exclude COVID deaths and there were still some COVID deaths in 2023.
You wrote: "Denis Rancourt 125 countries study paper (521 pages) found an overall average vDFR=.00127 which is 1 death per 787 doses which is consistent with other estimates presented here." In the 125-country paper and the earlier southern-hemisphere paper, Rancourt ignored how excess deaths had a much higher temporal correlation with COVID deaths than with the daily number of vaccine doses administered. When Rancourt calculated the figure of 17 million vaccine deaths, he assumed that all excess deaths since vaccine rollout were due to vaccines.
> In the high-quality databases for the USA, there is a close match between the weekly reported COVID-19 mortality and weekly excess all-cause mortality, in the Covid period (2020-2022), including prior to and during the vaccine rollouts (CDC, 2023).
> To the degree that COVID-19 death assignation represents a serious respiratory condition at death, and given the intricate weekly temporal matching of the reported COVID-19 mortality and excess all-cause mortality for up to 3 years in the USA data, this represents strong evidence that respiratory infections were dominantly (virtually entirely) associated with the excess all-cause mortality.
In the 125-country paper Rancourt wrote that the Czech Republic had a spike in deaths which coincided with the booster rollout. However I told him that if you look at age-stratified data, deaths peaked around the same time in all age groups even though new vaccine doses administered peaked about a month before deaths in ages 80+ and about a month after deaths in ages 40-59: https://x.com/henjin256/status/1819537703068738006. Age-stratified data presents a fatal weakness to his approach of temporally correlating spikes in deaths with a vaccine rollout.
In Rancourt's new paper I believe he referred to the Czech data in the following paragraphs, where he now seems to have admitted that the excess deaths that coincided with the booster rollout could not be attributed to people who had recently received the booster:
> Recently, Rancourt et al. (in preparation) analysed national mortality data in one country in which COVID-19 vaccination status was known at death, including the history of COVID-19 vaccinations, in a case in which the country exhibited rapid vaccine rollouts strongly temporally associated with observed surges in excess all-cause mortality. They found that relevant **peaks in excess all-cause mortality associated with booster rollouts could not preferentially be assigned to booster-vaccinated individuals** (and also that the vaccine had no detectable survival benefit).
> This means that the COVID-19 vaccination primary cause described in Section 3.3.5 did not produce a measurable increase in excess all-cause mortality in this country, which in turn means that sharp peaks in excess all-cause mortality which are temporally associated with rapid vaccine rollouts need not imply that COVID-19 vaccination is a primary cause of death. Rather, it seems that (as pervasive as they are) such temporal associations between mortality peaks and rapid vaccine rollouts are due to the primary cause described in Section 3.3.6 of campaigns and measures associated in time and place with COVID-19 vaccine rollouts. Although non-conclusive in general, this is consistent with the fact that the vaccine toxicity causing death inferred from populationwide adverse-effect monitoring is usually too small to be detected directly in populationwide (e.g., national) cause-independent all-cause mortality, as per analyses of USA VAERS (Vaccine Adverse Events Reporting System) data (Hickey and Rancourt, 2022).
> This would mean that the lethality of medical measures imposed during the Covid period and during vaccine rollouts is much greater than generally acknowledged, and much greater than the known (VAERS, autopsies, etc.) vaccine toxicity itself.
Rancourt now has to perform circus-level acrobatics to reconcile his earlier claim of 17 million vaccine deaths with his new claim that there were not necessarily that many deaths associated directly with vaccination, so he now suggests that the deaths were rather caused indirectly by measures associated with vaccination or by stress induced by vaccination: https://x.com/henjin256/status/1865524490194637008. As examples he gave "aggressive or extreme immobilization and isolation enforcement during the vaccine rollout" and "disrupted patient care schedule, including regular medication, meals and hydration".
However his new theory doesn't seem to explain why the excess deaths were concentrated in waves which were much higher in unvaccinated than vaccinated people even after adjusting for HVE. Why did stress induced by vaccination kill unvaccinated people?
You wrote: "The official UK ASMR 21 days from dose 1 vs. Dose 2. Shows it is dose dependent. A 'safe' vaccine cannot have a dose dependent ASMR." And you linked to this tweet: https://x.com/stkirsch/status/1858664074621710521.
However the tweet didn't show what part of the ASMR was accounted for by COVID deaths. In January 2021 COVID ASMR was about 56% of all-cause ASMR in the category "First dose, less than 21 days ago", but there was very low COVID ASMR in the category "Second dose, less than 21 days ago": sars2.net/uk.html#Clare_Craig_ASMR_within_3_weeks_from_vaccination_for_first_and_second_doses. So it might be that the vaccine was not yet fully effective during the first couple of weeks from vaccination, or that two doses offered better protection than one dose.
People who have passed the "healthy vaccinee" test twice might also have lower mortality risk on average than people who have passed it once.
The reason why canceledmouse was not able to reproduce my ASMR calculation was because he had 4 bugs in his Perl code. When he calculated an 11-day moving average of deaths, he added together the deaths on 11 days but he forgot to divide them by 11. And the percentage of each age group in the standard population should've been divided by 100 to get the fraction of the age group. And the deaths per person-days should've been multiplied by 365 to get deaths per person-years. And he divided the ASMR value by the percentage of total population made up by the age group which is not part of the formula for calculating ASMR.
He fixed the bugs after I pointed them out to him, and after that his code produced mostly similar results to my code: sars2.net/czech3.html#Reply_to_Substack_article_by_canceledmouse. The remaining differences to my code were for two reasons. First he used the WHO standard population which has a low percentage of people in elderly age groups so it's a very poor match to the Czech population structure. And second he applied an 11-day backwards moving average to deaths but not population size, so his deaths were lagging 5 days behind the population size which underestimated the ASMR of vaccinated people in early 2021 when the vaccinated population size was increasing rapidly.
canceledmouse claimed that my bucket analysis was done poorly, but the only reason he gave was that I assigned a random birthday to each person so he claimed my analysis was not reproducible. However he didn't notice that I assigned a seed in my code before I generated the random birthdays. He corrected his error after I notified him of it.
canceledmouse also claimed that I shouldn't have used the term ASMR because I used the Czech 2021 census population as my standard population, but it's not a standardized standard population like the WHO standard population. However I showed why he was wrong in the section of my website I linked above.
canceledmouse pointed out that when he ran my code for generating the plot for ASMR by vaccine type, he got extra gray line with the label NA. However that was a line for Novavax that I forgot to remove from the code on my website.
"1. The mRNA, which stands for modified mRNA, contains a synthetic nucleotide called N1-methylpseudouridine, which replaces all of the Uridines that would naturally occur in mRNA. This synthetic molecule results in an mRNA molecule that is long-lasting and does not readily breakdown in the same way that natural mRNA does. "
Is this what JJ Couey is talking about when he says the RNA cannot pandemic? That a natural RNA will readily breakdown before it can spread worldwide as essentially the same molecule detectable whether in Manaus or Madrid or Macau?
I really appreciate you locking onto this very important issue, like a Pitt Bull on a rope. You continue to inspire and motivate me… I just wanted to say thank you.
Thank you Mr. Kirsch for keeping this in the public eye.
Wilf, just another big pharma shill. Everyone with a working brain has known for years that the shot/hospital protocols killed and maimed millions in America alone. Most of us have many friends and family that have suffered or died. We also are aware of the malfeasance that was perpetrated on the people of the world. The patents tell the tale.
The Hungarian pop studies used the CDC definition of vaccination status (you're "unvaccinated" until 14 days after second shot), so the actual mortality outcomes are inverted. There is no benefit, only harm.
1. His table under methodology cherry-picks your weakest arguments.
2. Also under methodology, the "if net detriment" bullet point ignores the power of mass formation and humans going along to get along and therefore carefully staying within the Overton window.
3. Regarding the paper about the Hungarian population, I added this comment to the document:
"The increasing deaths with time for most vaccines, especially Moderna and Pfizer and especially in the first (epidemic) period, suggest a huge healthy vaccinee effect with death rates of Moderna recipients increasing by a factor of 4, mostly during the first (epidemic) period. Perhaps Moderna was taken primarily by the oldest where this effect would be most prominent. Perhaps instead it indicates vaccine related deaths.
I propose that 100% of the "benefit" this study showed and probably quite a bit more than that was due to not accounting for the fact that the healthy vaccinee effect has impact on death rates over only about the first 3 months with the majority of that over the first month. Those over about age 65-75 will also represent the vast majority of the healthy vaccinee effect as most non-accidental deaths occur in that age group.
