Do you have it? I hope your symptoms are not to bad. — Punshhh

No reply. Hmm :chin:

The reason you aren't seeing higher mortality among younger people with no underlying health issues is the availability of oxygen, the ability to resuscitate with saline, antibiotics, pressor drugs, and so on. — frank

I'm not sure, though. I get how that would not be reflected in the comorbidities from the death certificates, but I don't see how that gets around the overlap in prognostic factors. Those, presumably, cover all age groups, and those affect severity as well as death (it's not like death is predicted by a different range of factors to severity). So the number of people getting to a point where they need critical medical care will still be influenced most strongly by the same factors influencing mortality.

If this is the case, then the numbers in critical care will still be heavily drawn from the numbers who would have ended up in critical care any that year due to the overlapping factors. Obviously much less so than with fatality. The critical care group will have a much greater flux than the "end of life" group. Plus complicating factors will have a greater impact because of that. I'd be interested if anyone has heard any modelling of the critical care group.

I'm not sure how it makes the cause of death not a big deal though (is that what you meant?). The fact that there's a 90% overlap with comorbidities serious enough to be listed as a cause of death is hugely significant for risk assessment.

We're talking about deaths within 1 year, so talking about overlap with comorbidity in larger groups than "likely to die within 1 year" supports my position. — boethius

They are not comorbidity groups larger than "likely to die within a year". They are exactly comorbidity groups that are likely to die within a year. That's why the experts responsible are talking about overlap within that time scale.

Listing a comorbidity on a death certificate is not the equivalent of assigning a broad risk category. It's saying that the person was likely to have died from that condition had they not had Covid-19. That is literally the wording the ONS use.

Just to be abundantly clear about this the MCCD guidance states that a main listed cause of death must go "back through the sequence of events or conditions that led to death on subsequent lines, until you reach the one that started the fatal sequence. If the certificate has been completed properly, the condition on the lowest completed line of part I will have caused all of the conditions on the lines above it. This initiating condition, on the lowest line of part I will usually be selected as the underlying cause of death, following the ICD coding rules. WHO defines the underlying cause of death as “a) the disease or injury which initiated the train of morbid events leading directly to death"

And clearer still...

"The conditions mentioned in part two [not even the part we're talking about, a lesser subsidiary of it] must be known or suspected to have contributed to the death, not merely be other conditions which were present at the time."

Comorbidity on a death certificate is not the assignment into a broad risk category. It is the declaration of a very serious condition directly responsible (albeit sometimes in part) for the chain of events leading to death.

Most deaths within 1 year do not come from groups with 90% chance of death this year. — boethius

What? How does that even happen mathematically?

If statisticians put someone in a group of 1% risk of death due to heart disease this year, they are not saying that they were just too lazy to analyse further and see which of these people with heart disease have actually quite strong hearts (and so many 0.1% of dying) and which have "the weakest heart" (and so 90% of dying); they are saying "of 100 people in this group we expect 1 to be dead by the end of the year, but we don't know which one" — boethius

Evidence.

most deaths are from groups with small chance of death within the year, but they are large groups and so result in lot's of deaths. — boethius

Evidence, again.

things are no where close to predicting "who's going to die within 1 year". — boethius

Nor do they need to be. It is sufficient to see overlapping cohorts.

assuming the people who would die from heart disease this year have "the weakest heart" and the people with heart disease who die from Covid too have "the weakest heart". This is not what statisticians believe. — boethius

I've literally posted studies showing exactly that. Did you read any of them. They provide prognostic factors for deaths within broad groups (such as hypertension within the heart disease group) which accurately predict likelihood of death within that group. The same factors (in this case hypertension) are associated with a higher chance of death within the Covid-19 group. D-dimer count (18 fold increase) and SOFA scores (5 fold increase) are two more such factors.

If everyone, or most people, gets Covid, and most deaths arise within large risk-groups, then a very slight increase in chances of death due to surviving Covid can easily replenish all the risk groups to result in the same amount of deaths in absolute terms within the year. — boethius

Yes, but your premise is not true. Having a comorbidity of sufficient severity to class as a cause of death is not a "large risk-group" it is, as the country's leading expert in the field has said "people at the end of their lives".

I don't see how that gets around the overlap in prognostic factors. Those, presumably, cover all age groups, and those affect severity as well as death — Isaac

Those factors are also tied to a certain social setting. People will die in Honduras who wouldn't have died in the US. They'll die from dehydration, hypoxia, and septic shock. They could be in their 30s with no underlying health problems.

