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Comment by fortran77 | Hacker News Reader

It would be interesting if there are fewer deaths than expected in the next few years.

the point with death is that once you're dead it's over. and it won't "average out" in the sense of life expectancy. it gives the life expectancy growth a dent. it will only average out in the sense that everybody alife will die some day.

I wonder if they mean like the thing like what people say about DST causing deaths. But if you look on the large scale that blip does not exist. Standupmaths did a segment on it a few years ago. Basically the idea was 'yes you were going to die, and DST seemed to make it happen' but it seemed to only make it happen a few days sooner than it normally would have. Maybe that is what they are talking about? I personally know a couple of people who were marked as dying from covid. But the reality was they were going to die very soon. They both had very advanced stages of Alzheimer's.

as long as it's very.clear that the age distribution of surplus mortality in times of covid is heavily drawing from other than Alzheimer's dead-soon-anyhow; as long as it's very clear that covid-19 kills otherwise healthy diabetics, overweights, heart patients, cant-afford-healthcare people, was-misguided-about-indoor-events people, multiple sclerosis patients, the list goes on, and on and on, ....

as long as that is crystal clear, that "two old dead soon anyhow Alzheimer's patients" completely misrepresent the 500.000+ dead US citizens...

... such an anecdote is perfectly fine ...

There have been a number of studies (e.g. [1], [2], [3]) published estimating how many years of life have been lost to COVID-19. The estimates vary between ~10-15 average years lost per COVID death.

[1] https://www.nature.com/articles/s41598-021-83040-3

[2] https://www.news-medical.net/news/20201021/More-than-25-mill...

[3] https://www.sciencedaily.com/releases/2020/09/200923124557.h...

thank you for these! two us centric and one global, same results!

I can't resist: males of america! you are the the victims, the "loss leaders" of the plague:

> We find that over 20.5 million years of life have been lost to COVID-19 globally. As of January 6, 2021, YLL in heavily affected countries are 2–9 times the average seasonal influenza; three quarters of the YLL result from deaths in ages below 75 and almost a third from deaths below 55; and men have lost 45% more life years than women.

let that sink in:

> men have lost 45% more life years than women.

mask up! vaccine up! and don't let them mn-killers tell you otherwise.

/scnr

[Sorry for posting here. The other thread was flagged and subsequently closed]

Can you suggest me an advanced Bayesian Statistics book that focuses on application without sacrificing too much mathematical rigor?

I am graduating in MS in Stat. I've took a Bayesian Stat course that followed Statistical Rethinking by Richard McElreath. I liked this book because the author appeals to intuition instead of mathematical rigor. I took 2 semester long statistical inference course, so I am ready for some advance material.

Bayesian Data Analysis by Gelman et al. There's a free PDF available on Gelman's website [1]. Definitely application-focused, and the authors are a who's-who of contemporary Bayesian statisticians.

[1] http://www.stat.columbia.edu/~gelman/book/

Thanks! I'll check it out.

If this model works as expected, then it should take into account those who "would have die very soon" otherwise. It models the deaths that would have happened if it were not for COVID and measures the difference against that number. So the person you mentioned should be counted in the projection.

I don't know what fancy stats the economist does (and I don't trust fancy stats), but I looked at the french stats [1] recently and my back of the envelope approach [2] suggest 50k excess deaths. There was 55.7k more deaths in 2020 vs 2019 (which didn't seem to be an extraordinary year). Over a 25y period, the number of deaths increases by 3.4k every year on average (population growth).

The number of cumulative covid deaths in france is 109k, of which 65k to the 1st of Jan 2021 [3]. So the excess deaths seem to be in line with covid deaths.

Now you could get a very different result for another country depending on how well covid deaths are reported. Also difficult to predict how this will look like in 2021. Covid deaths seem to be predominantly people near their end of life, but on the other hand the delay of lots of medical procedures as the result of the lockdown should have its own excess death, plus impact of change in crime, accidents, increase in poverty, etc. God knows what will be the net effect of all this.

[1] https://www.insee.fr/fr/statistiques/2383440

[2] https://zbpublic.blob.core.windows.net/public/excessdeathfr....

[3] https://www.statista.com/statistics/1103422/coronavirus-fran...

In the USA, I heard it reported a couple of days ago that the nosedive in cases and hospitalizations, etc. is being attributed to a high jab rate of those 65 & up...because they were the primary group being hospitalized and dying.

The point being, excess deaths might be better stated as premature deaths. Mind you, death is death. But someone further along in life already nearing death's door isn't the same as a 25 y/o.

Seems that it'll be a year or more before we have more data and can quantify how premature the premature deaths were.

In the long run we’ll all be dead.

So if you killed everyone on earth the mortality rate for the next eternity would be 0.

Please don’t tell the singularity

Mortality rate would be undefined (0/0)

;)

Possibly. This is known as mortality displacement.

https://en.wikipedia.org/wiki/Mortality_displacement

There will still be years of life lost per dead person.

We'll all be dead eventually, but most of us aren't OK with losing X years of it.

> It would be interesting if there are fewer deaths than expected in the next few years.

There should be, due to the “harvesting effect”.

https://en.wikipedia.org/wiki/Excess_death

There's a horrifying subtext here, which is that if people who would have died next year died this year instead, that's... "OK", and it means that their early death doesn't count?

If it "averages out", that still means millions of life-years lost.

It might… but it would still indicate that many living-years had been lost.

It shouldn't, because expected deaths in a time period should be proportional to the living population. If half your population dies in a war, your model should predict half as many deaths the following year, unless you don't update the model.

That's only true if a random sample of the population dies. If we assume (and I'm making this up) that in the steady state, the elderly comprise 90% of deaths, then if a war kills only young people, you'll expect a substantial increase in proportional death rate.

I was simplifying, the point is that the model should always reflect the current state of the population. You shouldn't expect the kind of "catch up" effects that OP is referring to, unless you have static predictions that don't take into account actual deaths and births.

But... you would. If all elderly people dropped dead right now, deaths per year would plummet for decades.

And your model would reflect that after the day all the old people died. So you wouldn't see any negative excess deaths (= actual deaths - predicted deaths). Otherwise you would see massive excess deaths from the baby boomers getting old for example, or negative excess deaths from the WW2 generation in places where many young people died.

Looking at the official numbers in the UK, deaths seem to fall below the expected levels for a week or so, following a big spike in covid deaths.

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