Most over age 65 got vaccinated early (February and March). The healthy vaccinee effect was prominent during the epidemic period (April-June 20), but had faded by the nonepidemic period (June 21-August 15). This is supported by the increasing death rate with time among the vaccinated as the healthy vaccinee effect wears off and decreasing death rates among the unvaccinated as deaths of those who remained unvaccinated due to being on deaths doorstep have mostly occurred in the first 90 days. The steadily increasing slope among the vaccinated and the steadily decreasing slope among the unvaccinated is a very good match of the idealized death curve that results from the healthy vaccinee effect.
I further propose that there are lots of vaccinated bodies buried in the partially vaccinated period, especially among those who remained partially vaccinated due to sustaining an injury with the first dose. The authors revealed exactly zero information about what happened during to the partially vaccinated cohort."
FYI, being a statistician, what are the chances that Dr. Luc Montenier , Dr. Rashid Buttar and Dr. Zelenko all passed away in a three year period after having said that the Covid Vacc was a biological bomb, a work of the Grim Reaper. They gave a predictions that within a Four year period that the ravages of a planned population reduction program would come to fruition…. Well…..are we close… are we in it, what are the stats to prove-or disprove, oppppp you have already documented your findings, gruesome!
When working as an expert engineering witness I made sure my points were clear to non-technical readers. You have to present your material convincingly and clear so any reasonably educated person can understand. I remember this one case for a plaintiff customer whos lawyer I worked with who proudly showed me his indexed binder with his argument. The judge didn't care about his meticulous and expensive (at my customer's cost) binder. He never looked at it. He homed in immediately at the essence of the defendant's argument that the defendant did not sign for the extra work and therefore the plaintiff would not be getting paid for the unauthorized work. I had pointed this out to my customer in the beginning but he ignored my point.
I mention this as you dazzle with all the studies you quote however that requires reading the studies to find their supportive points and their flaws. Judges prefer concisely homing in on the important points you are trying to make.
Under Wilf: “No Mechanism of Action
So far there was no mechanism of action offered for how vaccines could cause so many deaths of different types. We'll address it if one is offered.”
The mechanism of action to cause a multitude of deaths from varying mechanisms and various temporal distances from the shots is protein production within the cells:
Comment 1:
Proteins made by the cells of the human body provide for every process such as proper processing of glucose, the electrical signals within the heart, or even transport of oxygen to the cells. Fetuses create organs and limbs based on the correct protein being present at the proper point during gestation. The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) protein misfunction causes thick, sticky mucus to be produced in every organ of the body that makes mucus causing blockages and trapping germs, leading to infections. Some people with Marfan syndrome make too little fibrillin-1 protein.
Protein mis-folding is believed to be the primary cause of Alzheimer's disease, Parkinson's disease, Huntington's disease, Creutzfeldt-Jakob disease, cystic fibrosis, Gaucher's disease and many other degenerative and neurodegenerative disorders. Amyloidosis is a rare disease that occurs when a protein called amyloid builds up in organs. This amyloid buildup can make the organs not work properly. Organs that may be affected include the heart, kidneys, liver, spleen, nervous system and digestive tract. Protein mis-folding resulting in intracellular pre-amyloid oligomer (PAO) accumulation is sufficient to cause cardiomyocyte death and heart failure.
The harms of altering protein production within cells was well known.
Covid19 shots alter protein production in cells. So, how long will depend on the composition and potency of the exact shot taken, the amount of cells which up-took the mRNA, the exact proteins actually created by the human cells, the quantity of those foreign proteins, and the proteins’ levels of toxicity, and finally the immune response of that specific human body. All of these variables will vary the type of illness and the time distance from the shot in which a catastrophic outcome will occur. And still there may be other variables at work here.
The mechanism of action within the C19 shots IS (& I cannot emphasis this enough IS) the mechanism of harm that will create a variety of illnesses at varying time distance from the shot. This is just one example of how protein production cause healthy functioning of the human body, there are tons of other articles and research papers that support the knowledge that each cell must produce the correct protein at the correct time which folds into the correct shape for the body to function in a healthy, life-sustaining way.
Here is just one article discussing the need for the right proteins in the right cells at the right time:
https://www.cedars-sinai.org/newsroom/researchers-identify-key-proteins-responsible-for-electrical-communication-in-the-heart/
Comment 2:
Causing cells to stop doing the work of health and wellness and begin producing a toxin never leads to health and wellness and makes no sense. Once the world finally grasps that fact, honest assessments and real solutions can be found.
Proteins made by the cells of the human body provide for every process such as proper processing of glucose, the electrical signals within the heart, or even transport of oxygen to the cells. Fetuses create organs and limbs based on the correct protein being present at the proper point during gestation. The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) protein misfunction causes thick, sticky mucus to be produced in every organ of the body that makes mucus causing blockages and trapping germs, leading to infections. Some people with Marfan syndrome make too little fibrillin-1 protein.
Protein mis-folding is believed to be the primary cause of Alzheimer's disease, Parkinson's disease, Huntington's disease, Creutzfeldt-Jakob disease, cystic fibrosis, Gaucher's disease and many other degenerative and neurodegenerative disorders. Amyloidosis is a rare disease that occurs when a protein called amyloid builds up in organs. This amyloid buildup can make the organs not work properly. Organs that may be affected include the heart, kidneys, liver, spleen, nervous system and digestive tract. Protein mis-folding resulting in intracellular pre-amyloid oligomer (PAO) accumulation is sufficient to cause cardiomyocyte death and heart failure.
The harms of altering protein production within cells was well known.
Covid19 shots alter protein production in cells. So, how long will depend on the composition and potency of the exact shot taken, the amount of cells which up-took the mRNA, the exact proteins actually created by the human cells, the quantity of those foreign proteins, and the proteins’ levels of toxicity, and finally the immune response of that specific human body. All of these variables will vary the type of illness and the time distance from the shot in which a catastrophic outcome will occur. And still there may be other variables at work here.
The mechanism of action within the C19 shots IS (& I cannot emphasis this enough IS) the mechanism of harm that will create a variety of illnesses at varying time distance from the shot.
Each cell must produce the correct protein at the correct time which folds into the correct shape for the body to function in a healthy, life-sustaining way.
Here a few articles discussing the need for the right proteins in the right cells at the right time:
https://www.cedars-sinai.org/newsroom/researchers-identify-key-proteins-responsible-for-electrical-communication-in-the-heart/
Even insulin is a small globular protein! (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297421/#:~:text=Insulin%20is%20a%20small%20globular,(30%20residues)%20(Fig.)
All of the hormones in the human body, except the sex hormones and those from the adrenal cortex, are proteins or protein derivatives. (https://training.seer.cancer.gov/anatomy/endocrine/hormones.html#:~:text=Chemically%2C%20hormones%20may%20be%20classified,are%20proteins%20or%20protein%20derivatives.)
And here are articles showing that the wrong protein causes harms:
Protein misfolding is believed to be the primary cause of Alzheimer's disease, Parkinson's disease, Huntington's disease, Creutzfeldt-Jakob disease, cystic fibrosis, Gaucher's disease and many other degenerative and neurodegenerative disorders.
https://pubmed.ncbi.nlm.nih.gov/16689923/#:~:text=Protein%20misfolding%20is%20believed%20to,other%20degenerative%20and%20neurodegenerative%20disorders.
It took 60 years for “science” to understand the mechanism of harm engaged by Thalidomide. The mechanism of harm was altering production of proteins inside human cells which lead to the various malformations suffered by babies impacted with Thalidomide. This research published just before Covid19 arrived: https://www.dana-farber.org/newsroom/news-releases/2018/after-60-years--scientists-uncover-how-thalidomide-produced-birth-defects/
Covid19 shots alter protein production in cells. The harms of altering protein production in cells was known. Causing cells to stop doing the work of health and wellness and begin producing a toxin never leads to health and wellness and never will.
An important point is that the only way to explain that people are still producing spike protein is that the cell nucleus was hacked by the vaccines, proving that they are not vaccines but haccines.
Nobody, not even Wilf, could be in favor of haccines! Even more, if they reached the germline: the problem is passed to future generations and the genepool!
The Swedish study proved that the DNA was hacked in vitro.
Many studies proved the existence of DNA plasmids designed to hack the nucleus, which were not informed by the manufacturers. Even Health Canada and Australian authorities recognized this!
This is a draft of an article I'm writing:
Plasmid-Gate: DNA haccines
Nov 2017. Dr. Tal Zaks, Chief Medical Officer at Moderna, TED talk:
“We are actually hacking the software of life. … In every cell there’s this thing called messenger RNA or mRNA for short, that transmits the critical information from the DNA in our genes to the protein, which is really the stuff we’re all made out of. This is the critical information that determines what the cell will do. So we think about it as an operating system.