The fact that there's a 90% overlap with comorbidities serious enough to be listed as a cause of death is hugely significant for risk assessment. — Isaac

True. It's interesting to me to step back and look at what we did, though. Across the world, societies, by going into lockdown, collectively shouldered a burden. I don't think that's how the average person thought of it, but that's what we did. We reduced the mortality rate of a pandemic by collective action.

Those factors are also tied to a certain social setting. People will die in Honduras who wouldn't have died in the US. They'll die from dehydration, hypoxia, and septic shock. They could be in their 30s with no underlying health problems. — frank

Yeah, absolutely. I think I did mention it somewhere, but it should be made even more clear. All this only applies to the developed world. The overlapping comorbidities have a completely different cohort size in developing countries (and presumably within small, very poor groups in developed countries, I don't know). I'm still not sure about "no underlying health conditions". I'd need to see the data on that. Some people work from a default position that disease is random until some factor is proven. I tend to work from the position that it is caused until the random factor is demonstrated. It's just a different axiom, I suppose.

We reduced the mortality rate of a pandemic by collective action. — frank

Well, that's a very positive way to look at it. Not saying that's a bad thing. Personally, I'm more of a governments-too-concerned-about-public-image-to-act-in-a-calm-reassuring-and-timely-manner-could-well-have-killed-thousands kind of guy, but each to their own.

Some people work from a default position that disease is random until some factor is proven. I tend to work from the position that it is caused until the random factor is demonstrated. It's just a different axiom, I suppose. — Isaac

Maybe you could flesh out how you're using "random" and "caused." Random stuff is usually understood to be caused.

Personally, I'm more of a governments-too-concerned-about-public-image-to-act-in-a-calm-reassuring-and-timely-manner-could-well-have-killed-thousands kind of guy, but each to their own. — Isaac

Things would have been worse if this happened 100 years ago. Things would have been worse without the lockdowns. In some places it was overkill, but that's no one's fault.

Maybe you could flesh out how you're using "random" and "caused." Random stuff is usually understood to be caused. — frank

Yeah, fair enough. I'm using random in the sense of not possible to control for. As in, some as yet hidden factor, some non-measurable element of chance (such as replication error in cellular growth), or some ubiquitous factor.

Things would have been worse if this happened 100 years ago. — frank

Interesting thought. Severely limited travel might have kept it in one place, lower population of elderly with comorbidities too. But lack of medical care on the other hand. Thing is, medical intervention is only saving a proportion of sufferers. Using the JAMA figures (which I know are preliminary) 14% went into care and 2.5% died. So presuming those that died went into care first, that care saved at most 85% (some survivors would have survived anyway). The first two factors only need to lower the total infected by, say, 80% or so and total number of deaths would have been lower even without modern medical care. Since the over 70 population has doubled in some countries in the last 100 years, plus most people lived and worked in one town/village...

Things would have been worse without the lockdowns. In some places it was overkill, but that's no one's fault. — frank

Yes, I think that's unarguable. They should have been sooner and accompanied by testing and tracing. We've known about the possibility of something like this for decades. It's shameful we weren't better prepared.

Yes, but your premise is not true. Having a comorbidity of sufficient severity to class as a cause of death is not a "large risk-group" it is, as the country's leading expert in the field has said "people at the end of their lives". — Isaac

"End of their lives" as in over 60?

Or, "end of their lives" as in will die within 1 year?

You can't just substitute meanings all over the place to pretend your position has been my position all along.

All my arguments have been about this 1 year time frame.

So, please show where this expert clarified their meaning of "end of their lives" as to mean "would have died within 1 year". Otherwise, again, you are citing evidence that supports my position, not yours.

"End of their lives" as in over 60? — boethius

No! Who the hell thinks people over 60 are at the end of their lives. I bloody hope not.

Or, "end of their lives" as in will die within 1 year? — boethius

Yes. In the context (and supported by David Spiegelhalter, who specifically referred to 2020). I'm quite confident "end of their lives" meant they they were close enough to death to fit mostly in the year's mortality. Coupled with the severity of a comorbidity appearing as a cause of death. If someone had lung cancer recorded as the cause of death, but then (imaginary doctor incompetence) it turned out they weren't dead after all, just unconscious, do you really think their not very much less likely than other lung cancer patients to make it through the year? "It was nothing, just a little lung failure severe enough to be listed as a cause of death... I got better"

show where this expert clarified their meaning of "end of their lives" as to mean "would have died within 1 year". Otherwise, again, you are citing evidence that supports my position, not yours. — boethius

What? If I can't cite evidence he meant within exactly one year then that somehow counts as evidence supporting your position? How on earth does that work? If I can't cite such evidence (notwithstanding my other supporting evidence) then at best that means we don't know. Under no circumstances does it mean that this cohort are definitely not expected to die anyway within the year. How does it support your position?

