COVID19 Again By The Numbers

According to the government's chief scientific advisor, Sir Patrick Vallance, the mortality rate for people infected with COVID19 is 0.1%. But, this average figure hides wide variations in terms of who is most at risk, and who is essentially not at risk in any statistically significant manner. A study by Imperial College provides the following table in relation to those expected to be admitted to hospital with the virus, based on data from China.

Age group	% symptomatic cases requiring hospital	% hospitalised cases requiring critical care	% Infection Fatality Ratio
0 to 9	0.1	5.00	0.002
10 to 19	0.3	5.00	0.006
20 to 29	1.2	5.00	0.030
30 to 39	3.2	5.00	0.080
40 to 49	4.9	6.30	0.150
50 to 59	10.2	12.20	0.600
60 to 69	16.6	27.40	2.200
70 to 79	24.3	43.20	5.100
80+	27.3	70.90	9.300

At the time of writing, 769 people have died, in the UK, from COVID19. On the basis of Vallance's figure for the mortality rate of 0.1%, or 1 in 1,000, we then should have total number of infected people of around 769,000, though the actual figure is probably higher than this, because infections will precede deaths. The Imperial study states, 

“Analyses of data from China as well as data from those returning on repatriation flights suggest that 40-50% of infections were not identified as cases. This may include asymptomatic infections, mild disease and a level of under-ascertainment.” 

However, most studies now indicate that around 80% of people have no or only mild symptoms from COVID19, and this explains why the number of infections is much greater than the number of people who have symptoms and seek medical treatment. But, also, many people have symptoms, but do not have COVID19. In Britain, at time of writing, 113,777 people had been tested for COVID19. Only those going to hospital with symptoms are tested. Of those tested, only 14,543 tested positive, the other 99,234 tested negative, presumably meaning that they had flu like symptoms, caused by either the flu virus itself, or some other flu like virus.  This also explains why health services are being overrun.  Its not from COVID19, but from an upsurge in people suffering from flu or other flu like viruses.  In other words, the number of people going to hospital with flu like symptoms was 113,777, but only 14,543 of these had COVID19, as opposed to having flu.  If the number of flu infections is even anything like the ratio in relation to COVID19, then it means that there are probably about 10 million people who have flu infections, if there are 1 million with COVID19 infections.

If the total COVID19 infections is estimated at around 769,000 based on Vallance's mortality rate, then, if the number suffering symptoms severe enough to go to hospital is 14,543 that means that the proportion suffering such serious effects is around 2% of the total. This figure is significantly below the figure of 20% in the at risk group, but this difference can be explained by the fact that, whilst those in the 80% may experience no symptoms or only mild symptoms, not all those in the 20% group either will experience severe symptoms to an extent that leads them to go to hospital. They may experience more than mild symptoms, but perhaps only similar to what might be experienced by a bad dose of the flu, for example.  It is, after all, not everyone in the 20% who dies either.

The Imperial College data is a model based on Chinese data, not on actual UK hospital admissions. The higher standard of living, and existence of the NHS, in Britain, is likely to result in better overall outcomes than those experienced in China - and the same in relation to access to healthcare applies in relation to the US, because of its lack of an NHS or Medicare For All. The predictions from the Imperial study are for those expected to be admitted to hospital in different age categories, and are not based on total number of people infected. They conclude, from the Chinese data, that the mortality rate would be around 0.9% overall, and with 4.4% of those infected being hospitalised. However, as the analysis by Vallance indicates, this figure of a mortality rate of 0.9%, is probably out by around a factor of 10. The reason is that the Chinese authorities themselves, as in Britain, only recorded as infected those that had been tested, and, as in Britain, only those that went to hospital were tested. Moreover, China, when it tested people, did not count as infected those that had been infected with COVID19, but who had developed antibodies against it. So, the Chinese data grossly overstates the proportion of people that were hospitalised with COVID19, and its mortality rate, as against the actual total number of people infected by it. 

The figure of a mortality rate of 0.9% is the basis of some of the more wild speculations of potential total deaths from COVID19. For example, if 50 million were infected, it gives a total number of deaths of around 450,000, though even that is significantly less than some scare stories which talked of deaths amounting to 5 million, which is an indication of the degree to which a total panic and atmosphere of hysteria has been created. The actual mortality rate given by Vallance of 0.1% produces total deaths of “only” 50,000, were 50 million people infected, but the reality is that long before 50 million were infected, herd immunity would be established, and would slow the spread of the virus. A far more likely total death total would be around 20,000, which is about the same as the number of deaths from “flu” in 2018, which itself included perhaps around 2,500 deaths from coronavirus, which were attributed to flu.  That is because as a Glasgow study found, around 14% of "flu like symptoms" each year are caused by coronaviruses, not by actual flu.

