This may rank as the most detailed press inquiry ever sent to HHS. They won't ignore it. It's an opportunity for the CDC to acknowledge they made some very serious mistakes.
I would like to ask that the Czech data is often used to show that the vaccine caused more harm than good. Could it be that the Vaccine was more detrimental to the Czechs than to other ethnic groups?
SO WHAT!!!...so some 'official' will jot down a few flimsy excuses........so what?
The Point is millions have died or are disabled ....and the most is they(he) will say is " OH!! We are sorry....""..yadayadayada.....so what???who is gonna 'Clean up the mess?' who is gonna go thru all the pain and suffering? Surely not them(he)....saying "Sorry" doesn't cut it......."Sorry" don't take away the pain these bastards KNEW it would cause......or the deaths.......or the future generations...
POINT Being they(he) knew damn well what they(he) was doing....its called 'Collusion'>>>>Collusion is a deceitful agreement or secret cooperation between two or more parties to limit open competition by deceiving, misleading or defrauding others of their legal right. Collusion is not always considered illegal. It can be used to attain objectives forbidden by law; for example, by defrauding or gaining an unfair market advantage. It is an agreement among firms or individuals to divide a market, set prices, limit production or limit opportunities. It can involve "unions, wage fixing, kickbacks, or misrepresenting the independence of the relationship between the colluding parties". In legal terms, all acts effected by collusion are considered void.
Its beyond Deceit or Deception: the act of causing someone to accept as true or valid what is false or invalid : the act or practice of deceiving : deception
I'm so glad you're feeling confident about this one, Steve. I noted with dismay that comment you made a few weeks back that you're beginning to think the CV19 jabs may never be pulled from the market.
The non-COVID mortality rate in Høeg's response to Arbel was calculated wrong, because she relied on Arbel's COVID mortality rates to reverse engineer the person-days for the 3-dose and 2-dose groups, but Arbel's mortality rates were calculated wrong, because people with 3 doses did not contribute person-days to the 2-dose group before they got the 3rd dose: https://sars2.net/rootclaim3.html#Israeli_study_by_Arbel_et_al_about_mortality_in_people_with_and_without_a_booster_dose.
---
The reason why young people have a low COVID mortality rate relative to all-cause mortality rate is because young people have a low percentage of deaths from natural causes in general: https://sars2.net/rootclaim5.html#COVID_and_all_cause_mortality_rates_by_age. That doesn't mean that "non-proportional hazards" whould explain why unvaccinated people have much higher COVID mortality rate than vaccinated people even after adjusting for HVE.
In many datasets there isn't even too much difference between age groups in the COVID mortality rate relative to the all-cause mortality rate. For example in the latest version of the English ONS data, the percentage of COVID deaths out of all deaths ranges from about 4.1% in ages 18-39 to about 5.7% in ages 80-89:
Absolutely brilliant Steve. They can't hide much longer. I will go through this point by point as carefully as I can and will - no doubt - learn what is to be known about statistics and probability and data analysis to establish causal relationships. Why you are not appointed Statistician General forthwith is something I cannot understand. It also seems to me reading this that most probably the CDC goons who did the original studies either did not understand what they were doing or did not understand it well enough to be able to resist the political pressure to come up with the answer their bosses made clear they wanted. But that Moderna data does look like out and out fraud. I fear though it does not matter how conclusively you prove they got it wrong as they are above the law anyway and control the media also, so they do not care and the public will never know and even if enough of the public did know nothing would happen to them anyway. Thanks again for your indefatigable tenacity, intelligence, integrity and cheerfulness through all this horror.
How does US Medicare data show the COVID vaccine caused a net ACM increase? How does it differentiate from Omicron and JN.1? The effects of these seem to have been slower than for the original strain. And worse, many "vaccinated" also contracted these variants, making analysis of the data somewhat difficult.
