None of that has any influence on the difference in risk between a member of a “risk group” and an “average person”. To the contrary: If the data is biassed towards cases with symptoms and symptoms are more likely to show up in risk groups, than the additional risk of this belonging to such a risk group is actually overestimated in the data!
Malibuflyer wrote:
To the contrary: If the data is biassed towards cases with symptoms and symptoms are more likely to show up in risk groups, than the additional risk of this belonging to such a risk group is actually overestimated in the data!
But this is a retrospective analysis and the endpoint is death. If a hypothetical individual case doesn’t have symptoms and is less likely to be included in the analysis as a result, then remember also that by definition they don’t die of Covid-19, so their exclusion from the results can only move the average risk one way.
The best explanation I have found is here, with the excellent summary:
This suggests that COVID-19 very roughly contributes a year’s worth of risk. There is a simple reality check on this figure. Every year around 600,000 people die in the UK. The Imperial College team estimates that if the virus went completely unchallenged, around 80% of people would be infected and there would be around 510,000 deaths.
So, roughly speaking, we might say that getting COVID-19 is like packing a year’s worth of risk into a week or two. Which is why it’s important to spread out the infections to avoid the NHS being overwhelmed.
It’s important to note that all the risks quoted are the average (mean) risks for people of the relevant age, but are not the risks of the average person! This is because, both for COVID and in normal circumstances, much of the risk is held by people whom are already chronically ill. So for the large majority of healthy people, their risks of either dying from COVID, or dying of something else, are much lower than those quoted here. Although of course for every death there will be others who are seriously ill
Graham wrote:
So, roughly speaking, we might say that getting COVID-19 is like packing a year’s worth of risk into a week or two.
If this metric helps people to understand the personal risks, then it is great. For me that metric is counterintuitive and therefore doesn’t help me.
Might be “One year of risk” – but what is such a one year? Just to put that into relationship: In 2019 Afghanistan had 16.300 deaths from terror attacks at about 600.000 total deaths in Afghanistan per year this equals about “10 days worth of risk” in your metric. In Central Europe we are talking about seconds of risk added. So why should people worry about terrorism at all?
Graham wrote:
It’s important to note that all the risks quoted are the average (mean) risks for people of the relevant age, but are not the risks of the average person!
The seems to be an interesting definition of “average person” (“interesting” as in “wrong”). An average person has exactly the average (mean) risk – and by the way an “average” person in Central Europe has about 9.995 fingers. This is why we would call him average.
What the author (and probably you) want to say is that you would regard the majority of people (and obviously yourself) not as “average” with respect to risk, but as an order of magnitude better risk (like with the pilots in any airfield bar that also regard themself as clearly above average pilots that strongly believe that accidents only happen to this high risk pilots they call “others”).
The data I provided earlier, however, clearly shows that this is not true as the risk – while obviously being higher for some people than for others – is much more evenly distributed than most people believe. If you take out the very old and very sick, it is very homogeneous (including the risk of smokers, obese and even CHF, etc. patients).
Malibuflyer wrote:
If this metric helps people to understand the personal risks, then it is great. For me that metric is counterintuitive and therefore doesn’t help me.Might be “One year of risk” – but what is such a one year? Just to put that into relationship: In 2019 Afghanistan had 16.300 deaths from terror attacks at about 600.000 total deaths in Afghanistan per year this equals about “10 days worth of risk” in your metric. In Central Europe we are talking about seconds of risk added. So why should people worry about terrorism at all?
It’s saying that, as a healthy non-elderly person, if you get Covid then your chances of dying this year become roughly double what they were without Covid. However, because a healthy non-elderly person has a <very small, so small we don’t worry about it> % chance of dying this year, double a very small chance is still a very small chance.
Malibuflyer wrote:
The seems to be an interesting definition of “average person” (“interesting” as in “wrong”). An average person has exactly the average (mean) risk – and by the way an “average” person in Central Europe has about 9.995 fingers. This is why we would call him average.