Second thoughts just don't bother answering. I've had enough of this.

As in, some as yet hidden factor, some non-measurable element of chance ( — Isaac

Some people become infected or colonized by this coronavirus and have no symptoms. Some become ill enough to die. I think there is a hidden factor involved.

They should have been sooner and accompanied by testing and tracing. — Isaac

I dont worry much about "should haves" unless there's a clear path to doing things differently in the future and there isn't here.

No! Who the hell thinks people over 60 are at the end of their lives. I bloody hope not. — Isaac

The point is, you don't know.

It's completely reasonable to say people at 60 are closer to the end of their lives than people at 20, more so people above 70 or 80.

It's entirely possible to talk about people "at the end of their lives" without meaning "people that will be dead within 1 year", just meaning that old people, by definition, are usually closer to the end of their lives than anyone else.

For a technical expert, it's entirely accurate to talk about old people as "close to the end of their lives".

Yes. In the context (and supported by David Spiegelhalter, who specifically referred to 2020). I'm quite confident "end of their lives" meant they they were close enough to death to fit mostly in the year's mortality. — Isaac

Quite confident based on nothing.

Read his papers, if he had statistical evidence for this, he would have included it in his model, as his model papers are all about health care capacity based on his best use of the statistics available to him.

For instance, he discusses the possibility that there's a very large amount of asymptomatic infected, and explains why (despite a large potential variation in this factor) it can't possibly be high enough to change the main conclusions of his paper and the requirement of social distancing to keep within health care capacity for a significant amount of time.

If he thought a large portion of people who were dying would have otherwise been dead within the year, that's very significant, and he would have included a model or at least some discussion of what that would mean.

The statement you're referring to is also clearly in the context of social distancing working to keep deaths below 20 000 for the whole UK; so, we can understand it to be a feature of that specific scenario, not a feature of Covid if left to proliferate uncontrollably (which his model of a unmitigated spread cannot possibly be interpreted to kill everyone who otherwise would have died within 1 year anyway, not even close). He also just says "maybe" in the sense that it hasn't been completely excluded yet, an upper bound without any reason to assume things will be anywhere close to that upper bound in reality.

So, he is not lending support to your position, just didn't completely exclude it yet within the context of a social distancing scenario that the UK has already passed.

You can't take one statement (not even in a paper but an interview) of an expert, out of the context of where they said it, interpret it wrong (confuse pre-modelling guesses of upper bounds and "likelihood"), not consider their published papers on the same subject, and call it evidence supporting your position (well you can say it is, as you've been doing, it just isn't actual evidence).

What? If I can't cite evidence he meant within exactly one year then that somehow counts as evidence supporting your position? — Isaac

The evidence you cited is that 90% of cases have comorbidities, that is not evidence that 90% (or anywhere close to that) "would have died within 1 year". You've cited risk factors for large groups.

The larger the risk-group Covid is affecting (where both the preexisting condition risk and Covid risk of death is low), the smaller the overlap between people who die from Covid and those that would have died anyway. You are citing evidence that supports my position.

You do not have the technical ability to understand your mistake. You don't want to be taught by me; fine, but your unwillingness to learn doesn't impact my willingness to defend my position.

Some people become infected or colonized by this coronavirus and have no symptoms. Some become ill enough to die. I think there is a hidden factor involved. — frank

I believe in that sense, comorbidity presence and severity explain a lot of the variation between those cases (they are the common factor). In general, the closer something gets to being a mysterious hidden factor (patternless unstructured variation), the closer it gets to being noise (unstructured individual level variation). Signals tend to announce themselves.

I believe in that sense, comorbidity presence and severity explain a lot of the variation between those cases (they are the common factor). In general, the closer something gets to being a mysterious hidden factor (patternless unstructured variation), the closer it gets to being noise (unstructured individual level variation). Signals tend to announce themselves. — fdrake

We simply don't know yet why some people go through infection without any symptoms. I agree that the descent to death is more likely in a patient with an underlying health problem. That's true of flu, motor vehicle accident, cocaine use, etc.