So if you could change that, which we call the software of life, if you could introduce a line of code, or change a line of code, it turns out, that has profound implications for everything, from the flu to cancer.
If you think about what it is we’re trying to do. We’ve taken information and our understanding of that information and how that information is transmitted in a cell, and we’ve taken our understanding of medicine and how to make drugs, and we’re fusing the two. We think of it as information therapy.”
” 1
3 Sep 2018. Moderna President Stephen Hoge: “Why are we so passionate about messenger RNA? ... In our language, mRNA is the software of life.” 2
20 Aug 2021. A Swedish study proved that, within 6 hours, “by using an in vitro cell line, we report that the SARS–CoV–2 spike protein significantly inhibits DNA damage repair, which is required for effective V(D)J recombination in adaptive immunity. Mechanistically, we found that the spike protein localizes in the nucleus and inhibits DNA damage repair by impeding key DNA repair protein BRCA1 and 53BP1 recruitment to the damage site. Our findings reveal a potential molecular mechanism by which the spike protein might impede adaptive immunity and underscore the potential side effects of full-length spike-based vaccines.” 3
Eight months after being peer-reviewed, the study was retracted without any scientific explanation, possibly due to enormous pressures, typically bribes and extortion on the authors or journal, on one of the two authors and possibly the journal: “One of the authors has raised concerns regarding the methodology employed in the study, the conclusions drawn and the insufficient consideration of laboratory staff and resources.” 4
Suspiciously, the Expression of Concern was super-fast tracked, published in 6 days since reception, including a weekend5, unlike the study, which took 2 months.6
Oct 2021. Dr. Craig Paardekooper with Team Enigma found in VAERS data:
• 1 in 200 of the batches have been found to be extremely toxic and lethal (0.5%). Each of these batches produced a consistently high number–1000 to 5000 times the base rate of 1–of adverse reaction reports, hospitalizations, and deaths across every US state. A 1 in 200 chance of death or disability.
• 1 in 20 (5%) of the batches accounted for 90% of the adverse reactions and deaths. This means 5% of the batches have caused nearly 100% of the harm from the vaccines recorded. This concurs with V-Safe: 7.8% of vaccinated people had a serious adverse reaction.7
• 70% of the batches have been found to be harmless or relatively harmless–with one or two adverse reaction reports associated.
The higher toxicity of the lethal batches could be explained by one or several possibilities:
a) Higher concentration of the same or different toxic ingredients: the concentration varies not only between vials but inside the vials (not a uniform suspension)8, proving that there’s little or no quality control, by both the manufacturer and governments.9
b) Different toxic substances (as proven by different analysis, for example of toxic metals, graphene),
c) Less degraded or zero10 RNA/DNA (for example, in manufacturing and cold chain). “The greater the stability of the envelope of lipid nanoparticles, the more frequent are vaccine side effects. …
Ribose in RNA contains a hydroxyl group … , which destabilises the phosphodiester bond. This ... can intramolecularly attack the phosphate group … of the nucleotide. This leads to autohydrolysis of the RNA even in the absence of decomposing enzymes. … DNA does not autohydrolyse and DNA fragments can remain stable for hundreds or even thousands of years. …
Moderna's mRNA LNPs are frozen in two buffers, Tris and acetate, while Pfizer/BioNTech's vaccine uses only one phosphate buffer. Phosphate buffers are known to be suboptimal for freezing as they tend to precipitate and cause abrupt pH changes at the onset of ice crystallisation.” 11 For instance, Pfizer had a degradation of 50% of the RNA12 from production to filling of vials:
d) different RNA/DNA coding:
10 Apr 2023. Kevin McKernan US study. “DNA contamination that exceeds the European Medicines Agency (EMA) 330ng/mg requirement and the FDAs 10ng/dose requirements. ...
These vectors contain an SV40 Promoter, SV40 Enhancer, S40 Origin, and an SV40 polyA signal. …
The assembly of Pfizer vial 1 contains a 72bp insertion not present in the assembly of Pfizer vial 2.
Note: an assembly is a computational representation, created by piecing together many short DNA sequences. The process of assembly involves sequencing the fragments and putting the sequences back together.
This indel is known for its enhancement to the SV40 promoter and its nuclear targeting signal.13 ...
. ” 14
People are still producing spike proteins:
Correct and thus the cells within their bodies are not producing health and wellness proteins that each tissue type needs for the body to work properly
For that matter how many cells of which tissue type uptake the mRNA and begin making spike protein? No one knows. Is different within each human body.
Again, my point is that the cells within the human body either make proteins for health and wellness or they don’t and when the cells within the body stop making health and wellness proteins disease and death occur.
The vaccines could not save more lives, simply because "official Covid-19 deaths" are fallacy-data, proven by the fact the average number of conditions being unincreased, while it should reach an average of 10 of CCW ones amongst true Covid-19 deaths: https://zenodo.org/record/8312871
There are two different analyses, the second one is much quicker and a bit simpler (is pasted as Shortened Supplement)
Oct 2023. More DNA plasmids found. “The amount of residual DNA varied substantially between lots. … a high fraction of the DNA is under the size range of the qPCR amplicons”
15
Residual DNA concentration for spike (red) and ori (blue) determined by qPCR and total residual DNA concentration in individual vials as determined by Qubit. In panel A both Pfizer and Moderna data are plotted on the same scale. The Moderna data are enclosed in a red box and displayed separately with an enlarged scale in panel B, to display detail.
Longest Oxford Nanopore (ONT) read aligns to the vector region shown in blue. ori and spike primer locations are annotated on the innermost circle. Open reading frames (ORFs) are annotated in gold and green arrows. Kanamycin resistance genes were detected in a very shallow sequencing survey of the vaccine.
Notice “HSV TK poly(A) signal” = Herpesvirus thymidine kinase polyadenylation signal (plasmid part).16
8 May 2024. König and Kirchner German study: “DNA impurities are also encased in lipid nanoparticles and are therefore difficult to quantify. … Pfizer) only measures DNA impurities in the active substance by means of … (qPCR), whose DNA target sequence is less than just 1% of the originally added DNA template. … no direct DNA quantification takes place, and compliance with the limit value for DNA contamination is only estimated from the qPCR data using mathematical extrapolation methods. However, it is also possible to dissolve the lipid nanoparticles with a detergent to directly measure DNA contamination in the final product by using fluorescence spectroscopic methods. 17
1000% variation in toxicity between vaccine batches of the vaccines points to inconsistency, FDA Good Manufacturing Practices violations, and grounds for legal nullification of any authorization by the FDA, even EUA.
https://www.bitchute.com/video/gMwRUL9mps6h/
There’s no quality control to guarantee uniformity in RNA content:
Analyzing the peaks:
23MH003: Pfizer, low reported severe side effects
https://knollfrank.github.io/HowBadIsMyBatch/HowBadIsMyBatch.html?batchCode=23MH003
FP1972: Pfizer, lethal effects
https://knollfrank.github.io/HowBadIsMyBatch/HowBadIsMyBatch.html?batchCode=FP1972
DNA is in excess of 36000% – 53400% of the FDA 10 ng limit and does not wane after expiration:
https://www.theepochtimes.com/health/covid-19-mrna-vaccine-contaminated-by-mystery-dnas-and-truncated-mrnas-health-implications-5201359
https://operationsavehumanity.substack.com/p/breaking-news-vaccine-nanotechnology
The production of mRNA vaccines at scale do not use any animal cells, but is done through in vitro transcription (IVT). The enzyme DNase is then used to destroy the DNA template and polymerase used in the reaction, and further filtration can be performed to reduce the amount of DNA fragments.
Health Canada actually wrote a detailed explanation (archive) of why DNA fragments are expected in mRNA vaccine manufacturing, and why the quantity in the vaccines is not a concern.
“Plasmids are an essential starting material for the production of mRNA vaccines. During the downstream process in mRNA vaccine manufacturing, the plasmid DNA is digested with enzymes to small fragments, and further removed to a level of not more than 10 ng/human dose, which is in line with the World Health Organization’s recommendation concerning residual DNA in biological drugs. The DNA is digested with enzymes post-transcription.”
https://archive.ph/qe0jc
The European Medicines Agency (EMA) also concurred, stating that the plasmid is broken down and removed during the manufacturing process:
https://twitter.com/BerryTartlet/status/1716923156685050004/photo/1
We would also like to point out that during the manufacturing process, this sequence and other plasmid DNA sequences are broken down and removed. Fragments of the SV40 sequence may only be present as residual impurities at very low levels that are routinely controlled.
