The government’s mantra to justify tough lockdowns has been the need to save the NHS from being overwhelmed with Covid cases. The actual number of COVID hospital cases is tracked on the government’s dashboard, and the last update was from 26th November and states
Patients admitted Daily: 1369 Last 7 Days: 10415
I had assumed that these figures were members of the public who had contracted COVID in their everyday lives and then become so sick that they had to be hospitalised, like Boris Johnson. So I was surprised to see this tweet:
6. The data pic.twitter.com/Drs3Sv8OU7
— Statistics Guy Jon ? (@Jon_statistics) November 30, 2020
I decided to look into this. Digging down on the dashboard under “Health Care” we find there are actually 2 categories of hospital patients. 1. Patients admitted to hospital and 2. Patients already in hospital. This is confusing because at first sight 2. seems to be the total number of COVID patients within Hospitals. However these figures are all based on a very large spreadsheet reporting data from each NHS trust. In that spreadsheet it is explicitly clear that 2. is “Total number of inpatients diagnosed with COVID (Last 24h)”. So that means these patients were admitted to hospital for other reasons (stroke, cancer, injury etc.) and who have then contracted COVID in hospital !
I took the Total England NHS data from this spreadsheet and plotted it:
I get exactly the same result as @StatisticsGuy. This means that by far the majority of patients contracted “COVID” in hospital after being admitted for something else! The number of community infections leading to hospital admission is much less! Hospitals seems to be a risky place for patients getting infected by COVID.
Here is the ratio of the two groups of cases with time
The conclusion is that when infection rates in the community are low as during the summer, then cases are mostly community infections. However when the community rates are high then hospital infections dominate. That means that infections are probably being spread to inpatients within hospitals by staff, cleaners & visitors because they get infected, perhaps asymptomatically, within the community. Hospitals are often too warm with little or no ventilation and many patients are held together on a ward. It is easy to imagine how easily infections can spread in such an environment.
What about death statistics? Nearly all “COVID” deaths occur within hospitals. These are defined by PHE as deaths which occur within 28 days (4 weeks) of a positive test. So the question is : How many of these “hospital” cases would have died anyway from the underlying condition that put them in hospital in the first place? These are then so-called deaths with COVID. If we assume that half of them were deaths with COVID then that still has a dramatic effect on the overall death rate. It reduces it by ~40% during the first peak and by 33% during the second peak.
This then implies that the number of deaths caused directly by COVID should be nearer 33,000 rather than the official figure of 51718 as of 1st December.
It also reduces the estimate for the Infection Fatality Rate (IFR) by 33%