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Fourth Pfizer Dose Slashed Risk of Catching Omicron in Study

@Joes Place Update (Jan 2022): I have calculated a rigorous arrival curve of actual in-clade mutation rate for SARS-CoV-2 at 1.45 x 10-4 mutations per site per year. This analysis is taken straight from the Nextstrain data published 26 Jan 2022,35 and can be accessed by clicking here. The data extract and worksheet can be accessed by clicking here. This matches the GISAID estimate of rate of mutation (1.8 x 10-4 in Exhibit 7.8 below) well. Thus our assumption of 3.6 x 10-4 was conservatively suitable for this analysis. One thing to note as well, is that SARS-CoV-2 is not mutating nearly the rate at which SARS-CoV-1 did, nor is it mutating at the purported furious pace which was sold to us in the media (see bottom chart in Exhibit 7.8).

Exhibit 7.8 – Actual mutation rate of SARS-CoV-2 compared to other human viruses
There are 29,811 single strand RNA nucleotides in SARS-CoV-2. Given its 93 differential mutations from a ~March 2020 Alpha Clade 20B variant, which can be seen in Exhibit 7.7, this would at first glance indicate around 8.7 years of genetic distance wound up inside Omicron’s divergence from other existing variants. However we must adjust the calculation in that only 66 of the 93 total mutations constitute the most typical RNA virus mutation, called a ‘substitution’.36 Therefore,

Substitution Clock – .00036 x 29811 = 10.7 mutations per year 66/10.7 = 6.1 years of mutation
However, genetic distance by typical RNA virus mutation is not the end-all of this derivation. Not all nucleotides mutate at the same rate.37 As we just mentioned, most mutations arrive in the form of synonymous high frequency events called substitutions – mutations that separate Covid in-clade variants in linear sequence from their initial index sequence (see horizontal lines in the left panel of Exhibit 7.9 below). The mutations in Omicron do not follow this pattern, and in fact constitute an exception within the entire diagram. Instead, Omicron mutations comprise about 32% of what are called ‘insertion/deletion’ mutations (INDELs).38 INDELs do not arrive at the same rate as higher frequency substitutions, but rather constitute less common absences or novel-presences of an entire nucleotide. Insertions and deletions constitute a change in the logical structure of the RNA sentence and not a mere synonymous replacement of a word, if you will. Thus they produce failures (extinction) more often than successes, and as such constitute a much bigger challenge in terms of genetic language. They can also often result in different mutational clock measures as compared to those based upon substitutions alone. In fact, RNA virus INDELs are 4x less frequent in their occurrence than are substitutions (actually deletions are 8x less frequent, and the majority of INDELs for Omicron are deletions – however, we still use 4x here for conservancy).39 If we approach our genetic clock with this second method of measuring genetic distance, we get the following result – which importantly, substantiates and exceeds fairly well our substitution-nucleotide method of measuring genetic distance conducted above.

INDEL Clock – (.00036 / 4) x 29811 = 2.68 INDEL mutations per year 30/2.68 = 11.2 years of mutation
We therefore through triple-conservancy in this method,40 can reasonably cite that 6.1 years (the smaller of the two above substitution and INDEL based estimates) would be the minimum time duration required to enact all 66 Omicron substitution mutations as observed in sample sequence QLD-2568 of 2 Dec 2021. We must leave the alarming INDEL mutation rate in Wittgenstein silence because sadly we cannot connect it back to any kind of usable reference. Finally, before we move on from this set of calculations, we should employ this same method to take quick note of the evolutionary time which would be required for SARS-CoV-2 to have evolved naturally from its nearest relative among beta coronaviruses, BANAL52. This will act as a double-check of the validity of our estimates above as well (consilience). We divide by two here because two virus evolutionary pathways are involved in this analytical context. Reader please note that this is a benchmark comparison for establishing credibility of our assumed 3.6 x 10-4 survival mutation rate only. It does not mandate that SARS-CoV-2 necessarily evolved naturally from BANAL52. The conjectured Jan 2018 lab accident could have released either a natural or edited SARS-CoV-2 under our hypothesis.

Total amount of time needed to naturally evolve from BANAL52 = (1/2 x 4% of 29,811 / 10.7) = ~55 years.
 