“The plasmid DNA is likely inside the LNPs and is protected from nucleases… data demonstrate the presence of billions to hundreds of billions of DNA molecules per dose in these vaccines. Using fluorometry, all vaccines exceed the guidelines for residual DNA set by FDA and WHO of 10 ng/dose by 188 – 509-fold. ” 18
For those following the plasmid DNA contamination issue, Dr Philip Buckhaults, self described 'genome jock' from SC, has begun asking for samples of tissues (tumours etc) from those who believe they are vaccine injured. ( Or in the case of those deceased, from pathologists.) He intends to qPCR sequence these tissues to look for integration of the foreign plasmid DNA, which I firmly believe he is going to find, even on just an odds basis: millions of DNA fragments per injection, into billions of arms, 2 or more times each. This would/ will be seismic. Is the world ready to accept billions of people were injected , many by coercion, with something which has integrated foreign DNA into their genome and is causing disease and injury? 2024 will continue to be a very interesting year.
rumble.com/v3z58rg-kevin-mckernan-presentation-to-the-croatian-parliament.html
ver en bio-bomb
https://jessicar.substack.com/p/integration-of-codon-optimized-modified
https://x.com/Bithiah333/status/1746957104999514495
2023. Dr. Speicher's testing revealed DNA levels between 7 to 145 times higher than the 10ng per dose Australian FDA (Therapeutic Goods Administration TGA) limit.19 TGA rejected this by only looking at naked DNA, not the all the DNA encapsulated in the lipid nano-particles20, only targeting fragments over 200 base pairs (lowest risk)21, failing to detect the bulk of the contamination, by using qPCR which under-measures synthetic DNA22 and not disclosing their test methods.
Still, the 10 ng limit was copied from the FDA, which was not based on science but on a meeting of “experts” based on “opinions”, and was applicable only to residual DNA, not DNA-plasmid bio-weapons:
2024. Dr. Konig also proved DNA plasmid “contamination”.23
Pfizer’s mRNA injections are for gene-editing. “In collaboration with biotech company Beam Therapeutics, Pfizer scientists are developing mRNA technology as a new approach to gene editing … lipid nanoparticles ... have the potential to add, remove, ... faulty genes”. 24
https://www.pfizer.com/news/behind-the-science/unlocking-power-our-bodys-protein-factory
3 Jan 2024. Florida Surgeon Genral warned of cancer and other side effects:
“discovery of billions of DNA fragments per dose of the Pfizer and Moderna COVID-19 mRNA vaccines … concerns regarding nucleic acid contaminants in the approved Pfizer and Moderna COVID-19 mRNA vaccines, particularly in the presence of lipid nanoparticle complexes, and Simian Virus 40 (SV40) promoter/enhancer DNA. Lipid nanoparticles are an efficient vehicle for delivery of the mRNA in the COVID-19 vaccines into human cells and may therefore be an equally efficient vehicle for delivering contaminant DNA into human cells. The presence of SV40 promoter/enhancer DNA may also pose a unique and heightened risk of DNA integration into human cells.” 25
12 Sep 2024. “Florida Surgeon General Calls for Halt of Covid-19 Vaccine for Safety Reasons”:
“Potential DNA integration26 from the mRNA COVID-19 vaccines pose unique and elevated risk to human health and to the integrity of the human genome, including the risk that DNA integrated into sperm or egg gametes could be passed onto offspring of mRNA COVID-19 vaccine recipients.” 27
3 Jan 2024. Florida Surgeon General: Pfizer’s and the FDA’s lack of proper animal and human testing (bona fide research) is beyond reckless as the mRNA nanoparticle technologies have the capability of introducing oncogenes (genes that cause cancer) as well as making transgenerational changes to the human species. 28
8 May 2024. First published peer reviewed study found synthetic DNA wrapped in LNPs:
“very high DNA values were measurable in all batches after Triton-X-100 treatment, with these values ranging from 360 to 534 times the permissible DNA limit or 3600 to 5340 ng DNA per dose.
“… to dissolve the lipid nanoparticles with a detergent to directly measure DNA contamination in the final product by using fluorescence spectroscopic methods” 29 a $10 test would have been enough to detect the DNA presence!
wonder if they could be sent a sample of GMO jab SpikoGen to detect foreign genetic material?
QuBit Fluorescence was used by my friend Kevin McKernan to detect Endotoxin in Pfizer jab.
He used an anionic detergent to open up the LNPs.
https://geoffpain.substack.com/p/measuring-endotoxin-in-jabs-with
https://www.theepochtimes.com/world/exclusive-health-canada-confirms-undisclosed-presence-of-dna-sequence-in-pfizer-shot-5513277
https://www.lifesitenews.com/news/health-canada-confirms-cancer-linked-simian-virus-40-dna-sequence-found-in-pfizer-covid-jab/
https://www.lifesitenews.com/news/pfizer-reportedly-withheld-presence-of-cancer-linked-dna-in-covid-jabs-from-fda-health-canada/
https://www.sott.net/article/490967-Health-Canada-confirms-Pfizer-chose-not-to-inform-them-about-DNA-in-COVID-jabs
https://kirschsubstack.com/p/ok-you-were-right-we-admit-vaccine
Deliberately, COVID Pifzer and Moderna vaccines had and still have SV40 DNA organized fragments (plasmids). Was it really added as a promoter in the DNA plasmid to drag DNA into the nucleus? No rational argument is provided to justify the use of that dangerous viral sequence and to hide it to the health authorities.
Another position states that it was deliberately added to induce cancer. It’s no coincidence that both Pfizer and Moderna also added undisclosed DNA plasmids to hack the cell nucleus and that turbo-cancers appeared after COVID shots.
it appears that DNA from the pfizer vaccine may be replicating in mammalian cells and that even small amounts of shedded plasmids can expand to become large amounts.
Kevin McKernan, who has just reported new research, explains at the link below. Here's an excerpt:
"Pfizer vaccine sequence can be detected 1 year after vaccination in a spike positive IHC colon cancer biopsy ... we are finding tissues that have similar CTs to the naked vaccine a year later. That can only happen if the vaccine DNA is integrating and amplifying or if the DNA is being replicated by these origins of replication as episomal plasmids ... If the DNA is replicating in mammalian cells, then we don’t need self amplifying mRNA vaccines as the population was already given them with Pfizer vaccines ... small amounts of shedded plasmids could expand in the [shedding] recipients ..."
SV40 origin of replication in mammalian cells in absence of SV40 Large T-Antigen
Positive tumor biopsy qPCR one year after vaccination
https://anandamide.substack.com/p/sv40-origin-of-replication-in-mammalian
Outstanding comment. A kind of anecdotal supplement to that...We know that the body is effected in some way from literally every single thing we do to it, or put in it. Time is the other component. Over time we can do small things, which always affect outcomes. We run every day, we get slimmed and gain endurance, we drink soda every day, we get a belly, we lift small weights every day we get toned. We lift heavy weights we get muscle we smoke, we wear out our lungs, we drink, our liver changes....small things creeping over time, produce a result. Now we are instructing our cells to alter their shape and function, daily for an extended time ( months if not years, if not permanently). I wonder if Mr Wilf can explain the mechanism that causes this product to be the first and only thing that exists in the world which doesn't create change over time. ...and just like with the masks, no study or person ever calculated at what point during use that they transition from help to harm...can Mr. Wilf identify the circumstance and point in time in which the mechanisms of this product, while continuing to alter cells, stops effecting bodily change over time, and how is it doing it?
Check out my detailed refutation of Wilf’s claims about COVID-19 vaccine efficacy in the Kirsch/Wilf $2M vaccine debate!
https://www.usmortality.com/p/debunking-pro-vaccine-arguments-in
What caught my eye from a very preliminary, fast, initial skim was the assertion that each Covid death represented 10 YALL (i.e., 10 years of actual life lost). That relies on Covid being indiscriminate in the underlying state of health of those dying with it – not unreasonable an assumption in say January 2020.
However, by mid-2020 we already had data that showed YALL was 12-16 MONTHS (or 1.00 to 1.25 Years – not 10 Years) in England & Wales. Italy was similar. Based on the profile of deaths by underlying prior state of health, I would expect similar YALL in most other countries.
Given treatment mis-steps early on, and dubious measures implemented that adversely affected (in particular) the elderly, a more appropriate YALL would be lower still.
