17 Comments

Would it be fair to say that "the z-scores support the generalizability of all past Trust covid analyses"?

Also guessing that the asymptomatic anomaly could be due to testing rates? Though we have already concluded there is no way to test that. It has slipped my mind what have been the best predictors of symptomatic covid from past articles.

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That's a rather neat way of putting it! Back in spring 2020 PCR tests were not readily available so quite how they classified cases is questionable. What gets coded in the EPR is not down to physicians alone - three clinical coders have confided that they were asked to code for COVID regardless of what SHOs had scribbled on casenotes - we're talking contractual desire rather than clinical reality.

My model for symptomatic COVID (published in part 11 of Do COVID vaccines work?) was pretty dire owing to lack of cases (only 224 such cases in my sample of 5,366 in-hospital deaths). Number of diagnoses, CDR, age and vaccination status made a showing but I'm not convinced it's worth much.

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Maybe could do some comparing of z-scores with infection/case fatality rates in and out of Trust?

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That would be lovely - I'll put it in my big black book of analyses to run.

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Low testing availability is a ruse. What I now realize more than ever (thanks to collaborating with associates in PANDA, since the group was kind enough to include me in their ranks) is that the mythologies/propaganda in countries that participated in Operation COVID-19 were the same. Govt officials have lied about every single thing-- and are still doing so. Keep that in mind when you look/think back to those narratives. My rule of thumb these days is, "If govt/media was saying x in spring 2020, the opposite or near-opposite was true."

Hospitals were testing and had what they needed into order for officials to create the appearance of sudden spread of a novel deadly CV.

Continue to look at place/setting of death, as you're doing, and in a time series format-- and you will start to see.

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How do these data compare with Euromomo data?

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A good question - I haven't had a look at Euromomo for some time. Hopefully an enthusiastic reader will enlighten us.

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Here's how they did that:

1. Test everyone already in the hospital

2. Push forward/reclassify some deaths that had occurred in earlier weeks/months but had not yet been fully processed and/or were being held back.

"Coordinated response"

See how easy that is?

Very, very easy.

Something you need, if you can get it, is daily occupancy for all NHS hospitals (even better would be London only).

New York's data is (intentionally) incomplete - and I suspect the front end numbers are "pushed" from the left (so to speak). Nevertheless, the claim is occupancy peaked at 20K and that nearly that many inpatients died in the same period. https://www.woodhouse76.com/p/wait-did-this-really-happen-in-new

That makes NO sense.

Would like to see what ONS/NHS data claim.

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Nice work as usual. The data chain was fucked from the start due to the anomalous choice of case definition requiring only a positive test and no symptoms. And then the choice to test everyone regardless of symptoms led to the predictable massive rate of false positives that results from any screening with low prevalence of the disease in question. And then the definition of “covid hospitalization “ and “covid death,” that you also point out were tied simply to a positive test result, completed the corruption of the data chain. The end result was a truly massive cluster fuck of iatrogenic deaths, particularly in the elderly and care homes, and an even more massive exaggeration of the harm from the virus itself. We estimate that 90% or more of the harm attributed to the virus was from other causes.

https://tamhunt.medium.com/how-covid-19-stats-are-grossly-exaggerated-a-brief-summary-of-the-arguments-53a5b4237c4c

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What is the ratio of symto vs assympto in the first wave? If you apply that to the official total of COVID deaths, that will actually tell us how many were actually non COVID. Looks to me like it's roughly half and half, maybe more non-COVID? That alone ought to be reason enough to condemn the Government response?

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Looks like I need to write parts 3 & 4 with all these great ideas popping out!

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I commenced my not particularly distinguished NHS Management career as a naïve postgraduate trainee, and my first assigned task was to count hospital beds at the ancient and venerable Chester Royal Infirmary. I swiftly learned that this was impossible, because there are multiple definitions of beds, including a stack of old ones in the basement that are scrap metal, the 30 TB beds in Ward VII that are unstaffed as nobody needs them, there is no working lift access, and the ward is infested by mice, and those ghastly tin trolleys in A&E. .

If I don't believe any NHS stats, it is in part because my sorry task was to make them up as best I could to please my masters - right up to and including answering PQs (Parliamentary Questions) ;-)

PS: I don't think - on the balance of probability - that Nurse Lucy Letby killed any babies in Chester, either, so I am clearly a hopeless nut-job) ...

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All of the above. Those regular meetings I had with the head of IM&T and clinical coding were rather interesting. They were uneasy with my managing of separate data systems that gave different answers. It is telling that legal always came to my department when they had to get it right.

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That's where the Sir Humphreys of this world are past masters of the dark and possibly dying art of circumlocution: they can always find weaselly ways of saying that "actually, nobody has a clue"! , whilst sounding deeply sincere and authoritative.

And of course Covid was doomed from the start by the abuse of the English language, not least the extraordinary re-definitions of words such as 'Pandemic' and 'Vaccination', and the utterly bizarre concept of asymptomatic infections.

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Quite! I was a master of hand waving, hence rapid promotion in the service of Her late Majesty as a suit of the realm.

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