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I get the lack of data argument.
I agree that argument A can only be said to be supported by data if Not A would imply a different result.

But there is still a lot wrong with how the original claim has been denied.
Most recent count is that UK has 21,787 patients in Hospital beds with Covid.
There are 112,000 doctors and 312,000 qualified nurses in the NHS (out of about 1 million total staff).There is no shortage of Doctors or nurses for Covid. What exists is a determination to continue to treat other patients rather than re-assign them to Covid patients. And that is because Covid is a limited problem which takes up only a small fraction of NHS time. The original claim is valid.

Actually it is Covid lockdown practices that really use up NHS capabilities, as every face to face treatment now takes up to 3X what it used to, so vastly reduced services are available while something like 20% of the NHS is devoted to Covid patients. Last number I could find was 140k hospital beds in UK

MD: It's useful to think about what other paths lead in or out of your train of argument. For example, if there were indeed a crowding out of beds for other patients, then the vast expansion of bed capacity via these Nightingale hospitals should have dealt with that. You'd simply move the covid patients into these facilities and let the non-covid patients be treated in the usual wards. So, can I now argue that the removal of the extra beds is evidence that other patients have not been crowded out?

This illustrates a huge difference between computation and statistical inference. To establish cause and effect, we need to go beyond chaining up a series of numbers. A + B = C may work numerically but to establish cause, we need to know that A and B are the only factors that influence C, that A and/or B directly influences C without passing through another factor, that C doesn't change on its own, etc. etc.

Well none of the numbers work, because at heart the Covid lockdown has slowed down the NHS much more than Covid patients have taken up capacity, so all measures are actually measuring lockdown policy, not virus effects.

I think my problem with the tweet is that the author is attacking a correct claim (The situation is not as bad as many claim) with a completely nonsensical counter claim. The first claim may be based on data that would also fit an alternate hypothesis. But the counter claim (there are not enough nurses) is actually based on an entirely different limiting factor - covid lockdown and restrictions on working practices.*

The truth of the matter is that while there are enough beds for Covid patients treatment for any other illnesses is almost impossible to obtain. Seeing a family doctor is almost impossible. Non-urgent operations are all cancelled. There is little early testing of cancer occurring.

*It is not the virus that is damaging the NHS, it is the over-reaction to the virus - which given how Covid kills patients is quite ironic but not funny.

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Kaiser Fung. Business analytics and data visualization expert. Author and Speaker.
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