That means:
1. ED, excess deaths (assuming that the “excess” is in excess of genuine expected) actually receive very little contribution at all from “Covid”
2. Vaccination against Covid – even should it significantly reduce the risk of catching or dying from Covid – saves at most a few months of life and only for the most vulnerable. So, little benefit as all.
3. ED in 2020 were caused by other factors than Covid.
4. Expected deaths in 2021 (before calculating any excess) and onwards also need to allow for the consequences of measures taken in 2020 (and - if persisting beyond 2020 - later).
In England & Wales, ED in 2020 was circa 8% of total deaths. The majority of that is attributable to measures taken e.g., mortality will be higher if dread diseases diagnosed later than would otherwise be the case, treatment commencing at later stage than would otherwise be the case, and treatment being deferred for new and existing cases.
It would be nice to have a clean copy of Wilf's remarks the same way I read yours - can't tell what's really his anymore b/c of the invite to make comments of Wilf's - some people clearly don't know how to do that only on the side and it's in the body. Steve, would you post his non-marked up version? Thanks.
https://www.tichyseinblick.de/gastbeitrag/sars-cov-2-laborursprung/
Paul Cullen uses simple math to show that the gene therapies could at most have saved 200k lives globally. Far less than they shortened and took:
Inzwischen ist klar, dass die Wirksamkeit der Impfpräparate im Laufe der Zeit stark nachließ. Wir wollen aber diese Tatsache außer Acht lassen und die Daten aus der Pfizer-Zulassungsstudie übernehmen (auch wenn immer mehr Mängel dieser Studie bekannt werden), wonach 100 Menschen behandelt werden mussten, um einen Covid-Fall zu verhindern. Als nächstes machen wir die pessimistische Annahme, dass wie in Heinsberg vier von 1.000 SARS-CoV-2-Infizierten an Covid sterben. Wie viele Menschen muss man dann impfen, um einen Todesfall zu verhindern? Die Antwort lautet: 1.000/4 = 250 x 100 = 25.000 Menschen. Weltweit sind ca. 5 Milliarden Menschen gegen Covid geimpft worden. Somit hätten maximal weltweit etwa 200.000 Menschenleben durch die Impfung gerettet werden können, fernab der Zahl von 20 Millionen, die immer wieder in den Medien kolportiert wird.
(Edit: I posted an updated version of my comments with images here: sars2.net/rootclaim.html.)
You wrote: "And then there is miscategorization bias. Engler (2024) points out that every single study with the words (covid, vaccine, efficacy, safety) that Neil and Fenton (2024) could locate had one or more types of miscategorization errors."
Neil and Fenton's cheap trick paper was recently demolished by Peter Hegarty, who is a professor of mathematics at the University of Gothenburg: https://x.com/PeterHegarty17/status/1869784526395978142. He found that only about a quarter of the 39 papers listed by Neil and Fenton actually employed the classification delay which Neil and Fenton have dubbed the cheap trick, and none of them only applied the form of the cheap trick postulated by Neil and Fenton where the classification delay was only applied to the numerator but not to the denominator.
The abstract of Neil and Fenton's paper said: "Simulation demonstrates that this miscategorisation bias artificially boosts vaccine efficacy and infection rates even when a vaccine has zero or negative efficacy." But in their simulation the 1-to-3-week classification delay was only applied to the numerator for cases but not to the denominator for the population size. When I modified their simulation so that I also applied the classification delay to the numerator, unvaccinated and vaccinated people had an identical rate of cases: https://sars2.net/uk.html#Martin_Neil_and_Norman_Fenton_March_2024_preprint_about_the_cheap_trick. Neil, Fenton, Crawford, and Lyons-Weiler have all failed to cite a single study where the classification delay was only applied to the numerator but not to the denominator. It wouldn't make any sense because it would introduce such an obvious bias, so it should at least be documented in the methods section of the study.
---
You wrote: "Fenton, Neil, McLachlan and Craig also managed to successfully demonstrate to the UK Office of the Statistics Regulator that these miscategorisation processes meant official statistics in the UK could not be relied upon when used to support arguments of Covid-19 vaccine effectiveness (link)". Where your linked this response by the UK Office for Statistics Regulation: https://osr.statisticsauthority.gov.uk/correspondence/ed-humpherson-to-norman-fenton-martin-neil-clare-craig-and-scott-mclachlan-ons-deaths-by-vaccination-status-statistics/.
However the response said: "In your paper you also state that the number of deaths reported within the first 21 days of receiving the first dose of the Covid-19 vaccination is below that which could be expected in the general population, and that this difference is evidence of systematic undercounting of deaths by ONS. Our view of this question starts with the consideration that the population included is not representative of the general population, and it is therefore likely that any pattern you observe is attributable to the 'healthy vaccinee' effect. This happens when people who are ill (either due to COVID-19 or another relevant illness) are likely to delay vaccination. The result of this effect is a lower-than-average mortality rate within the first 21 days of receiving a vaccination. This effect is described by ONS in their Deaths by Vaccination Status publication."
The response said that the misclasfification hypothesis by Fenton et al. was likely wrong because the low number of deaths in the first few weeks after vaccination was explained by the HVE instead (as your record-level datasets have also shown is the case in other countries).
The response was an answer to a question by Craig, Neil, Fenton, and McLachlan relating to a preprint they published in March 2022 titled "Official mortality data for England reveal systematic undercounting of deaths occurring within first two weeks of Covid-19 vaccination": https://www.researchgate.net/publication/358979921. In the preprint Craig et al. speculated that because the ONS dataset for deaths by vaccination status had a low number of non-COVID deaths in the first two weeks after vaccination, deaths that occurred soon after vaccination were somehow systematically omitted or misclassified, but they discounted HVE as an explanation for the low number of deaths.
Craig et al. wrote: "The healthy vaccinee hypothesis, that those close to death will postpone or decline vaccination might hypothetically account for a lower rate of death in the first two weeks. But as an explanation it is only plausible if every possible death that might occur in the first two weeks, after the offer of vaccination, was foreknown whilst those deaths in the third week were not, and hence those dying in the third week did not postpone or decline vaccination."
However Craig et al. didn't take into account that the temporal healthy vaccinee effect actually lasts longer than 2 weeks, but if you plot deaths by weeks since the first dose in England, the increasing trend in mortality caused by the waning out of the temporal HVE is counteracted by the decreasing trend in the background mortality rate, because many first doses in England were given during the first three months of 2021 when the mortality rate was falling rapidly because the COVID wave in the winter of 2020-2021 was passing by. A similar effect can also be seen in the Czech record-level data and in your Connecticut Medicare data: https://sars2.net/connecticut.html#Deaths_by_weeks_since_vaccination. And I believe it explains why the temporal HVE only appears to last for about 3 weeks in your old Medicare data.
I guess Clare Craig may have later come to the conclusion that the low number of deaths during the first two weeks might be explained by the HVE, because in 2024 when someone asked her what she meant by the healthy vaccinee effect, she answered that "Studies show that the first few weeks after vaccination are outliers because people who are feeling ill postpone." (https://x.com/ClareCraigPath/status/1844085783365550508)
In 2022 Martin Neil tweeted: "The ONS's December report claims anomalies we identified are caused by healthy vaccinee effect. We examined the new ONS data and found NO evidence to support this claim". (https://x.com/MartinNeil9/status/1481561698792267779) And in March 2024 Neil tweeted: "There is no evidence of a healthy vaccinee effect. You are signing up to an assumption usually exploited to pretend vaccines are effective. We demonstrated this using the ONS's own data." (https://x.com/MartinNeil9/status/1767991047940907318) However by April 2024 he seems to have changed his opinion about HVE based on the Czech study which said that HVE explained why unvaccinated people had elevated mortality: https://x.com/MartinNeil9/status/1780163490247791002.
So the old letter by Craig and Neil et al. might no longer represent their current views regarding the HVE.
You wrote: "In 2023, the mainstream news in 98.5% vaccinated Australia reported that 'A troubling new study released this week has shown Australia is experiencing its highest excess mortality rates in over 80 years.'" And you linked to this article: https://www.news.com.au/lifestyle/health/health-problems/report-shows-australias-excess-mortality-rate-has-risen-to-levels-not-seen-since-world-war-ii/news-story/2f86a5483b9ae8363fc80082ae95ba3d.