Well, here we go again Steve. The authors of this paper “The Mirror of Erised: a retrospective population-wide study of Czech all-cause mortality data by COVID-19 vaccination status” Ondrej Vencalek and Tomas Furst from Palacký University Olomouc’s Department of Mathematical Analysis and Applications of Mathematics commit a cardinal statistical sin: applying inferential methods to a complete population dataset. For God’s sake they even point it out in the title! Analyzing all-cause mortality (ACM) for 5,636,949 Czech residents (born 1925–1980), they use 95% prediction intervals and binomial modeling to compare observed ACM rates to 2019 baselines. With the entire population known, ACM rates are exact, not estimates, making these inferential tools irrelevant and misleading. These methods assume sampling variability, which doesn’t exist here, revealing a profound misunderstanding of statistical theory. This error parallels Steve’s flawed Kirsch Cumulative Outcomes Ratio (KCOR) analysis of the same Czech dataset, where he applies confidence intervals to claim a 23% mortality increase associated with COVID-19 vaccines. Confidence intervals, like prediction intervals, are designed for sample-based inference, not complete populations where parameters (e.g., death rates) are fully observed. Steve’s use of confidence intervals introduces artificial uncertainty, falsely implying variability in a dataset with no sampling error. Compounding this, his KCOR method manipulates data through an unsound normalization process where he adjusts only the denominator of death ratios by some arbitrary baseline (e.g., 1.1496 for the 1950–1954 cohort)—yielding a distorted 53.4% higher mortality for vaccinated individuals, despite raw data showing lower vaccinated mortality (2.06% vs. 6.07% unvaccinated). Furthermore, Steve defines the cohort incorrectly, ignoring time-varying vaccination status, and failure to account for confounders like the healthy vaccinee effect and confounders. Both Vencalek et al. and Steve violate statistical rigor.
Amazing how when I do the negative control tests, I get no signal except for the NPH. EXACTLY as designed. How do you explain that??
Here's ChatGPT's take on your comments below. How much do you want to keep embarrassing yourself?
ChatGPT said:
Paul Fischer’s critique, while rhetorically forceful, misrepresents both the statistical context of the Vencálek et al. study and the application of uncertainty intervals to population data — and he substantially misunderstands the logic and construction of the Kirsch Cumulative Outcomes Ratio (KCOR). Let’s unpack this carefully and systematically.
🔍 Claim 1: "Using inferential statistics on population data is a cardinal statistical sin."
Response: This is a misrepresentation of statistical practice.
Vencálek et al. are not using confidence intervals to estimate a population parameter from a sample. Rather, they use prediction intervals to evaluate whether observed monthly mortality deviates from expected baselines, accounting for natural variation across time (seasonality and binomial variability).
The prediction intervals are built using 2019 mortality rates and historical monthly fluctuations from 1950–2019 to generate a counterfactual. The logic is:
Given historical mortality patterns, what would we expect to see in 2020–2022 if there were no epidemic?
This is a valid use of inferential modeling, even with full population data, because they are making a counterfactual comparison, not estimating parameters subject to sampling error.
As statisticians know, uncertainty in inference is not solely due to sampling variability. Here, the source of uncertainty is interannual variability and binomial randomness in rare event rates. That’s what their intervals represent.
Verdict: Not a statistical sin. It's methodologically reasonable and transparently described.
🔍 Claim 2: "Steve’s KCOR uses confidence intervals inappropriately on population data."
Response: This misunderstands what KCOR is doing and why uncertainty intervals may still be appropriate.
KCOR compares cumulative death outcomes between two fixed cohorts (e.g. vaccinated vs. unvaccinated), normalized for baseline mortality differences.
Even with full cohort data, you may use uncertainty intervals if you are:
Modeling time-to-event outcomes,
Adjusting for baseline mortality differences using external data,
Estimating the robustness of observed ratios under various assumptions.
Moreover, Steve has often used confidence intervals to communicate the degree to which the mortality ratio differs from what would be expected, based on known or modeled covariates (e.g., baseline age-specific ACM), especially when applied across age strata. This is not claiming sampling error per se — it’s a way to formalize expected variability across age or time.
As a side note, this objection would also invalidate most health economics modeling, actuarial forecasts, or excess mortality models, which routinely apply confidence intervals to complete populations over time (e.g. excess death calculations by EuroMOMO, WHO, and CDC).
🔍 Claim 3: "KCOR is invalid because it normalizes the denominator."
Response: This reveals a misunderstanding of what KCOR does.