I think I'm on the border of not knowing what we're talking about. :razz: I just wanted a reason to drop in my comment about collective action and how amazing it is. Internet and whatnot.

I think I'm on the border of not knowing what we're talking about. :razz: I just wanted a reason to drop in my comment about collective action and how amazing it is. Internet and whatnot. — frank

:up:

Some people become infected or colonized by this coronavirus and have no symptoms. Some become ill enough to die. I think there is a hidden factor involved.

Yes, there are some geneticists looking into a genetic disposition. It makes sense to me, but I'm no expert.

I've heard from 1/3 to 1/2 exposed show no symptoms. And then others, yes sometimes young with no medical history, come close to death. It's strange.

if we look at a group in the population who are ill with one of the comorbidity diseases who would be destined to die in 2020. Some of those will die prematurely due to a Covid infection. I would find it hard to believe that many of these patients would survive Covid, only to die later in the year, so the overlap will be large, say around 95% ( of those who become infected with Covid)

There is a second group who are ill with the same illnesses, but who are not destined to die in 2020. A proportion of thes patients will die in 2020 after contracting Covid. I would expect the overlap here to remain high, but not as high, say 60%.(of those infected with Covid)

There is a third group who were destined to die of a disease in 2020, but who presented as quite well, but who will die unexpectedly in 2020. Of this group there may, or may not be an overlap, if there is I expect it is quite low, say 10, or 20%.( of those infected with Covid)

Presumably it requires statistical analysis to arrive at an overall overlap across the three groups. I expect we don't have sufficient data to come to anything near accurate.

I've heard from 1/3 to 1/2 exposed show no symptoms. And then others, yes sometimes young with no medical history, come close to death. It's strange.

From what I remember from the article I heard, some people might have a genetic predisposition which causes cells to repell, or become slippy to Covid.

Also I expect (although this is speculation) that some people have a genetic predisposition which makes their immune system somehow vulnerable to, or deadly for Covid.

It’s starting to look more and more like the infection fatality rate of covid-19 is in the ballpark of the seasonal flu, at least according to this study.

https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1

Here is the lowdown:



This is good new, if true.

if we look at a group in the population who are ill with one of the comorbidity diseases who would be destined to die in 2020. Some of those will die prematurely due to a Covid infection. I would find it hard to believe that many of these patients would survive Covid, only to die later in the year, so the overlap will be large, say around 95% ( of those who become infected with Covid) — Punshhh

I agree if you are destined to die in 2020 you are "even more" destined to die in 2020 if you get Covid.

This group I have been calling "would otherwise die within 1 year" or "terminally ill" interchangeably.

The first problem is that not all terminally ill people will get Covid. For instance, if only 15% of people have Covid so far, then there's 85% of these terminally ill people out there, absent a selector that makes these terminally ill vastly more likely to get Covid. If we look simply at the fact Covid progresses geographically then we already know the selector to get Covid of a "well mixed" sub-population is weak, because they are not all clustered geographically; yes, they may cluster around hospitals within their individual regions, but the disease still progresses geographically.

Furthermore, we know who the at risk populations are and we take additional measures, so this also weakens the selector.

Therefore, if 85% of terminally ill people are still out there, they will still die in 2020.

And that's an upper-bound of total infected. The lower bounds is as low as 1% infected (confirmed Covid infections) in which case 99% of terminally ill are still out there and will still die in 2020.

So, although we can assume terminally ill people who get Covid will more likely die even sooner than Covid somehow having the opposite effect and curing them of their underlying condition, for this to create a big effect of simply moving deaths around within the year then we need to have reason to believe this entire population gets Covid with extreme bias (and there's solid reason to not assume that's no so).

There is a second group who are ill with the same illnesses, but who are not destined to die in 2020. A proportion of thes patients will die in 2020 after contracting Covid. I would expect the overlap here to remain high, but not as high, say 60%.(of those infected with Covid) — Punshhh

I read this to mean that 60% of total Covid deaths are from ill people, just not ill enough to die in 2020.

Although I agree most people who die of Covid have underlying conditions, the reason to believe most Covid deaths are not from people who "would have otherwise died" within 1 year, is because the vast majority of deaths each year are not from people who doctors are certain will die within the year.