@Joes Place This matches exactly (consilience again) the 55 years divergence cited at the beginning of Question #7a above (1966 average through to 2021). It also means that 1 x 10-3 mutations per nucleotide per year estimates for rates of mutation are far too high and theoretical, to be used as basis for estimating the appearance of sustained Covid-19 variants like Omicron (the context we need for this deliberation). This 10-3 order of magnitude was also the mutation rate for SARS-CoV-1 after all, which mutated so fast that it exterminated all of its genetic lineages before it could spread past one season (see Exhibit 15.1).41 The Furin Cleavage Site mutates at a rate ten times faster (3.6 x 10-3) than does the overall Covid genome.42 So a too-fast Covid mutation rate, will only result in destruction of the virus’ very ability to infect human hosts to begin with.

Our assumed rate of mutation provides for the appearance of a new sustained SARS-CoV-2 variant every year, per clade. We have 23 clades as of December 2021 (see Exhibit 7.9), and only 13 named variants to date – so even this conservative rate indexes high against the Covid-19 mutational reality (left hand side of mutation rate spectrum in Exhibit 7.8 above). Therefore, as a mutation rate, 3.6 x 10-4 not only matches historical indexing against FCS mutations, but moreover provides a falsification-based sound match from every angle of outside-comparative or deliberation within this analysis. Nonetheless, I fully anticipate that the raw (theoretical) 1.1 x 10-3 or higher mutation rate will be exploited by those desperate to enforce the Dec 2019 narrative. Hold them accountable by showing that not only does Omicron not have an existing precedent from which it could recently have mutated (see Exhibits 7.6 and 7.9), but their preferred mutation rate would serve to extinguish SARS-CoV-2 within a season as well – both by SARS-CoV-1 precedent, and by mathematical modeling. Such a raw theoretical and excessive assumption is an orphan assumption and artifice, which in no way matches our observed Covid clade-to-variant reality.

Now lets carry this three-way validated, 6.1 years of genetic distance forward as we consider it in relation to the nearest relative to the Omicron variant. Omicron carries a mutation called N501Y, which affords the virus a greater ability to bind to human cells. This mutation was also present in the Alpha variant and was linked to its higher contagiousness as compared to the wild variant. But N501Y did not exist in Delta, nor the wild variant, so those constitute a separate evolutionary pathway – this is very important. Therefore Omicron must share an LCA not with the wild/Wuhan variant, but rather the very first Covid Alpha 20B Clade of 3 February 2020.43 Remember, that the 66-mutation line drawn in the GISAID chart on the left in Exhibit 7.9 is an assumption, not a derivation (and a wholly different assumption from the one in the Exhibit 7.7 left hand chart we showed earlier in this Omicron subject segment). These connectors therefore, are basically viral fiction.

Exhibit 7.9
Exhibit 7.9 above, as a set of phylogenetic precedents shown on the right hand side, if not the incumbent timing as well, was corroborated by a December 2021 Journal of Medical Virology study, whose Figure 3. can be found by clicking here.44

Now, if we add this 6.1 years of mutation clock time to evolve an Omicron variant directly from Alpha 20B (Sep 2021, or even 3 Feb 2020) as the Nextstrain/GSAID chart on the left in Exhibit 7.9 suggests, we get Oct 2027 (or Mar 2026) as a timeframe for Omicron’s arrival. This obviously did not happen – so Omicron did not originate from Alpha 20B itself, nor the wild variant, nor Delta, but rather a prior LCA with Alpha 20B. Therefore, conversely we must parse these same 6.1 years from the arrival date of Omicron (Nov 2021) through to the detection date of Alpha 20B (3 Feb 2020) in order to find the actual date of the LCA with Omicron and Alpha.

By the 2 variable/2 sentence reduction shown on the right hand side of Exhibit 7.9 we are able to solve for an estimated emergence date for this last common ancestor of January 2018. Exactly the date we have estimated for the lab leak in China.
To frame this in a simpler perspective – the average maximum clade divergence from Clade 19A (26 Dec 2019), wild variant, on the GSAID chart is 46 nucleotides (1 sigma = 6.2).45 The below mathematical approach is not entirely valid because successive mutations are merely synonymous substitutions, and do not usually include anywhere near Omicron’s 29% portion of INDELs. Nonetheless, let’s benchmark Omicron against the other clades on Exhibit 7.10 below.

