I'm going to explain why this chart is so important and why @jsm2334 is being disingenuous by ignoring it - whilst making points that undermine the "real world vaccine data" industry.
It's a Kaplan-Meier curve and it obliterates Jeffrey's argument.
Just to go over it... the lines show what proportion of subjects (children) ended up without chronic disease up to 10 years after being studied.
It's called a survival analysis because it's used for cancer survival.
If the red line was a cancer drug it would be a blockbuster
It shows that by the end of the 10 year follow-up, of those that they could still follow up (who stayed in the study) 57% (100-43%) of vaccinated kids had chronic disease (e.g. asthma) and 17% (100-83%) of unvaccinated kids did.
A huge difference not explainable by chance.
Jeffrey Morris ignored this chart because he didn't want to accept that this is EXACTLY the type of analysis that pharma companies provide for cancer drugs and vaccines.
Here's a bunch of examples.
The numbers of subjects remaining are usually posted underneath.
Here's a good one. @DrPatSoonShiong's "wonder drug" Abraxane.
Not only does it have a miniscule benefit in this chart but just check out the numbers remaining after 24 months.
Single figures. At 2 years.
Yet "low numbers" is exactly what Jeffrey Morris is complaining about for the follow-up in the Zervos study posted by @AaronSiriSG
How many people were included in the unvaccinated arm in this study at 2 years, or even 5 years?
Let's see.
We can estimate this in exactly the same way that Jeffrey Morris did.
In fact I totally agree with this chart.
That chart is based on the median and IQR points published in the study, and to make the curves you have to fit an exponential model to represent the numbers dropping out of the study.
We get this..
Big numbers in the vaccinated but still over 200 unvaccinated at year 5
And this is what that looks like visually with estimated numbers of incidents per year:
You can even get ChatGPT to draw these graphs for you if you know what to ask for:
(note the different scales)
What you can't do - if you let ChatGPT do all your thinking for you - is split your tweets to stay in length, which is presumably why Jeffrey Morris's thread started with an AI-like monologue.
Here are the estimated figures reverse engineered from the Zervos study
@seckennedy
And the table gives you an idea of the numbers in each year that were lost to follow-up (censored) and how many were affected (got chronic disease).
There is no "sudden jump" at year 5+ when the kids went to school. That was a junk excuse.
Also note that the numbers underneath are the proportion unaffected instead of the more standard "subjected remaining at risk". But it's not a crime because we can estimate the figures from those provided.
And with our figures you can check against each year as a sanity check to see if they fit the findings of a significant difference between the groups
e.g. year 5 (OR=0.18, p<0.001) - they do.
The low p-value tells you there are enough numbers.
Which...
Is exactly what @AaronSiriSG claimed and Jeffrey Morris attempted to refute.
But dug himself a hole writing an article for the pharma-funded @ConversationUS that failed to mention the K-M plot once (destroying any claim to neutrality).
And just to top this off...
by highlighting the "small numbers in a survival analysis" problem Jeffrey Morris has literally shone a spotlight on the whole field of oncology drug trials.
Better get some bigger trials, pharma.
Jeff says your 6-patient studies are junk.
@MaryanneDemasi @stkirsch @DravenS17 @TonyNikolic10 @RetsefL @joshg99 @Kevin_McKernan @canceledmouse @franklin_reeder @naomirwolf @AGHuff @RefugeOfSinner5 @ClareCraigPath @craigkellyAFEE @threader_app Addendum: For those who can't see the study link in the original posts
Recently released Australian Road Deaths data confirm that the @epiphare study claiming that COVID vaccination reduced road deaths by 32% was, as suspected, a complete fake.
Here are the actual road deaths data plotted from the Australian BITRE data repository using a trendline for 2000-2019 (excluding 2020 as it was a quiet year)
The pink area shows the inflection and increase in road deaths over the predicted number.
Note that road deaths have a downward trend despite an increase in population (due to safety measures and slowing of traffic).
So the question becomes...
"what is the probability that - if the @epiphare study was real (showing a 32% reduction in road deaths after vaccination) - the Australian road deaths (where nearly 100% of the adult population was vaccinated) would increase by 36%"?
Debbie's tweet was about her case against @HHSGov when her son developed Type 1 Diabetes after a routine vaccine, when he had a negative glucose test prior.
So it was clearly vaccine linked, but her case was denied.
Not only was the case denied (despite clear evidence of a new diagnosis immediately after vaccination) but the case was used by the "judge" to essentially ban ANY further cases that alleged a link between new diabetes and a routine vaccine.
I'll say it again. The vaccine industry [KNOWINGLY] hijacked cell pathways that cause cancer in order to induce antibody responses so that they can claim that their product "worked" by demonstrating those antibodies - even if they offered zero protection.
To explain, when you induce an immune response you have an immune debt to pay. You can't just keep creating an immune response - or, as in the case of cancer, you will die.
A vaccine creates an artificial immune response...
Which might be fine if it was done every now and again. But what they didn't tell you was that the human body will not respond to an injected antigen alone. It will ignore it (thankfully) and the generic immune system will mop it up, no antibodies required.
Just putting this into context. @DrCatharineY was originally DOD then published on a DARPA grant. One of her few co-authors is Stephanie Petzing of the "Center for Global Health Engagement"
All one big OneHealth family to nudge you into believing this @epiphare slop is real.
For the explanation as to why these "real world data" with "data not available" publications are absolutely junk and shouldn't be accepted to any major journal please see arkmedic.info/p/pharma-hell-…
Dr Young (DARPA/DOD) is clearly now working as an ambassador to cover for the actions of the corrupt Biden regime who we are learning covered up huge amounts of adverse events from their COVID program whilst funding pharma in the "cancer moonshot"
It looks like we found our vector.
They moved from spraying live (cloned) viruses to putting them in drinking water.. which we thought wasn't possible due to chlorine.
Well, it turns out that it is, if you use a stabiliser.
The @NIH told us that they stopped funding GOFROC research but they clearly didn't.
This is a modified live virus. That is, they took a pathogenic influenza and genetically modified it and propagated it using infectious clones (reverse genetics). nature.com/articles/s4154…
"MLVs were diluted in distilled water containing Vac-Pac Plus (Best Veterinary 418 Solutions, Columbus, GA, USA) to neutralize residual chlorine and adjust the pH"