Lot's of people who have 1% chance of dying from a heart attack have just that, a 1% chance. At the start of the year you can test them however you want, but you couldn't have done any test to determine a greater than 1% chance. The reason is that random things (from the perspective of the start of the year) happen: stressful life events, poor response to treatment due to genetic variation or "bad batch" of pharmaceuticals (quality control exists because processes aren't perfect, including quality control), taking up drinking, unlucky torque on an artery, immune system "learning something" by a lucky stochastic result.

If someone with a 1% chance of death has a prognosis of 1% chance of death from Covid if they contract Covid (what the evidence Isaac cited broadly indicates), then this is the "large risk" group situation I have been talking about and overlap with "who would otherwise die within 1 year" is small if Covid proliferates in these risk groups.

If you look at the risk groups people are in, they are these very large risk groups with around 1% dying per year (increasing with age and severity / number of conditions).

Very, very few people are in a risk group of 90% chance of dying this year. So if everyone got Covid, yes, all these people would die, but there are few deaths because it's a small group.

Very, very large amounts of people are in groups with < 1%, 1%, 2% up to about 10% (with decreasing total numbers). Most deaths per year are due to a very large number of people having a small chance to die, resulting in still a large number. Nearly all these people are above 60, but the are still in large groups that are not otherwise expected to die within 1 year.

The prevailing theory of medicine and actuary science is not that there are hidden variables within the body that actually explain who dies and who doesn't, but rather that variations in environment, disease progression, immune response, life choices, doctor actions, timing of intervention and dosage, etc. that determine who lives and who dies without any ability to predict these things much better than we currently do on a 1 year time frame.

Isaac's position relies not only on these hidden variables, but furthermore that these hidden variables are the same between determining "who actually die from Covid" and "who actually dies from underlying condition like heart disease".

It makes sense on the surface that "the weakest" would die in each case, but this is exactly the opposite idea actuary science is premised on; it's not true that the "weakest hearts" die each year (lot's of other factors involved), and even if it was true (which is isn't) it can easily be something else that drives Covid deaths within risk-groups, such as an otherwise benign genetic variation (subtle protein differences that don't have any difference until now, but Covid exploits that difference particularly well) that helps the virus proliferate faster (epidemic resistance is a classic reason to explain why genetic variation is a good thing). A genetic sub-group particularly susceptibility to Covid explains very well why we still see deaths even in seemingly healthy people.

There is a third group who were destined to die of a disease in 2020, but who presented as quite well, but who will die unexpectedly in 2020. Of this group there may, or may not be an overlap, if there is I expect it is quite low, say 10, or 20%.( of those infected with Covid) — Punshhh

This is statistically impossible to reach 10 - 20%; that would be a huge overlap for a group of people who's "otherwise death in 2020" shares no causal mechanism at all to their Covid death (as they were simply not expected to die).

For instance, I think we could agree that dying of Covid won't somehow preferentially select for people who would otherwise die in a car crash.

This is simply the "base case": let's say a person has 0.5% chance of dying from Covid and 0.5% chance of dying from something else had they lived (so the people that do die from this group represent "unexpected" deaths), so it's a simple "choose 1 out of 200, choose another out of 200, what are the chances the choice is the same item?" which is simply 1 out of 200, a small effect of Covid deaths overlapping "would have otherwise died deaths" in this case (and an effect easily compensated for by increase in death probabilities due to lung damage from Covid, interruption of quality care for many risk groups while the medical system deals with Covid, or other things that can have a small forcing on large groups; decrease in pollution and changes to stress patterns may push things the other way).

Of course, the probabilities don't need to be the same (but they remarkably line up pretty well with chance-of-death by year by age group), but if they are small then overlap is very small. If they are probabilities that apply to large groups, "like all 60 year old's that seem healthy and not expected to die this year" then you still have large numbers because these are large groups.

Furthermore, if Covid deaths would be happening in a short period of time, instead of over a year, then even groups that have low probabilities of dying from Covid, they would still overload the health system as they arrive in a short period of time (why the idea of trying to protect over-70s and letting everyone else live normally made no numerical sense).

I’m waiting for number of registered deaths in next UK report (in a few days).

If there are still 50% more deaths a week than usual then I’m inclined to disagree - judging by the UK governments latest statements I imagine the rough estimates are that the number of deaths (covid or otherwise) hasn’t eased off at all.

The hysteria does bother me, but that’s just human nature. From what little I’ve managed to glean I wouldn’t be at all surprised if the figure is below 1%, but don’t think it’ll be any lower than 0.5% - which are both significantly worse than the flu. Maybe the professor deems that ‘in the ballpark’, but it’s highly suspicious to say that rather than put an actual figure to his estimate.

it also depends on viral load

The latest peer reviewed estimate in the Lancet was .6%.