Benchmarking off this relative measure serves to place the latest Omicron variant (93 mutations on 2 Dec 2021) as originating from an LCA at 93/46 x 23 months = 47 months – or Jan 2018 in origin. A clean match.
 
@Joes Place Exhibit 7.10 – Omicron mutation timeline and lack of extant variant basis
If evolutionary pressure during the last year had served to accelerate this variant into being (or even cause its 12-mutation spread observed over a mere 8 days), then it should have borne the nucleotide base of any variant on the above chart (Exhibit 7.10) which has existed since Clade 19A. As one can observe in Exhibits 7.6 and 7.9 above, Omicron did not bear such a genetic legacy from any existing clade – merely the ‘N501Y association’ with Alpha. However, this mere single nucleotide linkage with Alpha is not enough solid evidence, so we undertook a more sophisticated approach to viral adjacency next.

Therefore, we developed a 144 nucleotide by nucleotide affinity-contrast analysis, weighted by each nucleotide position’s measured evolutionary entropy, or how often a particular site mutates over time. Thus if a number of low entropy sites have mutated, we know that those mutations look a long time to develop – longer than their peers which mutate more often, or have a higher entropy.46 We then applied these weighted factors across the mutation differences between four important variant benchmarks in SARS-CoV-2 history:

  • B.1 (Wuhan, 12/24/2019),
  • B.1.1.7 (Alpha, 2/3/2020),
  • B.1.617.2 (Delta, 10/08/2020, and
  • B.1.1.529 (Omicron, 11/24/2021).
If we take the frequency of differential mutations shared between these four variant benchmarks, and assign a value of 1 to each, then divide that value by the entropy for that nucleotide (therefore lower entropy sites carry more contrast weight), then we end up with a value for each of the variety of relative strengths in mutation relationships between the four variants (see ‘Relationship’ chart in the top center of Exhibit 7.11 below). The worksheet which outlines this analysis can be accessed by clicking here. The source for the nucleotide data was Covid CG – Covid Genetics: Lineage Reports by Nucleotide.47 The source for the entropy measures was Nextstrain.48

If those weighted contrast strengths are then summed as a total for 144 nucleotide sites, and shown as vectors on a spanning tree diagram (see upper right of Exhibit 7.11), they can be optimized into a single configuration of nodes (optimized spanning tree).49 As you can see, these relationship connectors span in direct proportion to the amount of time required for evolution to drive the introduction of each variant. Accordingly, a set of annual rings are placed, centered on Delta, indicating the relative amount of time in genetic distance each variant is from the introduction of the first sample sequence of Delta. Exhibit 7.11 is based upon the most important factor, differential mutations (not shared between two variants). However, we ran another version of this same chart based upon affinity mutations (shared) and got the exact same outcome, January 2018. That chart can be seen by clicking here.

If we then remove redundant but weaker relationship vectors we end up with a relationship spine, as shown on the lower center of Exhibit 7.11. As you can see from both elements inside Exhibit 7.11, the entropy weight averaged genetic distance (by differential mutations or contrast) places Omicron at a distance from Delta, of sufficient magnitude that Omicron cannot mathematically be a contemporary of the B.1-Alpha-Delta triad below. The only direction one can apply the time of genetic distance required is into the past. Thereby arriving at January 2018, quod erat demonstrandum. The exact same result which the affinity analysis produces.

This effort produces a diagram which allows us to observe that Omicron not only is nowhere near related to Alpha and Delta, but is offset from Delta by 2.8 years of evolution.

The important thing to understand here is that the only way one can assemble this optimized spanning tree is by assuming the ancestor of Omicron to have existed prior to the B.1 Wuhan strain – separated by an amount of time around quadruple that between Wuhan and either Alpha or Delta.
Exhibit 7.11
The dynamics of virus outbreaks are not well understood. Viruses have been observed to flourish, go dormant, and then re-emerge with relatively little genetic clock progression between the two outbreaks despite being separated in time by 5 years or more.50 Thus, objection to this theory based upon the idea that Omicron was ‘too human adapted and similar to the human adaptations of Alpha/Delta variants to be this old’, does not hold scientific water. Again, a highly ‘if’-dependent effort to stuff 10 pounds of evolution into a 2 pound bag of recency.

