Some types of science are more malleable than others. Randomized trials, if honestly reported, can be impacted by the inputs: control arms, post protocol care, concealment or blinding issues, and drop outs, but otherwise are solid.
Cost effectiveness studies are a different animal entirely. There are dozens of assumptions that go into them, and they can bend in any direction. That’s why we found, “Having a study funded by a pharmaceutical company was associated with higher odds of a study concluding that a drug was cost-effective than studies without funding (odds ratio, 41.36; 95% CI, 11.86-262.23).”
40!!!
The CDC’s recent modeling exercise arguing that young people are better off with bivalent boosters is shown here. It is the most malleable design of all. And just like Pharma, the CDC is an untrustworthy analyst. They already made the policy. Now they need the analysis to validate them. Yet, sadly, their mistakes, lies and exaggerations having robbed them of credibility. Take a look at the Figure.
The first thing to say is that it is 0 myocarditis… so far. The booster will definitely have myocarditis. I bet it will close to 1 in 10k, the estimate Sharff had for the last booster. The CDC’s harms balance is dishonest.
The second thing to say is that the rate of hospitalization is incorrect. These rates assume the rates of Dec 2022 last forever— they won’t b/c natural immunity— and do not exclude incidental covid19 hospitalizations. Specifically:
That’s bad. Obviously this inflates the upside of vaccines. Elsewhere the authors provide a version of the slide that tries to correct for this, and halves the numbers, but the deeper problem is that the taxonomy of for vs with covid hospitalizations is underdeveloped, and even this correction is likely a distortion
Next, the authors assume the Vaccine Effectiveness from VISION study, which is a test neg case control. But using this design with low uptake— BTW no one wants this bivalent booster anyway— creates volatile estimates. The VE estimate is basically made up as well. It assumes equal presentation patterns for illness, which is likely untrue. A randomized trial of 100k kids would give accurate estimates.
(Side note: Ironically, the ridiculously large benefit the authors postulate means that the trial is very doable)
So what is wrong with the CDC’s analysis?
The harms side of ledger is inaccurate
The benefits side is overstated
The vaccine effectiveness is a volatile estimate
Basically everything is wrong, and the conclusion is the absolutely most optimistic scenario, which SURPRISE, SURPRISE confirms the political decision their boss already made.
Granting EUA to bivalent boosters for most adults was a huge mistake. It was an abdication of FDA’s duty and the CDC has failed Americans to push it. Without precise estimates of VE (which come from RCTs), honest projections of future hospitalizations, and honest tallies of myocarditis— the CDC continues to push dishonest propaganda.
Trust in public health has been shredded. Joe Rogan didn’t do it.
I keep thinking "At some point, the adults will have to step in and take over at CDC/FDA, right, RIGHT???" Sadly no. So for me, with every study they (CDC et al) put out, there's an inverse square relationship with trust. And I am FAR FAR FAR to the right of that drop off curve. I dare say we're in the territory of criminal negligence. But I also know that NOTHING will come of it. Not with every MSM being lapdogs for Dr. Fauci.
Maybe Trump will say "Take the bivalent booster, it's AWESOME...'scuse me, 'scuse me...its GREAT" Then, every MSM and Doctors will shout "DON'T TAKE THE BIVALENT BOOSTER"
It's laughable, but I bet it'll play out exactly as above. There is precedent with AAP after all.
Thank you so much Vinay. I got one for you:
https://www.cdc.gov/mmwr/volumes/70/wr/mm7044e1.htm
This is the one they did when all the schools and employers were mandating the vaccine so that people with natural immunity from prior infection couldn’t get an exemption. Their science is so incredibly bad that a normal person with average intelligence (me) can read it and find the flaws. For reals. I’ll show you.
To start, the study design is absurd. The cohort is: all hospitalized patients with respiratory symptoms. Notice I didn’t say, ‘hospitalized patients with CoVid like symptoms’ because that could trick you into believing they did an actual study of vaxxed vs non vaxxed patients hospitalized with CoVid. No. They did a study which identified two groups: patients hospitalized with any respiratory virus who were CoVid vaccinated with no prior CoVid infection and patients hospitalized with any respiratory virus who were not vaccinated and had prior CoVid. Then they asked the question: in which group is there a higher PERCENTAGE of CoVid positive patients?
Well what good does that do us? We’re trying to stay out of the hospital here and not die of ANY respiratory virus. What we want to know is how many vaxxed vs unvaxxed are ending up in the hospital?
So if that’s your goal, you can look on the charts to get your answer. Similar results across all the subcategories but here’s Delta:
Total vaccinated with any virus: 5,213
Total unvaccinated with any virus: 189
Total vaccinated who had CoVid: 306
Total unvaccinated who had CoVid: 19
MmmmK🤔. So how do they conclude you should get vaccinated ASAP??? Because 306 is only 5.9% of 5,213 while 19 is 10% of 189. 10% is much higher than 5.9%, see. Duh.
If we’re going to look at ratios, fuck. Look at which group is ending up hospitalized at a higher rate. I am not a scientist however, I do own a calculator:
5,213 vaccinated patients is 96.5% of all patients hospitalized with a respiratory virus during Delta.
The CoVid vaccine caused people to end up hospitalized with both Delta and other respiratory viruses at a much higher rate than non vaxxed with prior infection. Shouldn’t that have been the title?
I would so love it if you, an actual Doctor, would look at this study and give it a rake through. Is it really possible this is still published and has not garnished widespread criticism?