Social GoldenWolf's COVID Vaccine/Lockdown Protest megathread

[Rob Battisti]

@Greco_Wiz

Also, what you’re doing — whether you know it or not — is arguing for a targeted vaccination campaign. Of which, I’d be supportive of. It only should have been for the at risk populations. So I agree with you. Thanks for proving my point so eloquently.

 

[Greco_Wiz]

Multiple. When you take a population of 100,000 and take all the 60-69 year olds — whatever confounders you think are there, disappear. Youre conflating imaginary ailments or conditions which is messing with the outcomes. It’s not.

Im not comparing the morbidly obese against the fit. I’m not comparing the diabetic against the non-diabetic. I’m looking at everyone aged 60-69 who was either in a control population or had been vaccinated. If you can’t see that as useful data, well — that’s likely the end of this discussion.

And bringing up relative risk again just shows your biases as well.

You have a gross misunderstanding of data and statistics. You’re talking about random sampling. That’s not what we’re doing. ThIS is a perfect example of how misinformation happens. You see a graph on Twitter and don’t understand it’s limitations. This is why science uses inferential statistics to generate conclusions. Larger sample sizes will make the differences in confounders between the groups more significant, not less.

Still haven’t figured out the difference between relative and absolute reduction?

 

[Greco_Wiz]

@Greco_Wiz

Also, what you’re doing — whether you know it or not — is arguing for a targeted vaccination campaign. Of which, I’d be supportive of. It only should have been for the at risk populations. So I agree with you. Thanks for proving my point so eloquently.

Some benefit more than others from vaccination. Ok great.

 

[Sano]

@Sano

The second one from Canada isn't stratified by age which could muddle the numbers. I'd like to look at the raw data. There's so many variables to consider.

The second one from the UK, I am looking at the raw data for age-stratified covid related deaths in 2022 april and may and not seeing the same thing: https://www.ons.gov.uk/peoplepopula...ths/datasets/deathsbyvaccinationstatusengland

For age-stratified data. In April 2022, deaths out of 100.000 who had covid was 95.5 for vaccinated and 204.7 for unvaccinated. In May 2022 it was 35.5 for vaccinated and 77.6 for unvaccinated. So the vaccination correlated with about half, or 50% less deaths. It's two months though at this time with very low deaths, immunity waning and the newer variant. If we go back to previous months during winter the difference is way larger. Taking a look at December 2021 for example. There the death rate was 520.5 for unvaccinated and 56.3 for vaccinated, meaning the vaccination correlated with 90% less chance of dying.

You can download the excel and look at rates (deaths per 100.000) for covid related deaths in table 1 if you can be arsed.

TLDR: The numbers on the UK chart doesn't add up when looking at the data. As far as I can tell the vaccine was 90% "effective" in December and 50% "effective" in May and April.

@Greco_Wiz

Also, what you’re doing — whether you know it or not — is arguing for a targeted vaccination campaign. Of which, I’d be supportive of. It only should have been for the at risk populations. So I agree with you. Thanks for proving my point so eloquently.

At least I think it's fair to say that the vaccine was much more necessary for the elderly than younger people, if looking only at the individual level.

 

[Rob Battisti]

You have a gross misunderstanding of data and statistics. You’re talking about random sampling. That’s not what we’re doing. ThIS is a perfect example of how misinformation happens. You see a graph on Twitter and don’t understand it’s limitations. This is why science uses inferential statistics to generate conclusions. Larger sample sizes will make the differences in confounders between the groups more significant, not less.

Still haven’t figured out the difference between relative and absolute reduction?

Oh I absolutely know the difference and how they can be used to misconstrue their impact. Now a random sampling is a bad measure of how a population gains benefits from a vaccine?

 

[MoparOrNoCar]

If an unvaccinated person dies while hospitalized and has multiple comorbidities as well as covid, you know they're going to count the official cause of death as a covid death.

If a vaccinated person dies while hospitalized and has multiple comorbidities as well as covid, you know they're going to count the official cause of death as one of the other comorbidities because they are going to assume that covid had no effect on their death because of their vaccination status.....even though that vaccination probably happened 5 variations ago and is useless at the time of death.

The numbers have been skewed since day 1 in favor of fear and big pharma profits.

 

[Greco_Wiz]

Oh I absolutely know the difference and how they can be used to misconstrue their impact. Now a random sampling is a bad measure of how a population gains benefits from a vaccine?

You were trying to suggest differences in important confounders between vaccinated and unvaccinated populations go away with larger sample sizes. That is simply untrue.