Thus, by means of this highly divergent novel-base Omicron genome, we find agreement with our early 2018 lab leak estimate and as well provide a ninth means of falsifying China’s Dec 2019 narrative.
Update 1: the following study came two weeks after this article was published.51

[Extensive analysis] reveals that Omicron variant formed a new emergent group that was not originating [from] other variants. It’s possible [therefore], that Omicron has been around for much longer than [originally] predicted…
Kandeel, Beltagi, et al.; Omicron variant genome evolution and phylogenetics, 14 Dec 2021
Update 2: It was clear in the variant data even in February 2020, that the December 2019 Wuhan variant (D614G) was merely the latest variant to hit the world at that time (no different than Delta emerging in India in October of 2020). A full fourteen clades and six variants already existed the very first day upon which SARS-CoV-2 was detected. Exhibit 7.12 (Figure 4. extracted from the Koyama, Takahiko footnoted study) shows a clear prior base of slower-moving SARS-CoV-2 variants well before October 2019, bearing extensive variant depth characteristic of years of prior circulation.52

Exhibit 7.12 – Koyama, Takahiko & Platt, Daniel & Parida, Laxmi. (2020). Variant analysis of COVID-19 genomes.
Conclusion – We found that several variants of the SARS-CoV-2 genome exist (Feb-May 2020) and that the D614G clade [Wuhan, Dec 2019] has [merely] become the most common variant since December 2019. The evolutionary analysis indicated structured transmission, with the possibility of multiple introductions into the population.
BEAST phylogenies give a tantalizing hint of population structuring in the evolution of Covid-19 in the human population. The branches with coalescence patterns most consistent with slow growth are almost all travelers and individuals with no contact with the seafood market. The rest of the growth occurred quite rapidly suggesting near exponential effective population growth. Curiously, not only is the slow-growth branch dominated by travelers, but the Covid-19 lineages appear to be phylogenetically related to each other, suggesting an exposure point for these individuals that is distinct from the rest of the population.

Koyama, Takahiko, et al.; Variant analysis of COVID-19 genomes, June 2020
 
YOU ARE a LIAR bonehead. Thanks for the spelling correction too dip wad. It does not trace back to prior variants whatsoever. You're a joke.

7b. Omicron Variantgenetics are older than and lineage does not connect back to Dec 2019 ‘wild’ type

Finally, emergence of the Omicron variant of SARS-CoV-2 in Botswana in November of 2021 presents another post October 2019 falsification-level event. The Omicron variant of SARS-CoV-2 has alarmed many scientists due to the sheer number of genetic mutations it carries — 93 in all, including 32 in the spike protein alone, 16 silent, 27 nucleotide deletions, 3 nucleotide/amino acid insertions, and at least 43 mutations that are unique to Omicron (see both left and right hand panels in Exhibit 7.7 below).26 27 28 In all, Omicron’s mutation set bears 29% nucleotide deletions, which is highly divergent as compared to the known SARS-CoV-2 phylogeny shown on the left side of Exhibit 7.7 below. This percentage of deletions (27 of 93) and amino acid mutations (50 of 93) both far exceed the number of much more likely silent-synonymous mutations (16 of 93). This suggests that the ‘deletions’ are rather actually ‘insertions’ which occurred in the lineage to the 2 Feb 2020 Alpha Variant Clade 20B. The terminology inversion stemming from an effort to stuff a 10 pound virus divergence into a 2 pound bag of posterity. We will treat these generically (conservatively) as INDELs (insertion-deletions) therefore in the genetic clock analysis later in this segment of Question #7.


Exhibit 7.7 – Nextclade: clade assignment, mutation calling and quality control for viral genomes (21K Omicron – Sequence QLD-2568 – 2 Dec 202129
As well, Omicron carries 3 amino acid insertion mutations (ins214EPE) which do not exist in any extant clade of SARS-CoV-2, but does exist in other human alpha and beta coronaviruses.30 If this insertion occurred as the result of ‘template switching’ in a human coronavirus co-infected individual, then the other alleles in Omicron should have matched the lineage of one of our known clades. It didn’t. Thus, we face a confounded problem in trying to stuff Omicron artificially into a recent (<2 year) timeline of origin. In the timeline developed from GISAID data in the left hand panel of Exhibit 7.7 for instance,31 the exceptional red clade-line, which suggests a narrative-comforming lineage for Omicron, is an assumption and not a derivation.