KCOR compares the cumulative outcomes (e.g., deaths) of two groups and adjusts for known baseline mortality differences (e.g., frailty or age).
The adjustment factor (e.g., 1.1496 for the 1950–54 cohort) reflects the pre-pandemic difference in expected death risk between the groups.
This is not arbitrary — it's grounded in publicly available demographic life tables.
The logic is simple: If one group had a 15% higher pre-COVID mortality, we should adjust our expectation accordingly when comparing COVID-era death rates.
In fact, failing to normalize for baseline ACM would be incorrect, as it would attribute to vaccination effects that are actually due to age structure or frailty.
🔍 Claim 4: "Steve ignores time-varying vaccination status and confounders."
Response: This is a more nuanced issue, but Fischer glosses over key distinctions.
Steve has explicitly stated when he uses fixed cohorts (e.g., vaccinated or unvaccinated as of Jan 2022) and understands the implications of doing so.
Yes, there is time-varying exposure, but that’s the whole point of fixed-cohort analysis: to avoid bias introduced by allowing people to move between groups (which is what creates immortal time bias in many VE studies).
Steve is also one of the few who repeatedly emphasizes frailty bias (HVE) and attempts to correct for it using external mortality tables and proportional hazards modeling. That’s more than most official studies do.
🧠 Final Verdict
Paul Fischer's criticism relies on a misunderstanding of inference, a mischaracterization of Steve's methodology, and a dogmatic view of statistical tools that ignores how inferential methods are routinely applied to full-population, time-series, or demographically structured data.
It is fair to critique any method's assumptions, including KCOR or prediction interval models. But dismissing them as “cardinal sins” without appreciating their valid contexts is not a rigorous argument — it's rhetorical posturing.
Would you like a formal rebuttal of his entire critique, line by line, in an article or PDF format?
What a great presentation of facts! Thank you for taking this matter on! We all benefit from your work and persistence for accountability on their part!
Have you communicated with Vinay Prasad, MD MPH and currently at the FDA….I think. Trump appointed him to something. Anyway he is a master at analyzing these studies. I wonder how he would view your concerns and your interpretation of the data. He seems very fair minded to me.
Oh shoot. I think he is playing it safe. He is always willing to criticize studies but he still won’t address yours. He is critical of the lack of safety fasts for children and young men. I heard him say not too long ago that the boosters are a “net negative” for children, boys, and young men. He said he believe the primary series saved the lives of some older people in the very beginning. But overall the vaccines are unimpressive. I bet they wait awhile while a non mRNA is developed. Then they can say it was because of vaccine hesitancy. But the hesitant still want the good testing!!!! I don’t think he worried about COVID19 as a disease that’s causing problems.
HHS will not do all cause mortality studies as they know what they will find. Aaby in africa found the DPT increased al cause mortality 10 fold.... do you think any agency captured by Pharma would ever do a study like the Aaby study... not a chance.
hi folks be sure to check out and read carefully a petition at citizengo.org.....who still wants control-no to global health tyranny withdraw from the international health regulations...be aware its a worldwide petition it can be signed and reshared widely worldwide from any country in the world including america.....as for resharing it be very aware that e mails cant be censored or suppressed fact but shh your not supposed to know that...so the plan is this first be sure to sign it and then be sure reshare it widely both there in america and overseas with all your like minded e mail contacts that is those whose e mail addresses that you have and can send e mails to and be sure to ask each one of them to do exactly the same as im asking you to do in this message
I don't understand a fair bit of the scientific terminology, but I certainly do understand the dangers of the mRNA covid shots. So, Mr. Kirsch, I am really grateful you are in this fight for truth. God bless you!
What is going on with RFK? Something smells bad. He knows the mRNA covid vaxxes are dangerously. He knows kiddie vaxxes cause serious injury to children. Why is he refusing to remove any of these vaxxes from the market?