If on average, someone who has cancer, or is obese, or has atherosclerosis, or diabetes, is more likely to get vaccinated, that means the vaccinated population will have higher rates of those individuals relative an unvaccinated population. That does not go away with higher sample size because they are independently associated with vaccination.

Here’s an example. Smoking cigarettes is associated with drinking alcohol. If I’m interested in how smoking affects some aspect of health, do you think comparing 1 million smokers to 1 million non smokers suddenly means alcohol consumption won’t differ between groups? Did the larger sample size magically make the difference in the alcohol covariate disappear?

 

[Greco_Wiz]

Oh I absolutely know the difference and how they can be used to misconstrue their impact.

Can you point to an example of when relative reduction was misused regarding C19 vaccine effectiveness, and when absolute reduction should have been used instead?

 

[Rob Battisti]

You were trying to suggest differences in important confounders between vaccinated and unvaccinated populations go away with larger sample sizes. That is simply untrue.

If on average, someone who has cancer, or is obese, or has atherosclerosis, or diabetes, is more likely to get vaccinated, that means the vaccinated population will have higher rates of those individuals relative an unvaccinated population. That does not go away with higher sample size because they are independently associated with vaccination.

Here’s an example. Smoking cigarettes is associated with drinking alcohol. If I’m interested in how smoking affects some aspect of health, do you think comparing 1 million smokers to 1 million non smokers suddenly means alcohol consumption won’t differ between groups? Did the larger sample size magically make the difference in the alcohol covariate disappear?

Once again, if this was the tactic of the response to the vaccination roll out, you would have had my support. For the general population, being vaccinated seems to provide no benefit against death.

 

[chardog]

Everyone is catching... Even the former Fauci fanatics in Blue States.

well, to be fair, you could be right, you could be wrong, you're going to get booed regardless if you're an insufferable cunt

 

[Rob Battisti]

Can you point to an example of when relative reduction was misused regarding C19 vaccine effectiveness, and when absolute reduction should have been used instead?

Should have been used simultaneously and by comorbidity.

 

[GoldenWolf87]

Should have been used simultaneously and by comorbidity.

That video was interesting thank you.

 

[Greco_Wiz]

Should have been used simultaneously and by comorbidity.

The early clinical trial data (where the first 95% effectiveness value came from) should absolutely not have been presented as an absolute reduction estimate. Unlike something like cancer or heart disease, with C19 the risk of the event is changing radically across time. It is not at some predicable background rate. This was especially true early in the pandemic with exponential infections. If that 95% estimate came from a window of time early in the pandemic, say over 3 months when only 1% of people had been infected, by definition the AR would have to be < 1%. That’s of no use when 12 months later, 10 times more people had been exposed.

 

[Rob Battisti]

The early clinical trial data (where the first 95% effectiveness value came from) should absolutely not have been presented as an absolute reduction estimate. Unlike something like cancer or heart disease, with C19 the risk of the event is changing radically across time. It is not at some predicable background rate. This was especially true early in the pandemic with exponential infections. If that 95% estimate came from a window of time early in the pandemic, say over 3 months when only 1% of people had been infected, by definition the AR would have to be < 1%. That’s of no use when 12 months later, 10 times more people had been exposed.

Which is why everyone was touting “100% effective” the beginning and everyone was then duped by the talking points.

Also, you realize that you can still take sample sizes and make predictive models, right?

 

[PhitePhan]

Should have been used simultaneously and by comorbidity.

Yep, “lies, damn lies, and statistics.”

 

[Greco_Wiz]

Which is why everyone was touting “100% effective” the beginning and everyone was then duped by the talking points.

Also, you realize that you can still take sample sizes and make predictive models, right?

There was no reason to believe that virus would stop spreading. The 95% estimate would have been misleading if you had reason to believe only a small portion of the population would end up infected. I don’t think anyone believed that to be the case.

I’m not sure what you’re trying to get at with your predictive models statement. Of course we can. How is that relevant to AR? Should we have presented the data as RR and a hypothetical “if 50% of the population gets infected in the next year” AR value? Not how it’s done, but you see how that works against your argument, not for it, right? You’re saying the current AR is misleading so we should calculate one for the future where it would be higher. Not helping your case.

 

[mon]

https://childrenshealthdefense.org/...tent&eId=b403e33a-6002-4da3-8319-2da60d6d9dbf

"Did Pfizer, Moderna Skip Animal Trials? Fact-Checking the Fact-Checkers"


For a good fucking call good old rooters, sounds like there have been some checks involved thats for sure....