This confounding, along with the evidence presented below, indicates that Omicron’s genetic particulars constitute not merely mutations, but more importantly alleles which pre-date, not post-date, our best index case of SARS-CoV-2 in Oct/Dec 2019 (according to Chinese and other narratives). In other words the genetic last common ancestor (LCA, aka ‘MRCA’) which birthed Omicron existed well prior to the Wuhan wild and B.1 variants of Oct – Dec 2019. Again, this is not inductive evidence (as has been used to assemble the Wuhan/China/WHO wet market chronology), but is rather much stronger deductive inference. The entailed calculations and logic are outlined below and in Exhibit 7.9.

Multiple studies have estimated that SARS-CoV-2 mutations occur at the rate of 1 x 10-4 (measured by survival in population)32 to 1.1 x 10-3 raw mutations per nucleotide per year.33 These extremes are shown in Exhibit 7.8 below. This equates to .0001 to .0011 mutations per nucleotide per year, with an average of .0006. Since the sustaining of a mutated clade-member or especially novel variant occurs at a slower rate than the raw rate of mutation,34 we err conservatively towards the survival rate, or .00036 (.0006 x .6 or 3.6 x 10-4) mutations per nucleotide per year, based upon the arrival rate of new sustainable mutations in the circulating population.

What you've posted is nonsense.
 
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@Joes Place Exhibit 7.10 – Omicron mutation timeline and lack of extant variant basis
If evolutionary pressure during the last year had served to accelerate this variant into being (or even cause its 12-mutation spread observed over a mere 8 days), then it should have borne the nucleotide base of any variant on the above chart (Exhibit 7.10) which has existed since Clade 19A. As one can observe in Exhibits 7.6 and 7.9 above, Omicron did not bear such a genetic legacy from any existing clade – merely the ‘N501Y association’ with Alpha. However, this mere single nucleotide linkage with Alpha is not enough solid evidence, so we undertook a more sophisticated approach to viral adjacency next.

Therefore, we developed a 144 nucleotide by nucleotide affinity-contrast analysis, weighted by each nucleotide position’s measured evolutionary entropy, or how often a particular site mutates over time. Thus if a number of low entropy sites have mutated, we know that those mutations look a long time to develop – longer than their peers which mutate more often, or have a higher entropy.46 We then applied these weighted factors across the mutation differences between four important variant benchmarks in SARS-CoV-2 history:

  • B.1 (Wuhan, 12/24/2019),
  • B.1.1.7 (Alpha, 2/3/2020),
  • B.1.617.2 (Delta, 10/08/2020, and
  • B.1.1.529 (Omicron, 11/24/2021).
If we take the frequency of differential mutations shared between these four variant benchmarks, and assign a value of 1 to each, then divide that value by the entropy for that nucleotide (therefore lower entropy sites carry more contrast weight), then we end up with a value for each of the variety of relative strengths in mutation relationships between the four variants (see ‘Relationship’ chart in the top center of Exhibit 7.11 below). The worksheet which outlines this analysis can be accessed by clicking here. The source for the nucleotide data was Covid CG – Covid Genetics: Lineage Reports by Nucleotide.47 The source for the entropy measures was Nextstrain.48

If those weighted contrast strengths are then summed as a total for 144 nucleotide sites, and shown as vectors on a spanning tree diagram (see upper right of Exhibit 7.11), they can be optimized into a single configuration of nodes (optimized spanning tree).49 As you can see, these relationship connectors span in direct proportion to the amount of time required for evolution to drive the introduction of each variant. Accordingly, a set of annual rings are placed, centered on Delta, indicating the relative amount of time in genetic distance each variant is from the introduction of the first sample sequence of Delta. Exhibit 7.11 is based upon the most important factor, differential mutations (not shared between two variants). However, we ran another version of this same chart based upon affinity mutations (shared) and got the exact same outcome, January 2018. That chart can be seen by clicking here.