The article was about excess deaths in 2022 and not 2023, and it said that Australia had about 20,000 excess deaths in 2022. At first I thought they might have exaggerated excess deaths if they used a prepandemic average baseline like the Australian Bureau of Statistics, but at Mortality Watch a 2010-2019 linear baseline also gave me 19,135 excess deaths in 2022: https://www.mortality.watch/explorer/?c=AUS&t=deaths&e=1&bf=2010&p=0. However as a percentage it was only about 11% excess deaths, and as a whole Australia has had low excess mortality since 2020 compared to countries that were not able to keep the virus out with lockdowns until the population was vaccinated.
And if the excess deaths were caused by the vaccines, then why wasn't there already high excess mortality in 2021?
Most regions of Australia had negative seasonality-adjusted mortality around the time in 2021 when people got the primary course doses. But then most regions had a sudden spike up in excess deaths around January 2022 which coincided with a similarly sharp spike in PCR positivity rate, except in Western Australia where the PCR positivity remained close to 0% in January 2022, there was also no clear increase in excess deaths in January 2022: sars2.net/i/nopandemic-australia-smaller.png.
You also wrote: "An excess deaths inquiry was held to investigate Australia's excess of nearly 30,000 deaths throughout 2021-2023." However if you use a 2010-2019 linear baseline at Mortality Watch, the number of excess deaths in Australia is 2,223 in 2021, 19,135 in 2022, and 7,846 in 2023, so almost none of the excess deaths were in 2021. And the total excess mortality in 2021-2023 is only about 5.7%.
---
You wrote: "Ed Dowd's book 'Cause Unknown' documents 500 people who died unexpectedly (that was the sole criteria). They have something in common: as far as we know, only one of the 500 was unvaccinated."
Dowd's book has a couple of alternate cover images. One version features Alex Apolinario, Josh Downie, Emmanuel Antwi, who all were not eligible for vaccination at the time of their death, and it features Logan Luker who died by suicide: https://x.com/WaitingForPerot/status/1739655583450517957.
Anothre version of the cover image features Brandon Fahey who was not vaccinated and who died from a malformed blood vessel in his brain, and it featured Aaron Vasquez who died from a congenital heart defect: https://x.com/Truth_in_Number/status/1743327152685085159. An article about Vasquez said that one of his coronary arteries "was in a place that, left surgically uncorrected, could result in death", and that he "was neither under the effects of the coronavirus nor of any vaccine against the coronavirus" (even though I don't know if it means he was unvaccinated) (https://parentheartwatch.org/dumont-student-athlete-who-suddenly-died-14-had-undetected-heart-condition-dad-says/).
You posted a plot from Mortality Watch and wrote: "This is a stunning chart because after such a huge mortality increase in 2020, we've 'pulled forward' the deaths of the weakest so excess death rates should turn into deficit death rates and the cumulative excess mortality bars should have gone down in 2021, down further in 2022, etc."
You compared total ASMR in 2021 against total ASMR in 2020, but 2020 also includes the months before COVID which reduces the total ASMR for 2020. And a lot of the excess deaths in 2021 were in January when there weren't yet that many people vaccinated.
But anyway I think Ethical Skeptic exaggerates the magnitude of the PFE: sars2.net/ethical2.html#Should_the_PFE_adjustment_last_for_only_6_6_years. He applies the PFE adjustment to the baseline for only 6.6 years, because he calculated that at some point the average age of people who died from COVID in Florida was 82 years, and he got a life expectancy of 6.6 years for age 82 for males from a calculator at seniorliving.com. However the life expectancy for females of age 82 was about 8.2 years on the same website, so I don't know why he didn't even take the average life expectancy for both males and females. And in the 2019 US life table the life expectancy at age 82 was about 8.2 years for both sexes combined. And at CDC WONDER the average age of UCD COVID deaths was about 73.8 in Florida and about 73.9 in the whole US, so both are about 8 years lower than Ethical Skeptic's figure of 82 years.
When I took the life expectancies for each age from the 2019 US life table and I calculated their average weighted by the number of UCD COVID deaths for each age at CDC WONDER, the resulting life expectancy was about 14.5 years. And if we assume that 14.5 years was the average life expectancy of people who died from COVID, then even 14.5 years later there would still be many people who would be alive if they hadn't died of COVID. So the duration of the PFE adjustment should probably be much longer than 6.6 years, which would also cause the average magnitude of the PFE adjustment to be much lower because the adjustment would be spread out over a longer period.
I did a simulation with two scenarios, where in both scenarios the population size for each age started out as one tenth of the mid-2018 US resident population estimates. I otherwise used a 2011-2019 linear trend in CMR for each age in both scenarios, except in the other scenario I multiplied the mortality rates in 2020-2021 to match the actual pattern of excess deaths in the United States. But in the scenario with elevated mortality in 2020-2021 I got only about 1.5% less deaths in 2022-2024. (All of this is described under my previous link.)
USMortality also did similar simulations and he got a much lower reduction in deaths than in Ethical Skeptic's plots: https://x.com/USMortality/status/1861469855607652804. He agrees with me that Ethical Skeptic's PFE adjustment is too heavy and he has said "I'd like to see actual proof that PFE actually exists": https://x.com/USMortality/status/1857130356052488394.
Even in Bergamo the number of deaths in the summer of 2020 was not clearly reduced apart from the very oldest age groups: https://x.com/henjin256/status/1861555471322103936.
If you calculate ASMR then it already accounts for the reduction in population size after excess deaths in a straightforward and objective way. But Ethical Skeptic thinks ASMR is some kind of black magic and he usually plots raw deaths without even adjusting for population size, and he seems to have made up the shape of his PFE adjustment curve based on some arbitrary subjective criteria. I have been telling him to use a method where he would calculate the prepandemic trend in CMR for each age and then multiply the population size of each age by the projection of the trend, but so far I haven't seen him use that method either. That method would also account for the reduction in population size in a straightforward and objective way like ASMR, but neither method produces nearly as heavy reduction in the expected deaths as his PFE adjustment.
You wrote: "Right after corporate America started requiring COVID vaccinations, the CEO of the OneAmerica insurance company publicly disclosed that during the third and fourth quarters of 2021, death in people of working age (18–64) was 40 percent higher than it was before the pandemic. Significantly, the majority of the deaths were not attributed to COVID."
However the article you linked just said: "Most of the claims for deaths being filed are not classified as COVID-19 deaths, Davison said." (https://www.thecentersquare.com/indiana/indiana-life-insurance-ceo-says-deaths-are-up-40-among-people-ages-18-64/article_71473b12-6b1e-11ec-8641-5b2c06725e2c.html) So it said most deaths in general and not most excess deaths, which does not exclude the possibility that most of the 40% excess deaths would've been due to COVID.
On CDC WONDER during the second half of each year, ages 18-64 have 351102 deaths in 2019, 437852 in 2020, 495284 in 2021, and 395982 in 2022: `fread("http://sars2.net/f/uspopdeadmonthly.csv")[year<2024&month>=7&age%in%18:64,sum(dead),year]`. So the number of deaths in 2021 is in fact about 41% higher than in 2019.
In July to December of 2021, ages 18-64 had 87677 deaths with UCD COVID and 97630 deaths with MCD COVID. So deaths with UCD COVID account for about 61% of the difference between 2021 and 2019 (from 87677/(495284-351102)). The number of deaths with UCD related to recreational drug use also increased from 34240 in the second half of 2019 to 49196 in the second half of 2021, so it's about 10% of the increase in total deaths between 2019 and 2021: `v=fread("curl -Ls sars2.net/f/vital.csv.xz|xz -dc");v[month>=7&age%in%18:64][cause%like%"X4[0-4]|X6[0-4]|Y1[0-4]",.(ucd=sum(ucd),mcd=sum(mcd)),year]`. If I would've looked at MCD instead of UCD, the percentages would've increased to about 68% for COVID deaths and 11% for drug deaths.
---
On CDC WONDER if you calculate a ratio of deaths with UCD COVID in 2021 divided by 2020, it's about 1.97 in ages 18-64 but about 1.00 in ages 65 and above: `v[cause=="U071"&age%in%18:64,sum(ucd),year][,V1[2]/V1[1]]`. So why did working-age people have such a high percentage of COVID deaths in 2021 relative to 2020? I think it's because in 2021 working-age people were less likely to be vaccinated than elderly people.
In the winter of 2020-2021 the Czech Republic had a pattern of mortality with three distinct humps, where in ages 80+ the first hump was the highest and the third hump was the lowest, but ages 40-59 followed an opposite pattern. I think it's because by the time of the third hump, the percentage of vaccinated people was over 50% in ages 80+ but less than 10% in ages 40-59: sars2.net/czech.html#Daily_deaths_and_vaccine_doses_by_age_group.