What the author (and probably you) want to say is that you would regard the majority of people (and obviously yourself) not as “average” with respect to risk, but as an order of magnitude better risk (like with the pilots in any airfield bar that also regard themself as clearly above average pilots that strongly believe that accidents only happen to this high risk pilots they call “others”).
The data I provided earlier, however, clearly shows that this is not true as the risk – while obviously being higher for some people than for others – is much more evenly distributed than most people believe. If you take out the very old and very sick, it is very homogeneous (including the risk of smokers, obese and even CHF, etc. patients).
Nope, I’m afraid you’re wrong. The average number of fingers per person in Central Europe may be 9.995 but the average person has 10 (and some very tiny number have an integer less than 10, no-one has 9.995.) They are different things.
In both these examples it is quite evident that risk is not spread evenly throughout the population. The assertion, that most people are ‘above’ average (in the sense that they have less risk) is correct. Most people have very little risk and a small subset of the population bears the majority of the risk for that whole population. You’re sort of correct in how you say it’s homogenous in the remaining population once you take out the old and those with existing medical risks – homogenous at very close to zero because in removing those people you have removed nearly all the risk with them. And it isn’t just the ‘very old’ and ‘very sick’, the ‘not in very good shape’ also see a significantly-increased risk over the fit-and-healthy, no matter how much you might want to pretend, presumably for personal reasons, that is isn’t so.
We don’t like to think of it like that in flying, because one very good way to reduce our own personal risk is to always consider ourselves high risk, not be complacent, etc. This is a good thing. But the fact remains that if you take a population of pilots, most of them are low risk and almost all of the total statistical risk for that population sits with a small number who have particularly poor judgement, skills, and tendency to engage in risky behaviour.
The data you provided earlier does not show what you think it does.
Both sides here are half right.
The risk of death is highly concentrated in those of 60+ years of age. And whether the younger with to accept a risk of 0.x% – which is around double the risk they would normally have to die in any given year – could be left to the individual.
However, hospitalisation rates of >5% for around half the population are pretty severe and cannot be ignored.
But that is, per the chart title, your ‘risk if diagnosed’.
I simply argue that many infections, probably a majority, are not diagnosed and thus many infected datapoints who are neither hospitalised nor die are excluded and thus the rates shown are artificially high.
It also doesn’t cover comorbidities. For any data point along the axes, e.g. 51yr old man with hospitalisation 8.8% and death 0.5%, one needs to divide that to reflect relative risk in the population because the average healthy 51yr old man, on diagnosis, does not have an 8.8% chance of going into hospital. The data shows that 8.8 out of 100 51yr old men get hospitalised, but probably 8 of them have comorbidities.
Graham wrote:
I simply argue that many infections, probably a majority, are not diagnosed and thus many infected datapoints who are neither hospitalised nor die are excluded and thus the rates shown are artificially high.
That is definitely the case. It may or may not be a majority, but it won’t be far off.
So the % of asymptomatic infections is somewhere between 30-70%, with a high concentration in the younger. So half of all cases being entirely asymptomatic is certainly plausible.
Graham wrote:
It also doesn’t cover comorbidities.
I wish that was the case, but these graphs are for people without co-morbidities – I should have added that, I have posted them before. Also, the data is without vaccination, and now a year old – but it was hard to find anything reasonable about this that wasn’t, the stuff @Malibulyer referred to also was not very recent.
Here is the one for type 2 diabetes as co-morbidity.
https://www.economist.com/graphic-detail/covid-pandemic-mortality-risk-estimator
I roughly figured that the risk of serious injury or death from COVID while unvaccinated and otherwise healthy middle age is roughly the same as the risk of serious injury or death from racing in the Isle of Man TT.
However, at least the Isle of Man TT is enjoyable for the competitors, COVID not so much.
Malibuflyer wrote:
So why should people worry about terrorism at all?
That’s actually a very good question. IMO, we are worrying way too much about terrorism.
Graham wrote:
Nope, I’m afraid you’re wrong. The average number of fingers per person in Central Europe may be 9.995 but the average person has 10 (and some very tiny number have an integer less than 10, no-one has 9.995.) They are different things.
You are mixing average with median