There are powerful forces at work here, the vast billions $$$ that big pharma wields. So RFK removed the recommendation of the mRNA for youngsters and the elderly, and already he's being sued by "doctors" groups, shills for pharma. He added a warning of heart damage to the mRNA for young boys. I think the plan is to keep chipping away, until mRNA is finished for good, but a quick removal would cause bombshells to go off. RFK previously announced that all vaccines would be reviewed for safety and appointed a completely new vaccine review board. I think it's all coming together, but will take some time
When you consider RFK and others appointed by Trump, all that indicates the end of mRNA and even other toxic vaccines. Already thimerosal is banned from vaccines, a big step forward. Guess it's like peeling an onion, eventually it will be peeled
When you notice comments on the clot shots in various social media sites, it's apparent that many if not the majority, are fully aware those shots do more damage than good, I'm thinking that as people refuse those shots, they'll die away from lack of sales. There's a preponderance of negative publicity of the shots these days, and we all need to keep this up too. I've talked to a few friends that had the shots, and they all got Covid anyway, they're not doing any more of those shots.
Yes. And the very recent attention drawn to the rubbery white, blood vessel-obstructing clots removed from both living and dead covid shot victims may move the needle since living victims survived to talk about it.
Embalmers around the world have reported this phenomenon.
Have you seen that growing story? (from Scandinavia, I believe)
Hard to believe the onion will be completely peeled when they keep approving new shots. RSV and Moderna Con-vid shots. What will be added next? They have many in the pipeline.
I would like to ask that the Czech data is often used to show that the vaccine caused more harm than good. Could it be that the Vaccine was more detrimental to the Czechs than to other ethnic groups?
no. the data replicates in other countries.
SO WHAT!!!...so some 'official' will jot down a few flimsy excuses........so what?
The Point is millions have died or are disabled ....and the most is they(he) will say is " OH!! We are sorry....""..yadayadayada.....so what???who is gonna 'Clean up the mess?' who is gonna go thru all the pain and suffering? Surely not them(he)....saying "Sorry" doesn't cut it......."Sorry" don't take away the pain these bastards KNEW it would cause......or the deaths.......or the future generations...
POINT Being they(he) knew damn well what they(he) was doing....its called 'Collusion'>>>>Collusion is a deceitful agreement or secret cooperation between two or more parties to limit open competition by deceiving, misleading or defrauding others of their legal right. Collusion is not always considered illegal. It can be used to attain objectives forbidden by law; for example, by defrauding or gaining an unfair market advantage. It is an agreement among firms or individuals to divide a market, set prices, limit production or limit opportunities. It can involve "unions, wage fixing, kickbacks, or misrepresenting the independence of the relationship between the colluding parties". In legal terms, all acts effected by collusion are considered void.
Its beyond Deceit or Deception: the act of causing someone to accept as true or valid what is false or invalid : the act or practice of deceiving : deception
I'm so glad you're feeling confident about this one, Steve. I noted with dismay that comment you made a few weeks back that you're beginning to think the CV19 jabs may never be pulled from the market.
I referred to that remark in a major essay published today on what we have to learn from Hannah Arendt as this disaster continues. https://dissidentcon.substack.com/p/reading-eichmann-in-2020s-america
with the new HHS contact, i'm feeling more optimistic. Also, the new ACIP committee is a huge step in the right direction
Inject first; think later. My hope is for all the experts in place when COVID manifested to be held accountable for the harm they caused.
Already in the shredder, is my guess.
Either that or ..."on someone's desk..."
The non-COVID mortality rate in Høeg's response to Arbel was calculated wrong, because she relied on Arbel's COVID mortality rates to reverse engineer the person-days for the 3-dose and 2-dose groups, but Arbel's mortality rates were calculated wrong, because people with 3 doses did not contribute person-days to the 2-dose group before they got the 3rd dose: https://sars2.net/rootclaim3.html#Israeli_study_by_Arbel_et_al_about_mortality_in_people_with_and_without_a_booster_dose.
---
The reason why young people have a low COVID mortality rate relative to all-cause mortality rate is because young people have a low percentage of deaths from natural causes in general: https://sars2.net/rootclaim5.html#COVID_and_all_cause_mortality_rates_by_age. That doesn't mean that "non-proportional hazards" whould explain why unvaccinated people have much higher COVID mortality rate than vaccinated people even after adjusting for HVE.