Also, I've looked into the Chinese and WHO handling and the more I look into it, the more appalled I'm getting. I can get the misinformation from the local Chinese government as that's to be expected in a "shoot the messenger" culture. After that though, 10 january China fails to communicate an almost certain person-to-person transmission to the WHO and instead feeds it the famous 14 january line that "no clear evidence" exists fo person-to-person transmission. While that might have been technically true, it appears to be purposefully misleading given the available anecdotal evidence at the time.

It's fine to say you haven't conclusively established it but if you're sure as shit looking into it because of the anecdotal evidence, China should've said so.

Let's remember 10th of january is the same day the WHO does not advise to test people flying from Wuhan.

And sure the WHO is a political body but the level at which it is, is rather worrying. There really does seem too much subservience towards China that has endangered a lot of people across the world as a result.

Notwithstanding all the aid now flowing from China this really needs to be taken seriously as it's really problematic if they fail to appropriately inform others of new diseases.

There are a large number of factors resulting in deaths in this pandemic, so I want to focus on this point you are making about the overlap.

So you are happy with there being a group (1), which is a small group, who are destined to die in 2020 due to another medical condition, comorbidity. With an overlap of 95% or more, who have contracted Covid, dying due to Covid.

You are happy with a group (2), who have an underlying medical condition, comorbidity, but who are not destined to die in 2020, they may die in 1, 2, or 10 years of these conditions. That this is a large group, and that a large proportion of these patients will die in 2020 if they contract Covid. I estimated that 60% of these who contract Covid will die.

You are happy with another group (3) who are destined to die in 2020, but who don't present as very ill when they contract Covid. I accept for now that the overlap here may be smaller say 1-5% who contract Covid will die.

It's important that we don't complicate this with discussing the percentage of the population who has currently been exposed to the virus, because this figure is changing throughout the year and the degree of this change is determined by many factors other than morbidity.


So you are proposing that (1) is very small, so insignificant. That (2) is very large, and presumably (3) is small. Meaning that the majority of the comorbidity deaths are in group 2 amongst people who may have an underlying health condition which is not going to kill them for many years in most cases, but who have a high mortality if they contract Covid.

So your main point is to highlight the large number of deaths in group 2. So how do you conclude that the overall comorbidity overlap is small? ( is (2) a small percentage of the population?).

I'm trying to follow your line of argument here (or rather your request for clarification), but your terminology is a little confusing in places. It may just be that you're attempting to reflect boethius's terminology, but I may also have just misunderstood what you're saying, so...

If you're accepting that there could be a "large number of deaths in group 2", then group 1 cannot possibly be "small". Experts predict about 20,000 deaths total from Covid-19. Group 1 has at least 300,000 in it. Or is that the point you were trying to make and I missed it?

So you are happy with there being a group (1), which is a small group, who are destined to die in 2020 due to another medical condition, comorbidity. With an overlap of 95% or more, who have contracted Covid, dying due to Covid. — Punshhh

No, because not everyone in this group gets Covid.

It works in reverse, 95% of people in this group who get Covid we might reasonably expect they die of Covid, and certainly all of them within 2020 (as we don't expect Covid to somehow cure them).

But, the whole group doesn't get Covid. So far estimates are 1 - 15% of the population actually has Covid ... or exposure to Covid, even in hotspot areas (exposure, even if real and not a false positive, may or may not provide good immunity). So, even with the upper bound of 15% got Covid, 85% of people in this group don't die of Covid and do die of something else, so their burden on the medical system remains 85% (and they are a small group to begin with).

As more people get Covid, more of this group also get Covid, but more people in other groups get Covid too. The ratio remains more or less the same (for decision making purposes about projecting health care burden) absent an extreme bias for this group to get Covid (for which there is no plausible mechanism, considering geographic constraints alone).

You are happy with a group (2), who have an underlying medical condition, comorbidity, but who are not destined to die in 2020, they may die in 1, 2, or 10 years of these conditions. That this is a large group, and that a large proportion of these patients will die in 2020 if they contract Covid. I estimated that 60% of these who contract Covid will die. — Punshhh

This is not justified by what we know so far.

The basic pattern is Covid doubles your risk of death this year. Most people who have a risk of death "within 10 years" don't have 30% risk of death this year and therefore 60% risk of death with Covid this year (which is still not 60% chance of death from Covid). If a person of high risk of death with in 10 years has 5% risk of death this year, then their risk of death of Covid seems to be also 5% (therefore 10% within the year).

