As London goes into Tier 4 COVID lockdown here is proof that the government data for London is flawed

With the sudden announcement of the Tier 4 lockdown for London yesterday I decided to look at the London hospital admissions and 'case' data (where, by definition, 'case' = positive test). Using the data at https://coronavirus.data.gov.uk and filtering on London I did a plot of hospital admissions as a percentage of cases (this is a crude measure of 'severity' of the virus at any time). I used 7-day rolling averages for both cases and admissions and assumed a 4-day lag from positive test to admission (none of these assumptions makes a lot of difference to the results). The results I got below are very interesting for two reasons.

 The first reason is that you can see that the percentage of 'cases' leading to hospitalisation has been steady at around 7% for over 3 months, so no increase in 'severity'. In fact, as recently as mid-September it was much higher at 12%, and in June it was really much higher at ....120%. Which brings me on the second reason why the results are, to say the least, interesting. It should, of course, be impossible for the number of COVID hospitalizations to be greater than the number of COVID 'cases'. Yet it is not my analysis that is in error here. Here are the raw data, for example, from June:

I have highlighted some examples of admission numbers which do not appear to be feasible given the previous days number of new cases. Now, of course, for any new admission we do not know date of the associated positive specimen. For my chart above I have assumed on average a hospital admission follows 4-day after a specimen was take that ended up positive. But we know that a hospital 'admission' is also classified as COVID when there is a (first) positive test after admission. However, whichever way you look at this data it cannot be correct. The data for COVID hospital admissions (in June at least) must be exaggerated (it cannot be that 'cases' are underestimated because a hospitalisation cannot be classified as COVID without a positive test, i.e. a recorded 'case').

In case anybody thinks the error must be in the way I have extracted the data, here are screen shots for relevant part of June from the government website:

Now, there they may be understandable reasons for errors in the Government data. For example, perhaps only a subset of hospital admissions were recorded in June, or perhaps there are different definitions of what 'London' is defined as for 'cases' compared to 'admissions'.  But, whatever, if the Government cannot get such basic data correct, it hardly inspires trust in their Draconian decisions. And how do we know that the number of COVID hospital 'admissions' is still not being exaggerated?

Update (21 Dec): Here is the London case fatality rate. Again, not much here to suggest the need for panic.

See also:

Remarkable relationship between number of tests and positivity rate when we drill down into regions