But, what the Imperial data does show is the point I have set out in previous posts over the last few weeks I am grateful to Nomadron for his rational and calm assessment of my posts during that time, which is what I would expect from someone with his experience working for various international NGO's over the years. The Imperial data shows that the mortality rate amongst the under 50's is more or less statistically insignificant. If we bear in mind that the overall mortality rate from actual infections rather than only the reported infections, which is what this data was based on, is 0.1% and not 0.9%, then we would need to shift these percentage figures to the right by one decimal place. That gives a mortality rate for the under 10's of 0.0002%, for the 10 – 19's of 0.0006%, the 20's to 29's of 0.003%, the 30's to 39's of 0.008%, 40's to 49's of 0.015%. 

But, what is significant here is the risk to those in the older categories compared to the younger age groups rather than the actual percentages. In short, someone in the over 80 category is about 60 times more likely to die than someone in the 40-49 group. They are 120 times more likely to die than someone in the 30-39 category, 350 times more likely to die than someone in the 20-29 category, and 1750 times more likely to die than someone in the 10-19 category. These multiples can be approximately halved for someone in the 70-79 category, and halved again for someone in the 60-69 category, so that, for example, someone in this latter category is about 400 times more likely to die than someone in the 10-19 category. 

Of course, as I have set out previously, this breakdown by age is itself misleading, because it is not, by any means, just those who are more elderly who are most at risk, and who fall into the 20% category. Also in that group are those who have underlying medical conditions that makes them vulnerable, and, for example pregnant women. Also at risk will be anyone who may not normally have other underlying conditions, but whose immune response is currently weakened by other conditions. They may have recently had some other illness, they may have been working long hours, and so are tired, and so on. The fact is, however, as this Imperial data shows, the actual risks for those in the 80% are extremely low not just of death from COVID19, but even of serious ill-health requiring hospital admission. The need for critical care for anyone in such groups is even lower. According to this data it is only around 5%, for those younger than 50, but given what has been stated previously that figure is only for those themselves admitted to hospital, whereas a much, much larger number of people in those age ranges will contract COVID19 without knowing it, and so will not go to hospital in the first place. The percentage of people in those age ranges contracting COVID19, and requiring critical care, is then likely to be extremely small. In other words, probably only around 0.05% of those infected in those age groups would require to be hospitalised, and of those only 5%, would require critical care, that is 0.0025%. That is why the number of people, in these younger age groups, that are being admitted to hospital and require critical care, can be counted more or less on one hand, and yet, the media publicise these individual cases as though they were the rule rather than a very limited exception to it. By contrast, 27% of people in the over 80 category who are tested for COVID19, are admitted to hospital. On the above basis that the actual total number of infections is approximately ten times the number of reported cases, that means about 2.7% of this population requires hospital treatment. But, of this 2.7%, 70% require critical care, that is approximately 1.9% of the total actually infected. That is a significant number compared to those in the younger age groups. 

That is precisely why the rational strategy should have been to, early on, isolate the people in the at risk 20%, so that they could have been prevented from catching the virus in the first place, and so would have avoided needing hospitalisation, and more importantly avoided the need for critical care. It is clearly these at risk groups, particularly amongst the elderly, that are creating the surge in demand for treatment, and, particularly, for critical care. My guess is that, just as with the situation in Italy, the reason for this is that COVID19 got into the health and social care system where these elderly and vulnerable groups are concentrated. As with the spread of MRSA, in hospitals, previously, once the virus is in that environment it can spread rapidly. Care workers in most cases do not have adequate PPE, so that each care worker becomes infected with the virus, most of them suffering no symptoms, but then rapidly spreading it throughout the care home sector. Reports indicate that nurses, GP's and other health workers also do not have adequate PPE either, and so this same transmission mechanism for the virus quickly spreads it through the hospital system. 

But, the data also indicates that 10 times more people who are falling ill are people suffering from flu or other flu-like viruses, not from COVID19, despite all of the hysteria being whipped up around it.  The real story is the fact that the NHS is not fit for purpose, is badly equipped, and hugely understaffed, as a result of ten years of Tory austerity, and the same can be said of the health service in Italy, and elsewhere in Europe where the same austerity measures have been implemented following the financial crash of 2008. But, those austerity measures will appear as nothing compared to the economic damage that is currently being done to economies as a result of closing them down by government diktat.