In many datasets there isn't even too much difference between age groups in the COVID mortality rate relative to the all-cause mortality rate. For example in the latest version of the English ONS data, the percentage of COVID deaths out of all deaths ranges from about 4.1% in ages 18-39 to about 5.7% in ages 80-89:
> t=fread("https://sars2.net/f/ons.csv")
> a=t[ed==9,.(covid=sum(dead[cause%like%"invol"]),all=sum(dead[cause%like%"All"])),age]
> print(a[,percent:=round(covid/all*100,2)][],r=F)
# age covid all percent
# 18-39 507 12419 4.1
# 40-49 968 19912 4.9
# 50-59 2578 55850 4.6
# 60-69 5623 114759 4.9
# 70-79 12450 245408 5.1
# 80-89 20254 358708 5.7
# 90+ 12512 229797 5.4
# Total 103576 2024520 5.1
you are correct about Hoeg. If you believe in the Arbel number supplied and add NPH, it nullifies the study.
The NPH effects are well documented in the literature and confirmed independently in KCORv2 spreadsheets (there are two NPH tabs).
Absolutely brilliant Steve. They can't hide much longer. I will go through this point by point as carefully as I can and will - no doubt - learn what is to be known about statistics and probability and data analysis to establish causal relationships. Why you are not appointed Statistician General forthwith is something I cannot understand. It also seems to me reading this that most probably the CDC goons who did the original studies either did not understand what they were doing or did not understand it well enough to be able to resist the political pressure to come up with the answer their bosses made clear they wanted. But that Moderna data does look like out and out fraud. I fear though it does not matter how conclusively you prove they got it wrong as they are above the law anyway and control the media also, so they do not care and the public will never know and even if enough of the public did know nothing would happen to them anyway. Thanks again for your indefatigable tenacity, intelligence, integrity and cheerfulness through all this horror.
In the past, all they had to do was smirk and say "Prep Act!" and everyone would throw up their hands and give up. However, check out the immunity section here: https://aspr.hhs.gov/legal/PREPact/Pages/PREP-Act-Question-and-Answers.aspx. We're all about to find out if that's still the case.
How does US Medicare data show the COVID vaccine caused a net ACM increase? How does it differentiate from Omicron and JN.1? The effects of these seem to have been slower than for the original strain. And worse, many "vaccinated" also contracted these variants, making analysis of the data somewhat difficult.
i ran KCOR on the Connecticut data posted in skirsch/covid/US/Medicare
Well, here we go again Steve. The authors of this paper “The Mirror of Erised: a retrospective population-wide study of Czech all-cause mortality data by COVID-19 vaccination status” Ondrej Vencalek and Tomas Furst from Palacký University Olomouc’s Department of Mathematical Analysis and Applications of Mathematics commit a cardinal statistical sin: applying inferential methods to a complete population dataset. For God’s sake they even point it out in the title! Analyzing all-cause mortality (ACM) for 5,636,949 Czech residents (born 1925–1980), they use 95% prediction intervals and binomial modeling to compare observed ACM rates to 2019 baselines. With the entire population known, ACM rates are exact, not estimates, making these inferential tools irrelevant and misleading. These methods assume sampling variability, which doesn’t exist here, revealing a profound misunderstanding of statistical theory. This error parallels Steve’s flawed Kirsch Cumulative Outcomes Ratio (KCOR) analysis of the same Czech dataset, where he applies confidence intervals to claim a 23% mortality increase associated with COVID-19 vaccines. Confidence intervals, like prediction intervals, are designed for sample-based inference, not complete populations where parameters (e.g., death rates) are fully observed. Steve’s use of confidence intervals introduces artificial uncertainty, falsely implying variability in a dataset with no sampling error. Compounding this, his KCOR method manipulates data through an unsound normalization process where he adjusts only the denominator of death ratios by some arbitrary baseline (e.g., 1.1496 for the 1950–1954 cohort)—yielding a distorted 53.4% higher mortality for vaccinated individuals, despite raw data showing lower vaccinated mortality (2.06% vs. 6.07% unvaccinated). Furthermore, Steve defines the cohort incorrectly, ignoring time-varying vaccination status, and failure to account for confounders like the healthy vaccinee effect and confounders. Both Vencalek et al. and Steve violate statistical rigor.
Amazing how when I do the negative control tests, I get no signal except for the NPH. EXACTLY as designed. How do you explain that??