If we then remove redundant but weaker relationship vectors we end up with a relationship spine, as shown on the lower center of Exhibit 7.11. As you can see from both elements inside Exhibit 7.11, the entropy weight averaged genetic distance (by differential mutations or contrast) places Omicron at a distance from Delta, of sufficient magnitude that Omicron cannot mathematically be a contemporary of the B.1-Alpha-Delta triad below. The only direction one can apply the time of genetic distance required is into the past. Thereby arriving at January 2018, quod erat demonstrandum. The exact same result which the affinity analysis produces.

This effort produces a diagram which allows us to observe that Omicron not only is nowhere near related to Alpha and Delta, but is offset from Delta by 2.8 years of evolution.


Exhibit 7.11
The dynamics of virus outbreaks are not well understood. Viruses have been observed to flourish, go dormant, and then re-emerge with relatively little genetic clock progression between the two outbreaks despite being separated in time by 5 years or more.50 Thus, objection to this theory based upon the idea that Omicron was ‘too human adapted and similar to the human adaptations of Alpha/Delta variants to be this old’, does not hold scientific water. Again, a highly ‘if’-dependent effort to stuff 10 pounds of evolution into a 2 pound bag of recency.


Update 1: the following study came two weeks after this article was published.51


Update 2: It was clear in the variant data even in February 2020, that the December 2019 Wuhan variant (D614G) was merely the latest variant to hit the world at that time (no different than Delta emerging in India in October of 2020). A full fourteen clades and six variants already existed the very first day upon which SARS-CoV-2 was detected. Exhibit 7.12 (Figure 4. extracted from the Koyama, Takahiko footnoted study) shows a clear prior base of slower-moving SARS-CoV-2 variants well before October 2019, bearing extensive variant depth characteristic of years of prior circulation.52

Exhibit 7.12 – Koyama, Takahiko & Platt, Daniel & Parida, Laxmi. (2020). Variant analysis of COVID-19 genomes.
You're completely full of shit.

One of your photos is linked by Google Image Search to a CATO Institute Op Ed.

Opening statement claims "Los Alamos National Laboratory" confirms this - the link provided goes TO NO SUCH SOURCE.
It's linked to a Russian article and Russian propaganda, spud.

The frigging link claiming to be Los Alamos (which is outright fabrication) is this:

And it says:

The mutation Spike D614G is of urgent concern; it began spreading in Europe in early February, and when introduced to new regions it rapidly becomes the dominant form. Also, we present evidence of recombination between locally circulating strains, indicative of multiple strain infections. These finding have important implications for SARS-CoV-2 transmission, pathogenesis and immune interventions.
 
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How many flu shots do you get in a year?
How is this comparable to an entirely new virus, that no one's ever been exposed to?

When you make THAT comparison, you see that 4x-5x shots is pretty much the norm.
 
Cross-reactive and innate immunity in humans can handle “entirely new” viruses without the help of 4 or 5 injections of a rushed vaccine. At least mine did. I’m not going to risk compromising a fully functioning system.
 
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Wow, 80% of the population is fully vaccinated but they only account for 41% of the deaths. That’s great news.

Numbers actually make sense here, when you realize the deaths rates are about 3x+ higher for unvaccinated people than vaccinated.

20% of the population there is unvaccinated, and with a 3x deaths rate, implies they'd account for 60% of the deaths, and that's exactly where the numbers seem to land...

Coincidence? Nope.
 
The corporations that made hundreds of billion$ the past two plus years indicate they were extremely good at selling the “died of” angle.
 
The corporations that made hundreds of billion$ the past two plus years indicate they were extremely good at selling the “died of” angle.

Good thing we have independent agencies and scientists to evaluate the data, and don't need to rely on "Pfizer" and "Moderna" for their press-releases.
 
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What you've posted is nonsense.
LOL! You're an idiot. Given the in-depth analysis I posted, this is all you got except for looking at some photo in a google image link. Do better man. You're entirely wrong. Most of the data in the article is sourced off NextStrain and backed by studies. You can't even come up with anything to refute what was said. You have no understanding of it which is why you can't come up with anything.