Compared to elderly people, working-age people in the Czech Republic also had a high age-standardized rate of COVID hospitalization in 2021 relative to 2020, but it's explained by a lower percentage of vaccinated people among working-age people: sars2.net/czech3.html#Hospitalizations_by_age_group_and_vaccination_status.
---
Another problem with blaming vaccines for the excess deaths in working-age people in the second half of 2021 is that there were low excess deaths in northeastern states which had a high percentage of vaccinated people, but there were high excess deaths in southern states which had a low percentage of vaccinated people: sars2.net/statistic.html#Fabian_Spieker_US_summer_of_deaths_in_2021. A large part of the deaths also occurred during the Delta wave in August to September 2021, even though there weren't that many new people getting vaccinated at the time. And in some northeastern states like Connecticut where the PCR positivity rate remained low in August to September of 2021, there were also low excess deaths. If the wave of excess deaths was due to vaccines then why did occur in some states but not others even though all states got vaccinated?
Among the vaccinated people who are included in your "Medicare all states subset" spreadsheet, there was also very little increase in deaths in August to September of 2021 relative to the general population of the US which also includes unvaccinated people, so the bump in deaths during the Delta wave is almost flat (ibid.). Your old Medicare spreadsheet also shows that among people in southeastern states who got vaccinated in the second half of 2021, the number of deaths was not clearly elevated during the first few months from vaccination (ibid.).
---
The number of additional working-age people who got vaccinated in the third quarter of 2021 after the mandates is also fairly low compared to the number of people who got vaccinated in the first half of 2021: sars2.net/statistic.html#Pierre_Kory_Excess_deaths_in_young_age_groups_in_the_fall_of_2021. So if the mandates caused a massive wave of deaths then why weren't people also dropping like flies around March to May 2021 when a larger number of people got vaccinated?
You wrote: "Hulscher (2024) looks at highly vaccinated King County. 'We found a 25.7% increase in total cardiopulmonary arrests and a 25.4% increase in cardiopulmonary arrest mortality from 2020 to 2023. Applying our model from these data to the entire United States yielded 49,240 excess fatal cardiopulmonary arrests from 2021-2023' (due to the COVID vaccine)."
However Hulscher et al. simply included all cardiac arrest deaths and they didn't exclude deaths due to COVID. Washington State had a low number of COVID deaths in 2020. Based on CDC WONDER's data for King County, deaths with MCD COVID explain a large part of excess MCD cardiac deaths since 2020, and there's a low number of excess UCD cardiac deaths since 2020: sars2.net/statistic2.html#McCullough_Foundation_Paper_about_cardiac_arrests_in_King_County_EMS_data.
Hulscher's figure for 2023 was not even real data but a linear projection of the figures for 2021 and 2022. The real figure for 2023 ended up being only slightly lower than their projection, but I think the authors should've just excluded 2023 from their paper instead of making up projected data for 2023.
The authors only showed data going back to 2015 even though the source where they took the deaths extended back to 2003. The authors might have omitted earlier years because there was a big drop in the number of deaths between 2014 and 2015.
The 2015-2019 linear baseline they used might have been too low especially by 2023, because the long-term trend in deaths going back to 2003 seemed to be curved upwards. But you couldn't tell it from their paper which only included data going back to 2015. At CDC WONDER the long-term trend in all-cause deaths in King County is similarly curved upwards.
McCullough's Substack article about the paper was titled "Peer-Reviewed Study Reveals 1,236% Surge in Excess Cardiac Arrest Deaths Among 2 Million COVID-19 Vaccinated Individuals". But the paper didn't include information about the vaccination status of the people who died, and it might be that unvaccinated people were overrepresented among the people who died in excess since many of the excess deaths seem to have been due to COVID.
And the 1236% increase was actually an increase from about 1.0% excess deaths in 2020 to about 11.6% excess deaths in 2023, so it was only an increase of about 10.6 percentage points. McCullough's people seem to have intentionally chosen a misleading headline, because they probably knew their followers would misinterpret the headline figure of a 1236% increase.
Hulscher et al. wrote: "Specifically, the number of cardiopulmonary arrest deaths increased from 891 in 2015 to 1,110 in 2020, representing a 24.6% increase. In 2021, deaths jumped to 1,229 and continued to rise to 1,310 in 2022. The projection for 2023 suggests 1,392 cardiopulmonary arrest deaths in King County, WA, indicating a sharp 25.4% increase since the onset of COVID-19 vaccination campaigns"
However in Hulscher's Table 1 the number of deaths in 2020 was 1121 and not 1110. But 1110 was his baseline value for 2020, so he seems to have accidentally calculated the increase between 2020 and 2023 using the baseline value instead of the number of deaths for 2020.
Hulscher even calculated the number of deaths wrong because he multiplied the number of patients with the rounded percentage of patients who didn't survive, even though he could've derived the exact number of deaths by subtracting the number of patients who didn't survive instead. The real number of deaths in 2020 was 1116.
But anyway, Hulscher's number of deaths actually increased from 1121 in 2020 to 1392 in 2023, so it was an increase of about about 24.2% and not 24.6%. But his baseline also increased by about 12% from 1110 in 2020 to 1245 in 2023. So the excess deaths only increased by about 10.8 percentage points: (1392/1245)-(1121/1110).
However his figure for 2023 wasn't even the real number of deaths but a linear projection of the deaths in 2021 and 2022. The real number of deaths in 2023 was published in September 2024 and it was 1358, so the excess deaths between 2020 and 2023 increased by only about 8.1 percentage points relative to Hulscher's baseline: (1358/1245)-(1121/1110).
But his linear baseline might have also been too low in 2023 because the long-term trend in deaths seemed to be curved upwards. And he also didn't exclude COVID deaths and there were still some COVID deaths in 2023.
You wrote: "Denis Rancourt 125 countries study paper (521 pages) found an overall average vDFR=.00127 which is 1 death per 787 doses which is consistent with other estimates presented here." In the 125-country paper and the earlier southern-hemisphere paper, Rancourt ignored how excess deaths had a much higher temporal correlation with COVID deaths than with the daily number of vaccine doses administered. When Rancourt calculated the figure of 17 million vaccine deaths, he assumed that all excess deaths since vaccine rollout were due to vaccines.
However in a recent paper Rancourt now wrote that US data presented strong evidence that excess deaths were nearly entirely associated with deaths labeled as COVID deaths (https://correlation-canada.org/respiratory-epidemics-without-viral-transmission/):
> In the high-quality databases for the USA, there is a close match between the weekly reported COVID-19 mortality and weekly excess all-cause mortality, in the Covid period (2020-2022), including prior to and during the vaccine rollouts (CDC, 2023).
> To the degree that COVID-19 death assignation represents a serious respiratory condition at death, and given the intricate weekly temporal matching of the reported COVID-19 mortality and excess all-cause mortality for up to 3 years in the USA data, this represents strong evidence that respiratory infections were dominantly (virtually entirely) associated with the excess all-cause mortality.
In the 125-country paper Rancourt wrote that the Czech Republic had a spike in deaths which coincided with the booster rollout. However I told him that if you look at age-stratified data, deaths peaked around the same time in all age groups even though new vaccine doses administered peaked about a month before deaths in ages 80+ and about a month after deaths in ages 40-59: https://x.com/henjin256/status/1819537703068738006. Age-stratified data presents a fatal weakness to his approach of temporally correlating spikes in deaths with a vaccine rollout.
In Rancourt's new paper I believe he referred to the Czech data in the following paragraphs, where he now seems to have admitted that the excess deaths that coincided with the booster rollout could not be attributed to people who had recently received the booster:
> Recently, Rancourt et al. (in preparation) analysed national mortality data in one country in which COVID-19 vaccination status was known at death, including the history of COVID-19 vaccinations, in a case in which the country exhibited rapid vaccine rollouts strongly temporally associated with observed surges in excess all-cause mortality. They found that relevant **peaks in excess all-cause mortality associated with booster rollouts could not preferentially be assigned to booster-vaccinated individuals** (and also that the vaccine had no detectable survival benefit).
> This means that the COVID-19 vaccination primary cause described in Section 3.3.5 did not produce a measurable increase in excess all-cause mortality in this country, which in turn means that sharp peaks in excess all-cause mortality which are temporally associated with rapid vaccine rollouts need not imply that COVID-19 vaccination is a primary cause of death. Rather, it seems that (as pervasive as they are) such temporal associations between mortality peaks and rapid vaccine rollouts are due to the primary cause described in Section 3.3.6 of campaigns and measures associated in time and place with COVID-19 vaccine rollouts. Although non-conclusive in general, this is consistent with the fact that the vaccine toxicity causing death inferred from populationwide adverse-effect monitoring is usually too small to be detected directly in populationwide (e.g., national) cause-independent all-cause mortality, as per analyses of USA VAERS (Vaccine Adverse Events Reporting System) data (Hickey and Rancourt, 2022).