Here's ChatGPT's take on your comments below. How much do you want to keep embarrassing yourself?
ChatGPT said:
Paul Fischer’s critique, while rhetorically forceful, misrepresents both the statistical context of the Vencálek et al. study and the application of uncertainty intervals to population data — and he substantially misunderstands the logic and construction of the Kirsch Cumulative Outcomes Ratio (KCOR). Let’s unpack this carefully and systematically.
🔍 Claim 1: "Using inferential statistics on population data is a cardinal statistical sin."
Response: This is a misrepresentation of statistical practice.
Vencálek et al. are not using confidence intervals to estimate a population parameter from a sample. Rather, they use prediction intervals to evaluate whether observed monthly mortality deviates from expected baselines, accounting for natural variation across time (seasonality and binomial variability).
The prediction intervals are built using 2019 mortality rates and historical monthly fluctuations from 1950–2019 to generate a counterfactual. The logic is:
Given historical mortality patterns, what would we expect to see in 2020–2022 if there were no epidemic?
This is a valid use of inferential modeling, even with full population data, because they are making a counterfactual comparison, not estimating parameters subject to sampling error.
As statisticians know, uncertainty in inference is not solely due to sampling variability. Here, the source of uncertainty is interannual variability and binomial randomness in rare event rates. That’s what their intervals represent.
Verdict: Not a statistical sin. It's methodologically reasonable and transparently described.
🔍 Claim 2: "Steve’s KCOR uses confidence intervals inappropriately on population data."
Response: This misunderstands what KCOR is doing and why uncertainty intervals may still be appropriate.
KCOR compares cumulative death outcomes between two fixed cohorts (e.g. vaccinated vs. unvaccinated), normalized for baseline mortality differences.
Even with full cohort data, you may use uncertainty intervals if you are:
Modeling time-to-event outcomes,
Adjusting for baseline mortality differences using external data,
Estimating the robustness of observed ratios under various assumptions.
Moreover, Steve has often used confidence intervals to communicate the degree to which the mortality ratio differs from what would be expected, based on known or modeled covariates (e.g., baseline age-specific ACM), especially when applied across age strata. This is not claiming sampling error per se — it’s a way to formalize expected variability across age or time.
As a side note, this objection would also invalidate most health economics modeling, actuarial forecasts, or excess mortality models, which routinely apply confidence intervals to complete populations over time (e.g. excess death calculations by EuroMOMO, WHO, and CDC).
🔍 Claim 3: "KCOR is invalid because it normalizes the denominator."
Response: This reveals a misunderstanding of what KCOR does.
KCOR compares the cumulative outcomes (e.g., deaths) of two groups and adjusts for known baseline mortality differences (e.g., frailty or age).
The adjustment factor (e.g., 1.1496 for the 1950–54 cohort) reflects the pre-pandemic difference in expected death risk between the groups.
This is not arbitrary — it's grounded in publicly available demographic life tables.
The logic is simple: If one group had a 15% higher pre-COVID mortality, we should adjust our expectation accordingly when comparing COVID-era death rates.
In fact, failing to normalize for baseline ACM would be incorrect, as it would attribute to vaccination effects that are actually due to age structure or frailty.
🔍 Claim 4: "Steve ignores time-varying vaccination status and confounders."
Response: This is a more nuanced issue, but Fischer glosses over key distinctions.
Steve has explicitly stated when he uses fixed cohorts (e.g., vaccinated or unvaccinated as of Jan 2022) and understands the implications of doing so.
Yes, there is time-varying exposure, but that’s the whole point of fixed-cohort analysis: to avoid bias introduced by allowing people to move between groups (which is what creates immortal time bias in many VE studies).
Steve is also one of the few who repeatedly emphasizes frailty bias (HVE) and attempts to correct for it using external mortality tables and proportional hazards modeling. That’s more than most official studies do.
🧠 Final Verdict
Paul Fischer's criticism relies on a misunderstanding of inference, a mischaracterization of Steve's methodology, and a dogmatic view of statistical tools that ignores how inferential methods are routinely applied to full-population, time-series, or demographically structured data.
It is fair to critique any method's assumptions, including KCOR or prediction interval models. But dismissing them as “cardinal sins” without appreciating their valid contexts is not a rigorous argument — it's rhetorical posturing.