Why we see Covid deaths overwhelming medical system is that large numbers of people have a low risk of sever complication of Covid.

Most individual deaths within a year are not well predicted individually at the start of the year. Being in a risk group of 10% chance of death this year is a very high risk group.

Actuary science and medical science places a large importance on random variation of environmental factors, internal factors, life choices, life events, medical intervention, accidents, family support, etc. in causal determination of who will actually die within a year time span. In short, there are large groups of which a small portion of them will get "unlucky" within a year time-frame (with a fundamental inability to make a better prediction at the start of the year regardless of amount of tests, measurement, modelling, crystal balls or any other predictive device).

Definitely, these groups from which deaths happen "randomly" are heavily weighted towards being old and / or having underlying conditions, but these groups are still very large for our statistical purposes here of estimating overlap between the set of Covid deaths and the set of "otherwise would have died this year".

The reason that the group of people we are pretty certain will die this year is small, is because (for most people in wealthy society not at war) to get to ~90% chance of death this year (such as 90 year old with dementia and failing heart) meant having a ~80% chance of death last year (due to slightly less sever dementia and failing heart), and ~70% chance of death the year before that, and so on (though these numbers will depend on disease, there is not a large group that had 0.1% chance of dying last year but 90% chance of dying this year). So most people "getting old", the group they are a part of was already reduced significantly each year prior to getting to 90% and in a accumulative way: starting at about 5% chance of death this year, these risk-groups thin out very rapidly in a 10 year time span (each year they lose members and the chance of death of remaining members increases); during this time span most deaths are not well predicted individually (of 20 people, one of them dies the first year; maybe in a way that makes sense in hindsight, but there was no way to predict which individual would die at the start of the year).

This is why from 60 to 100 years of age the demographic chart is nearly a straight line to almost 0 population at 100, but it's a fat bar until 60 (variations in birth rates and immigration can dominate death rates below 60).

Also, why I keep coming back to the fact the discussion is about a year time frame.

If we were talking about dying within a 20 year time frame, the overlap can easily start approaching 90% for the exact same reasons (relatively high-risk groups rapidly thin out on decade time scales; just not 1 year time scales). Overlap between dying of Covid or "otherwise would die within 20 years", which is not to say people who will die within 20 years are "very likely to die of Covid".

In a 1 year time frame -- which is relevant for estimating health care resource needs and other policy choices -- overlap is low if a disease affects large risk groups (such as people in their 60s with hypertension). If a random (otherwise benign) genetic difference is also a good predictor of death from Covid, then the overlap is even less strong as Covid doesn't tend to select for "worst heart" within these risk groups but it's random genetics that dominates chance of death from Covid between risk category peers, leaving survivors to be just as likely to die of heart failure as before (perhaps more so due to long term lung injury), and also explains why Covid can kill completely healthy people, as perhaps they just have bad genetic luck (maybe Covid exploits particularly well 3 uncommon gene variation; then it could be if you have all 3 genes you have a 90% chance of death even if healthy, and it's quite rare to have them all, but happens) so is consistent with "gene variations matter hypothesis" and this hypothesis is consistent with the dominant medical theory.

Unless there is a very clear pattern that would be obvious by now (you only die of Covid if you not only have hypertension but have already had a heart-attack, or if you are on immune suppression therapy or otherwise severely immuno-compromised); absent such patterns, "risk-factors and genetics" is the go-to explanation for why some populations survive a selective pressure and some don't, without good individual predictors available at the start: it's how evolution usually works, so no reason to assume it's not happening with Covid; i.e. it obviously doesn't help to be obese or have hyper-tension or smoke or be old and frail, but the virus maybe only particularly lethal with certain particular kinds of proteins on cells; i.e. certain genes or particular epigenetic gene expression or specific immune system history (such as getting or not getting some particular common cold in the past by random chance).

Therefore, it's more reasonable to assume there is large random variation determining individual deaths from Covid from among large risk groups (as this is the pattern we actually see) and subsequently assume that deaths from other causes will continue, perhaps even increase (for the purposes of decision making), than to assume actuary and medical science is wrong (foundationally, not just some specific issue) and there are some hidden variables that dominate the real determination of both individual death each year, for instance not just heart disease but having "the weakest heart" (but in a way we can't measure), and individual death from Covid (and these hidden variables would need to be the same in both cases to boot; the hypothesis is implausible, and even if true, it's still implausible) resulting in Covid deaths tending to lighten the burden on the health system from other causes of death (as those deaths are now dead from Covid, no longer available to die of something else).