You're pathetic and WRONG.
 
https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fb3d554bf-cc3c-4e09-ab78-76d5fa1cbbae_1171x961.png
 
LOL! You're an idiot. Given the in-depth analysis I posted
You didn't post "in depth analysis"

I took one link and found Russian propaganda bullshit.
Claiming "Los Alamos National Lab" found Omicron came from another source. But know what happens when you click the link? it takes you to an article that says no such thing.

And Los Alamos has not performed "epidemiology" tracking on the viruses, they've run computer simulations - so this is clearly a Russian troll - YOU- posting intentional disinformation.
 
Which means it can absolutely be related to your Covid, because that's a known complication from it.

And getting the vaccine at the same time you get Covid can have usual impacts, as well - which is why they recommend you WAIT to get the vaccine until after recovering for several weeks.
Again I'm not following, Vaccinated 4 times BEFORE I got Covid...

March = Vaccination # 4
April = Pulmonary Embolism
July 1 = Covid positive

Note - Wife is now Covid positive, August 8, after getting her 5th jab on August 1st...
 
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Baloney.

You bailed out of that thread, after your links were exposed. Vanished like a Fart in the Wind.
I've never supported Ivermectin. You are mistaken about that. I did post a comprehensive list of HCQ studies that showed both positive and negative results. You love moving goalposts so much that you probably are confused.

Let's go back and talk about the Pfizer and Moderna clinical trials, and how that turned out. Those studies wildly exaggerated the efficacy and safety of the vaccines. Just 13 months ago Joe Biden said if you were vaccinated you wouldn't get Covid or spread Covid. I posted a link to the CNN article in another thread.

Dr. Birx also admitted the CDC knew the claims were phony. You can keep believing in worthless studies that are designed to promote a US Government goal. Dr. Birx has already admitted that narrative was designed for people just like you.

I'm going to pay more attention to studies from Europe, Australia, Israel, etc. because they don't have the pressure of NIH grant money to come to a conclusion that favors Pfizer or Moderna.
 
I've never supported Ivermectin. You are mistaken about that. I did post a comprehensive list of HCQ studies that showed both positive and negative results. You love moving goalposts so much that you probably are confused.

Let's go back and talk about the Pfizer and Moderna clinical trials, and how that turned out. Those studies wildly exaggerated the efficacy and safety of the vaccines. Just 13 months ago Joe Biden said if you were vaccinated you wouldn't get Covid or spread Covid. I posted a link to the CNN article in another thread.

Dr. Birx also admitted the CDC knew the claims were phony. You can keep believing in worthless studies that are designed to promote a US Government goal. Dr. Birx has already admitted that narrative was designed for people just like you.

I'm going to pay more attention to studies from Europe, Australia, Israel, etc. because they don't have the pressure of NIH grant money to come to a conclusion that favors Pfizer or Moderna.
 
I would imagine that a fifth dose of the Pfizer vaccine will deliver world peace...
 
I've never supported Ivermectin. You are mistaken about that. I did post a comprehensive list of HCQ studies that showed both positive and negative results. You love moving goalposts so much that you probably are confused.

Let's go back and talk about the Pfizer and Moderna clinical trials, and how that turned out. Those studies wildly exaggerated the efficacy and safety of the vaccines. Just 13 months ago Joe Biden said if you were vaccinated you wouldn't get Covid or spread Covid. I posted a link to the CNN article in another thread.

Dr. Birx also admitted the CDC knew the claims were phony. You can keep believing in worthless studies that are designed to promote a US Government goal. Dr. Birx has already admitted that narrative was designed for people just like you.

I'm going to pay more attention to studies from Europe, Australia, Israel, etc. because they don't have the pressure of NIH grant money to come to a conclusion that favors Pfizer or Moderna.
Memory refresher

Too many gems to select from, but the “dumb” starts around page 2. Your links for IVM narrative and your propping up a Duke study are pages 4 and 5. Also good to note what posts Finance gives likes to (and the poster providing them).
 
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Your reply was 1 minute after his post. Did you even look at the link? Does 'peer reviewed' not mean anything to you? The very first one is a clinical study, not just statistical. Why would you dismiss this without even reading it?
He’s intimately familiar with informedchoiceaustralia.com and their conspiratorial ways...been studying and monitoring them for years. Probably.

It’s a lot of responsibility being the board’s resident doctor and immunologist but it’s something he takes very seriously.
 
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