Discover more from bad cattitude
new data on vaccine efficacy from scotland and more evidence on bayesian datacrime
and more bad news for "the experts"
it’s becoming a bit like beating a dead horse to keep highlighting more and more data that shows the failure of the vaccines to act as promised, but this one highlights something else i was discussing recently and provides a tangible example of the math and definitional manipulation that’s going on.
so let’s take a quick spin:
(all data from HERE)
as is becoming endlessly apparent and replicable, “unvaxxed” is outperforming every other category.
vaccines are not stopping spread, they are most likely (subject to the limitations of non randomized society scale data) accelerating it.
addendum i should have made clear:
this data is all age adjusted by the scottish health authorities to remove age based health and vaxx issues.
this becomes readily apparent when we calculate risk ratios. (incidence of group divided by incidence in unvaxxed control, so any number >1 = more risk)
risk in the double vaxxed is well over twice as high as in the unvaxxed. boosters seem to help, but still cannot get you back to baseline and i want to emphasize the word “seem” here because i think this data is misleading and is vastly overstating booster efficacy and likely making double vaxxed look worse than it is. (more in a minute)
we can also look at hospitalization:
what’s most interesting here is that it seems like there was some vaccine efficacy against hospitalization but that it inverted as 2022 began.
we can see the risk ratio on 2 doses rise sharply from 0.76 (24% VE) to 1.39 (-39% VE). this is an 82% jump in risk ratio and it was durable into the following week. i have emphasized this in red.
boosters seem effective (but there’s that word again) but even this seeming efficacy is rapidly dropping and risk ratio is up from 0.15 in week 3 dec to 0.38 in week 2 jan, a 150% change.
i see 2 likely explanations here and they are not mutually exclusive:
this is omicron, the OAS/vaccine evading variant showing up and taking over. as it does, vaccine efficacy drops like a rock because you are antigenically imprinted for the wrong spike proteins. what had been a help becomes actual harm because a bad response is worse for you than making one up on the fly and omicron is the optimized output of selection by leaky vaccine for vaccine evasion and superspread. we’re now into OAS territory, just as certain gatos told you we would be…
this is bad math and bad definitions being used to hide properties of these vaccines and shift risk. defining as “3 doses” those only those 2 weeks after their 3rd jab is bayesian datacrime, especially when the jab itself is known to cause ~2 weeks of immunosuppression and higher risk.
the jab itself generates a high risk cohort but then attributes that risk to the cohort before it. it’s like blaming getting hit by a car crossing the street on having stayed on the sidewalk, and the effects can be gigantic. you can hide ANYTHING in that. it’s bad definitions leading to bad math and it’s been widespread practice since pfizer ginned it up to slant their trials.
you can get a full walk through on this issue and the various forms in which is can manifest here:
the bottom line is that this is literally a card sharp palming a bad card out of his hand and dropping it into yours. lumping this 2 week risk period into the group that did not get the most recent round of vaxxes is an absurd risk shifter. it will always make whatever the new round of vaccines is look like it’s working.
the examples linked about lay it out clearly: you can make a zero efficacy vaxx look like it works and this works even better if it causes a rise in risk in the 2 week period you lump into the prior group.
thus, boosters make “full vaxxed” look bad. fully vaxxed made unvaxxed look bad. so much of what has been claimed to be vaccine efficacy is just a mathematic rig job from poorly chosen definitions and there is simply no way that that was an accident.
pfizer does not make mistakes like that or like vaxxing the whole control group right when vaxx fade started to get bad. they make choices and those choices have been aided and abetted by regulators and public health agencies.
they all signed off on and adopted these misleading definitions and have been providing information and making policy based upon them.
i’m willing to believe that the CDC was too inept to spot this. it’s sad, but it’s plausible.
but the NIH should have seen it and the FDA not only should have spotted it instantly but should have disallowed a trial using such a shady tactic. it’s pure manipulation.
they both let it go because they were both involved. NIH licensed the IP for the vaccine payload to moderna. former FDA head gottlieb stepped down mid-term to join the pfizer board of directors.
this is what full blown regulatory capture looks like and big pharma companies have the kinds of ethics that would make a DRC cobalt miner using child soldiers blush.
if you doubt that, read this:
pfizer is just about if not the most fined and sued pharma company in the world for a reason and the reason is “their behavior.”
this cattle vaccine (PregSure BVD) was causing massive, wholesale death in calves that nursed from mothers that got it. the inoculant was given over and over as regular doses. the problems emerged, the data was clear, and pfizer fought it all. they lied and denied and most of all kept selling and marketing the vaccine. they claimed the side effects were overstated and unlinked.
calves were literally bleeding out through their eyes. it destroyed their bone marrow. it was killing 15% of the junior moo team at some farms. this was not “long ago.” this was 2006. no one pulled it until 2010.
pfizer denies the issues to this day.
the head of the animal division that did this was albert bourla.
albert is currently the CEO of pfizer.
draw your own conclusions about their priorities from that…