Of course, there can be second order effects that actually do reduce deaths (people drive less and therefore there are less accidents) but this has nothing to do with the statistical overlap discussed here but a consequence of our response to Covid (it's entirely reasonable for modelers to estimate less traffic due to lock-downs, and therefore less accidents and therefore position less traffic accident resources; this was an obvious lock-down health-care hypothesis that has already been proven true; but another hypothesis that people who need care for other things don't get care and therefore die at a higher rate also seems to be proven true).

I was not trying to make a point, I was trying to work out what Boethius's point is.

For me the confusion seems to be in dividing group 1 from group 2. So I phrased it in terms of those who are, or are not destined (absent the Covid epidemic) to die during 2020. Thus confining members of each group to their group, eliminating overlap between the groups.

So when we include Covid the size of each group is unchanged with no overlap. But in this case a percentage of group 2 does die in 2020, solely due to contracting Covid.

The idea being to tease out what Boethius is trying to say.

I was asking about those who do catch Covid, I even put it in bold.

So it looks like you're saying that not many in group 1 die in 2020 because only a small amount of them will become infected?
Unfortunately we don't know how many will become infected by 31st of December.
Also that just as many by percentage of fit and healthy people get it to( perhaps the size of the group 1 by percentage is important here).

Regarding group 2 your wall of text suggests to me that you disagree with my 60% of those infected? Where would you estimate the figure? Or do you think it can't be estimated for the reasons you give?

So it looks like you're saying that not many in group 1 die in 2020 because only a small amount of them will become infected? — Punshhh

Well, I'm relating this group to my discussion with Isaac.

If this group was very large and most deaths from Covid came from this group, then Covid deaths displace near-future deaths.

If this this group is small and people are dying of Covid outside this group then this effect is small. If, for our purposes of decision making now, this group has not even gotten Covid much, then the effect so far is even smaller and so even less likely this group is displacing near-future deaths.

However, if your question is simply if we can be 95% sure people who are destined to die in 2020 would die of Covid if they get it, then no we can't make that assumption. It doesn't really matter what we assume, as they are going to burden the health care system either way, but we'd have to know more about these people; maybe they have some terminal disease that doesn't affect their resistance to Covid (they experience Covid as just a cold and go onto die from a heart attack this year anyways).

Thanks, that ties in with what I thought you were doing, but I wasn't sure.

So it might help to put some numbers in?

Group 1 - those who are going to die this year is about 500,000, but when we're talking about overlap of comorbidities, we're only really interested in a sub-group {those who are going to die this year from underlying health issues}. That's about 300,000 - taking away accident and intentional self-harm.

Group 2 - comorbidities which will not lead to death this year. About 2.5 million for cancer, 7.4 million for heart disease. Other risk groups are much smaller, so we could say about 11 million.

Group 3 - some proportion of the remainder (about 59 million) who will, despite a lack of comorbidity die from coronavirus. We know from the studies that this group is somewhere between 0 and 9 % of all coronavirus deaths, so taking Prof Ferguson's latest estimate of 20,000, and a mid-range estimate, this group would be about 1,000 people.

So the question is how the remaining 19,000 estimated deaths will be distributed between groups 1 and 2.

We know that this group (the 19,000) will have comorbidities serious enough to be listed as a cause of death. So we can re-label this group, group A {those with comorbidities serious enough to appear as a cause of death}

As you can see, the size of groups 1 and 2 is irrelevant right now. The question is solely about the nature of group A. Is group A drawn mostly from group 1 or mostly from group 2? Group 2 being bigger only makes a difference if group A is being drawn from the pooled group 1+2 at a bias that is significantly less than the 3 in 100 ratio between the group sizes (boethius's contention).

Disputing even the lower of the estimates for overlap (50%), we'd need to argue that fewer than 49% of those in group A are drawn from group 1. Ie we'd have to say that the group of people so ill with a condition that it is listed as a cause of death is not even majoratatively drawn from a group of people so ill with that same condition that they are going to die of it later this year.

To me, such a contrary contention would require a substantial amount medical evidence demonstrating its veracity and the mechanism by which it acts. (not to mention the reason why the country's leading expert on pandemics has somehow missed this fact in his training thus far)