> This would mean that the lethality of medical measures imposed during the Covid period and during vaccine rollouts is much greater than generally acknowledged, and much greater than the known (VAERS, autopsies, etc.) vaccine toxicity itself.
Rancourt now has to perform circus-level acrobatics to reconcile his earlier claim of 17 million vaccine deaths with his new claim that there were not necessarily that many deaths associated directly with vaccination, so he now suggests that the deaths were rather caused indirectly by measures associated with vaccination or by stress induced by vaccination: https://x.com/henjin256/status/1865524490194637008. As examples he gave "aggressive or extreme immobilization and isolation enforcement during the vaccine rollout" and "disrupted patient care schedule, including regular medication, meals and hydration".
However his new theory doesn't seem to explain why the excess deaths were concentrated in waves which were much higher in unvaccinated than vaccinated people even after adjusting for HVE. Why did stress induced by vaccination kill unvaccinated people?
You wrote: "The official UK ASMR 21 days from dose 1 vs. Dose 2. Shows it is dose dependent. A 'safe' vaccine cannot have a dose dependent ASMR." And you linked to this tweet: https://x.com/stkirsch/status/1858664074621710521.
However the tweet didn't show what part of the ASMR was accounted for by COVID deaths. In January 2021 COVID ASMR was about 56% of all-cause ASMR in the category "First dose, less than 21 days ago", but there was very low COVID ASMR in the category "Second dose, less than 21 days ago": sars2.net/uk.html#Clare_Craig_ASMR_within_3_weeks_from_vaccination_for_first_and_second_doses. So it might be that the vaccine was not yet fully effective during the first couple of weeks from vaccination, or that two doses offered better protection than one dose.
People who have passed the "healthy vaccinee" test twice might also have lower mortality risk on average than people who have passed it once.
You wrote "this Henjin-produced graph is seriously flawed as explained in great detail here". And you linked to this post by canceledmouse: openvaet.substack.com/p/dunning-kruger-illustrated-asmr-explained.
The reason why canceledmouse was not able to reproduce my ASMR calculation was because he had 4 bugs in his Perl code. When he calculated an 11-day moving average of deaths, he added together the deaths on 11 days but he forgot to divide them by 11. And the percentage of each age group in the standard population should've been divided by 100 to get the fraction of the age group. And the deaths per person-days should've been multiplied by 365 to get deaths per person-years. And he divided the ASMR value by the percentage of total population made up by the age group which is not part of the formula for calculating ASMR.
He fixed the bugs after I pointed them out to him, and after that his code produced mostly similar results to my code: sars2.net/czech3.html#Reply_to_Substack_article_by_canceledmouse. The remaining differences to my code were for two reasons. First he used the WHO standard population which has a low percentage of people in elderly age groups so it's a very poor match to the Czech population structure. And second he applied an 11-day backwards moving average to deaths but not population size, so his deaths were lagging 5 days behind the population size which underestimated the ASMR of vaccinated people in early 2021 when the vaccinated population size was increasing rapidly.
canceledmouse claimed that my bucket analysis was done poorly, but the only reason he gave was that I assigned a random birthday to each person so he claimed my analysis was not reproducible. However he didn't notice that I assigned a seed in my code before I generated the random birthdays. He corrected his error after I notified him of it.
canceledmouse also claimed that I shouldn't have used the term ASMR because I used the Czech 2021 census population as my standard population, but it's not a standardized standard population like the WHO standard population. However I showed why he was wrong in the section of my website I linked above.
canceledmouse pointed out that when he ran my code for generating the plot for ASMR by vaccine type, he got extra gray line with the label NA. However that was a line for Novavax that I forgot to remove from the code on my website.
---
You also linked to your summary article about the Czech data, but I addressed the article here: sars2.net/czech3.html#Comment_to_Substack_post_by_Kirsch.
This site already shut down, go figure! Policy, I guess discource is a threat...
This is from the WILF argument:
"1. The mRNA, which stands for modified mRNA, contains a synthetic nucleotide called N1-methylpseudouridine, which replaces all of the Uridines that would naturally occur in mRNA. This synthetic molecule results in an mRNA molecule that is long-lasting and does not readily breakdown in the same way that natural mRNA does. "
Is this what JJ Couey is talking about when he says the RNA cannot pandemic? That a natural RNA will readily breakdown before it can spread worldwide as essentially the same molecule detectable whether in Manaus or Madrid or Macau?
I really appreciate you locking onto this very important issue, like a Pitt Bull on a rope. You continue to inspire and motivate me… I just wanted to say thank you.
Lock them up. It is past time for Nuremburg 2.0.
COVID and the jabs were the greatest genocide in the history of the world. More people died than the total from WW One and WW Two combined.
Short ropes and long drops. Fauci can go first. Gates can be next.
Thank you Mr. Kirsch for keeping this in the public eye.
Wilf, just another big pharma shill. Everyone with a working brain has known for years that the shot/hospital protocols killed and maimed millions in America alone. Most of us have many friends and family that have suffered or died. We also are aware of the malfeasance that was perpetrated on the people of the world. The patents tell the tale.
The Hungarian pop studies used the CDC definition of vaccination status (you're "unvaccinated" until 14 days after second shot), so the actual mortality outcomes are inverted. There is no benefit, only harm.
Under Wilf:
1. His table under methodology cherry-picks your weakest arguments.
2. Also under methodology, the "if net detriment" bullet point ignores the power of mass formation and humans going along to get along and therefore carefully staying within the Overton window.
3. Regarding the paper about the Hungarian population, I added this comment to the document:
"The increasing deaths with time for most vaccines, especially Moderna and Pfizer and especially in the first (epidemic) period, suggest a huge healthy vaccinee effect with death rates of Moderna recipients increasing by a factor of 4, mostly during the first (epidemic) period. Perhaps Moderna was taken primarily by the oldest where this effect would be most prominent. Perhaps instead it indicates vaccine related deaths.
I propose that 100% of the "benefit" this study showed and probably quite a bit more than that was due to not accounting for the fact that the healthy vaccinee effect has impact on death rates over only about the first 3 months with the majority of that over the first month. Those over about age 65-75 will also represent the vast majority of the healthy vaccinee effect as most non-accidental deaths occur in that age group.
Most over age 65 got vaccinated early (February and March). The healthy vaccinee effect was prominent during the epidemic period (April-June 20), but had faded by the nonepidemic period (June 21-August 15). This is supported by the increasing death rate with time among the vaccinated as the healthy vaccinee effect wears off and decreasing death rates among the unvaccinated as deaths of those who remained unvaccinated due to being on deaths doorstep have mostly occurred in the first 90 days. The steadily increasing slope among the vaccinated and the steadily decreasing slope among the unvaccinated is a very good match of the idealized death curve that results from the healthy vaccinee effect.
I further propose that there are lots of vaccinated bodies buried in the partially vaccinated period, especially among those who remained partially vaccinated due to sustaining an injury with the first dose. The authors revealed exactly zero information about what happened during to the partially vaccinated cohort."
Steve just wanted to see how your’re feeling - saw you post on telegram. Wishing you good health! And a Super big hug and Thank you for all you do! 🥰
FYI, being a statistician, what are the chances that Dr. Luc Montenier , Dr. Rashid Buttar and Dr. Zelenko all passed away in a three year period after having said that the Covid Vacc was a biological bomb, a work of the Grim Reaper. They gave a predictions that within a Four year period that the ravages of a planned population reduction program would come to fruition…. Well…..are we close… are we in it, what are the stats to prove-or disprove, oppppp you have already documented your findings, gruesome!
When working as an expert engineering witness I made sure my points were clear to non-technical readers. You have to present your material convincingly and clear so any reasonably educated person can understand. I remember this one case for a plaintiff customer whos lawyer I worked with who proudly showed me his indexed binder with his argument. The judge didn't care about his meticulous and expensive (at my customer's cost) binder. He never looked at it. He homed in immediately at the essence of the defendant's argument that the defendant did not sign for the extra work and therefore the plaintiff would not be getting paid for the unauthorized work. I had pointed this out to my customer in the beginning but he ignored my point.
I mention this as you dazzle with all the studies you quote however that requires reading the studies to find their supportive points and their flaws. Judges prefer concisely homing in on the important points you are trying to make.