"False claims that COVID-19 vaccine producers skipped animal trials due to the animals dying have resurfaced online. Pfizer-BioNTech, Moderna and Johnson & Johnson conducted these trials and had no significant safety concerns to report https://reut.rs/3vGFQih"

Stated pretty clearly one would think, yet.

"Reuters admitted animal trials were not completed prior to initiating human trials “due to time constraints and the urgency to find a vaccine for COVID-19"



You wouldn't think it was able to but it gets worse.


"The fact that COVID-19 vaccine animal trials were done at the same time as human trials “doesn’t make anybody who has that feeling feel any better,” she said."


And than it gets much fucking worse.


"We now don’t know the long-term side effects in animals’ because animals were euthanized within 7 days"


To the retarded

"Full Fact’s April 2021 fact check also stated that animal tests were done and the animals — in this case, mice — did die, but the deaths weren’t caused by the vaccine."

Fraud and manipulation every where and on all levels of this trial.

"The mice died because they were euthanized seven days after being injected with the vaccine, as is “standard procedure in this sort of trial.”

https://www.jax.org/news-and-insights/jax-blog/2017/november/when-are-mice-considered-old
"Mice ranging from 18 - 24 months of age correlate with humans ranging from 56 - 69 years of age. This age range meets the definition of “old,”"


This should be fucking obvious to even the dimest.
7 days on an under exaggerated life span to make it easy. 2 years, so 104 weeks or 728 days.
0.962% of the rodents life span was observed following the injections, seriously theres people that can't see the problem!


1 So we ran animal testing at the same time as human because we deemed a failed for 25years tech safe.

2 Studied for damage less than 1% of the animals lifespan after injection and than we destroyed the animals.
(If we had a criminal habitual offender or indications of fraud one might wonder if there was something nefarious going on like safety signals showing that may have indicated failure)

3 why bother going through all the red flags, you either understand behaviour and expression of self or you dont.


As I said sweating bullets if I was stuck with that crap because I'm starting to sweat not being stuck

 

[lifelessheap]

There was no reason to believe that virus would stop spreading. The 95% estimate would have been misleading if you had reason to believe only a small portion of the population would end up infected. I don’t think anyone believed that to be the case.

I’m not sure what you’re trying to get at with your predictive models statement. Of course we can. How is that relevant to AR? Should we have presented the data as RR and a hypothetical “if 50% of the population gets infected in the next year” AR value? Not how it’s done, but you see how that works against your argument, not for it, right? You’re saying the current AR is misleading so we should calculate one for the future where it would be higher. Not helping your case.

No reason to believe the virus would stop spreading?



The President lied.




Media lied.



Fauci lied.

 

[lifelessheap]

By the way, all the videos from media pundits saying the shots STOP the spread are now hidden by Alphabet. They try to rewrite history and pretend that they all weren't in on the lie.

 

[mon]

https://nakedemperor.substack.com/p/bmj-opinion-from-former-editor-time/comments

BMJ Opinion from former Editor - Time to assume that health research is fraudulent until proven otherwise?

"Richard Smith, editor of the British Medical Journal (BMJ) until 2004"

"Time to assume that health research is fraudulent until proven otherwise?

Health research is based on trust. Health professionals and journal editors reading the results of a clinical trial assume that the trial happened and that the results were honestly reported. But about 20% of the time, said Ben Mol, professor of obstetrics and gynaecology at Monash Health, they would be wrong. As I’ve been concerned about research fraud for 40 years, I wasn’t that surprised as many would be by this figure, but it led me to think that the time may have come to stop assuming that research actually happened and is honestly reported, and assume that the research is fraudulent until there is some evidence to support it having happened and been honestly reported"ed




Its not like they're putting much effort into the fraud either. Have a think about it, literally add up in your heads all the whistle blowers, obvious lies and bullshit with the covid jabs.
Probably cheaper to buy a few civil servants and politicians than to run an actual trial, no risk of money down the drain either.


I'm still literally lol at the safer than placebo, yet the german SSausage has said one serious adverse reaction every 5000 doses. Wtaf, and there are still geese honking ligitimate (on sherdog and irl) un fucking believable.




"Ian Roberts, professor of epidemiology at the London School of Hygiene & Tropical Medicine, began to have doubts about the honest reporting of trials after a colleague asked if he knew that his systematic review showing the mannitol halved death from head injury was based on trials that had never happened. He didn’t, but he set about investigating the trials and confirmed that they hadn’t ever happened. They all had a lead author who purported to come from an institution that didn’t exist and who killed himself a few years later. The trials were all published in prestigious neurosurgery journals and had multiple co-authors"



Got a suspicious feeling there will be a few more mysterious deaths as the dead wood with liability attached are cut free.