CDC reports of historical covid deaths drop by 70k to correct "coding error"

this data is still badly wrong, but i have some real concerns about who we are allowing to "fix" it and how unsupervised they will be as they do so

of all the insanity around covid that took what would literally have been a baddish flu year would have passed with little comment or historical import and turned it into a mass hallucination of apocalypse, defining “covid death” as a death not “from covid as a proximate cause” but rather as “death from any cause if you had had a positive PCR test for covid in the previous 28-30 days” carries a special pride of place.

many of us stood up and screamed about this right from the beginning.

it made zero sense. nothing else is counted this way (for a reason) and the confluence of doing so with the staggeringly unprecedented mass testing of healthy people with overclocked PCR tests run at a 40 or higher Ct that was so over-amplified that it lacked any clinical relevance whatsoever and was probably kicking out 70-90% rates of non-clinical positivity was madness.

once this disastrous definition was put in place, apocalypse was assured.

but “the experts” ran with it, defended it, and treated as unarguable truth that “800k+ americans died from covid.” but they didn’t. it was not even close.

and now that the panic they drove has ended and further deaths are “inconvenient” they are starting to walk it back over what they claim was a “coding error.”

Nicole Saphier, MD @NBSaphierMD

** Correction with updated numbers. The CDC may have removed closer to 70k deaths. Difficult to tell exacts as prior data has been removed.

these charts are telling.

the one on the left is from BEFORE the one on the right.

historical deaths dropped 72k.

huh.

it’s a start, but this is still a glaring, whopping overstatement.

now do “died from, not merely in proximity to a positive PCR sample for” covid and let’s see what happens.

my bet is that you drop the count by another ~70%.

here’s some fun math:

the average person probably has (to be conservative) 2 episodes a year in which they would, at a 40 Ct, test positive for the common cold. this does not mean you were sick, felt sick, were contagious, or any of that. it just means “you had enough viral genetic material in your mucus that someone using 1 trillion X amplification on it before looking for it could find it.”

let’s say these periods last 3 days and if you die in the 28 days following, this gets called a “common cold death” just as we did for covid.

this gives you something on the order of 62 days a year when getting hit by a car would still get counted as “cold death” just as in covid.

that’s ~17% of the year. (and these times will tend to overlap with peak winter seasons when more people die anyhow, but let’s ignore that.)

• about 2.9 million people die in the US annually.

• 17% of 2.9 million is 493,000.

starting to see the problem?

adjust this for higher rates of positive viral tests for the old and infirm who are also more likely to die and this really blows out.

• 53% of US covid deaths were in the 6.9% of population over 75 years old and 75% were in over 65s’.

• only about 8% of deaths were in the 39% of the population under 30.

the number of people who “tested positive for covid” was likely overstated by 70-90% when considering who had actual clinical covid and was sick/contagious.

even the NYT figured this out.

and yet the folks at CDC have not, until recently, even tried to address this. this will have had a proportional effect on reported “covid deaths.”

and now they are seeking to erase them and claiming “coding.”

and i do not trust this one whit.

the CDC have not been straight with us from the beginning and have been pushing definitions they knew to be wrong and studies on interventions, especially masking, that were clear, undeniable fraud.

and i fear we are in for more of the same because the CDC are completely, hopelessly politicized and compromised and their federal paymasters need to ensure that 2 things happen:

1. that non-pharmaceutical interventions look like they worked

2. that the vaccines they pushed so hard and got so wrong worked

and neither is true.

but i doubt that they will let that stop them. i have spoken many times about how the epidemiology grift is just the climate grift played at 50X fast forward.

many of the tactics and praxis of running and manipulating the scare to grab for cash, prominence and power have been the same and i expect this to remain so. it’s the same playbook.

so let me show you a trick play that has been all too common in climate and that i suspect we’re about to see run here:

when the data goes against you, change the data.

in climate, this has gone on for decades. they literally go back and change the past, cooling the warm periods of the 1930’s and adjusting current temperatures up. bingo, bango, instant warming trend and “unprecedented highs.”

this wonderful gif from steven goddard makes the process clear. and this was LONG before the east anglia “climategate” scandal and the 100 other times they have been caught adulterating data. it’s rife to the point that you pretty much cannot trust anything in the space. i found this so hard to believe i actually once went and checked the paper records myself to comp them to those in the databases. it’s true. they literally inverted the slope of the curve from the 1930’s to 2000 by fiddling the data.

and if you think they will not play this game on covid, i must sincerely ask you: “what movie have you been watching for the last 2 years?”

the fix is about to be in. “adjustments” are going to be applied selectively to make masks look like they worked and vaccines look like they reduced overall societal hospitalization and deaths from covid.

the US data is about to be turned into propaganda.

will this spread globally? who knows? it certainly did in climate. i don’t think this crowd is any nobler and the incentives are the same.

anybody need to buy a vowel here?

the same people who overstated this situation so aggressively are going to be the ones “fixing” the data to make sure it’s correct.

the same people who pushed and mandated draconian responses that have failed so spectacularly are going to be the ones “adjusting” the data that allows us to assess those outcomes.

we’re already caught them lying who knows how many times.

it is not a conspiracy theory to expect them to lie again.

it is a conspiracy theory to claim they’ll be honest this time.

i recommend grabbing all the data you can now and storing it. the presumption it will be available in unaltered form in the future may not be a good one.

honestly, tracking the changes to the dataset may be the only way to see if the CDC is playing it straight and they look to be disappearing past references already.

this is probably a worthwhile project for some of the datahawks.