Is this estimating the right quantity? Wouldn't it be more relevant to estimate the total number of years of human life lost due to covid, rather than the number of deaths attributable to covid?
It might also be interesting to measure the cost of the pandemic in terms of economic harm, how much the GDP dropped, how much production was lost, how many stores closed, etc.
Consider the average human worker. In their life, they will output around 10.5 human years worth of work. 50 million years represents the total output of about 4.76 million human lives.
So if you delete the production of 3 million people due to COVID deaths plus all the time spent in lockdowns, 50 million human years lost sounds about right, but probably could be higher. I'd say it's probably about 80 million human years lost.
We could count "years of productive work lost", but that feels like a very cynical way to look at it.
On way of contextualizing it that doesn't equate lives with economic output is to divide by life expectancy: if life expectancy is 70 years then 50 million years lost ~= 0.7 million human lives that never happened, or 0.7 million healthy newborns that died preventable deaths.
> From a purely utilitarian perspective, the worst age to die is 20-22,
that's easily adjustable: if 95% of newborns become healthy 20 yr olds, then just multiply the number of newborns by 0.95. The harder part is estimating total number of years lost, but it doesn't sound particularly out of the ordinary for a research problem in statistics/epidemiology.
Which "costs" more, 100k 20-year-olds dying today, or 100k babies dying today? The 20-year-olds have already had a lot of time, money, and opportunity poured into them, while the babies have not.
“oh, those slaves in [country] only cost me 0.03$/year, no big deal.”
As the hypothetical trolley controller, how many 50-year-olds would you kill to save one 16-year-old? And would you kill the 16-year-old to save a one-week-old baby?
https://en.wikipedia.org/wiki/Value_of_life
This does have this tidbit:
"Historically, children were valued little monetarily, but changes in cultural norms have resulted in a substantial increase as evinced by trends in damage compensation from wrongful death lawsuits.[38]"
Organ donation prioritization does this analysis all the time. They don't publish the exact rules they use for matching but the most important are urgency, compatibility, locality, and survival benefit. Survival benefit is almost literally expected quality life years (QALY) from an organ transplant. A 98-year old will not get an organ that could give a 50-year old another 20 years of life, but a 20-year old that can survive for another year will not get an organ that the 50-year old needs this week. Compatibility and locality are the biggest problems apart from basic availability (too few organ donors, too many patients needing transplants). Once we can print/grow organs the calculus will reduce to prioritization on urgency and then QALYs if supply is still constrained in some way.
You'd probably want to gather life expectancy rates for individuals once they reached five years of age (since infant mortality necessarily lowers life expectancy but after a cliff people who make it tend to live longer than the average with a bunch of 0s, 1s, and 2s in it) for each country in question.
Then you'd need stats for the age of the dead in each country which I guess you don't really have in most cases since the deaths aren't aggregated anywhere since they haven't been attributed to COVID.
Thanks to the Economist for publishing their model. Would be neat to see more stuff like this. I haven't delved too deeply into the code (several 1000 line scripts which would take some sussing out) but it's nice people will have real world projects they can delve into.
“1.5 million potential years of life lost to COVID-19 in the UK, with each life cut short by 10 years on average”
https://www.health.org.uk/news-and-comment/news/1.5-million-...
That would capture not only years of life lost but also the quality of those years. Long-covid seems to be a serious issue for a lot of people and an accurate estimate of that impact would be very valuable.