Would you like a formal rebuttal of his entire critique, line by line, in an article or PDF format?
What a great presentation of facts! Thank you for taking this matter on! We all benefit from your work and persistence for accountability on their part!
Have you communicated with Vinay Prasad, MD MPH and currently at the FDA….I think. Trump appointed him to something. Anyway he is a master at analyzing these studies. I wonder how he would view your concerns and your interpretation of the data. He seems very fair minded to me.
Oh shoot. I think he is playing it safe. He is always willing to criticize studies but he still won’t address yours. He is critical of the lack of safety fasts for children and young men. I heard him say not too long ago that the boosters are a “net negative” for children, boys, and young men. He said he believe the primary series saved the lives of some older people in the very beginning. But overall the vaccines are unimpressive. I bet they wait awhile while a non mRNA is developed. Then they can say it was because of vaccine hesitancy. But the hesitant still want the good testing!!!! I don’t think he worried about COVID19 as a disease that’s causing problems.
he always ignores everything I send him. I give up.
HHS will not do all cause mortality studies as they know what they will find. Aaby in africa found the DPT increased al cause mortality 10 fold.... do you think any agency captured by Pharma would ever do a study like the Aaby study... not a chance.
Trump is Compromised by Epstein. Obvious as day now.
Trump supports the covid shots because he has to.
Putting RFK in was a controlled burn, slow drip, Controlled opposition.
We should be done with hope. Gloves off time!
hi folks be sure to check out and read carefully a petition at citizengo.org.....who still wants control-no to global health tyranny withdraw from the international health regulations...be aware its a worldwide petition it can be signed and reshared widely worldwide from any country in the world including america.....as for resharing it be very aware that e mails cant be censored or suppressed fact but shh your not supposed to know that...so the plan is this first be sure to sign it and then be sure reshare it widely both there in america and overseas with all your like minded e mail contacts that is those whose e mail addresses that you have and can send e mails to and be sure to ask each one of them to do exactly the same as im asking you to do in this message
I don't understand a fair bit of the scientific terminology, but I certainly do understand the dangers of the mRNA covid shots. So, Mr. Kirsch, I am really grateful you are in this fight for truth. God bless you!
What is going on with RFK? Something smells bad. He knows the mRNA covid vaxxes are dangerously. He knows kiddie vaxxes cause serious injury to children. Why is he refusing to remove any of these vaxxes from the market?
because trump will fire him if he does and then where will he be?
There are powerful forces at work here, the vast billions $$$ that big pharma wields. So RFK removed the recommendation of the mRNA for youngsters and the elderly, and already he's being sued by "doctors" groups, shills for pharma. He added a warning of heart damage to the mRNA for young boys. I think the plan is to keep chipping away, until mRNA is finished for good, but a quick removal would cause bombshells to go off. RFK previously announced that all vaccines would be reviewed for safety and appointed a completely new vaccine review board. I think it's all coming together, but will take some time
But how long will that time take? It’s already been an insanely long time!!
When you consider RFK and others appointed by Trump, all that indicates the end of mRNA and even other toxic vaccines. Already thimerosal is banned from vaccines, a big step forward. Guess it's like peeling an onion, eventually it will be peeled
I truly appreciate your optimism, Duane. Sad to say, I'm losing mine...
When you notice comments on the clot shots in various social media sites, it's apparent that many if not the majority, are fully aware those shots do more damage than good, I'm thinking that as people refuse those shots, they'll die away from lack of sales. There's a preponderance of negative publicity of the shots these days, and we all need to keep this up too. I've talked to a few friends that had the shots, and they all got Covid anyway, they're not doing any more of those shots.
Yes. And the very recent attention drawn to the rubbery white, blood vessel-obstructing clots removed from both living and dead covid shot victims may move the needle since living victims survived to talk about it.
Embalmers around the world have reported this phenomenon.
Have you seen that growing story? (from Scandinavia, I believe)
Hard to believe the onion will be completely peeled when they keep approving new shots. RSV and Moderna Con-vid shots. What will be added next? They have many in the pipeline.
Malone says the new shot is a stinking pile of shit and he's working on it, I don't know how it was approved in the first place.