Most 🌍 comparisons for C19 go wrong as they don't considering demographics.
For countries I've managed to src detailed death data for, here's total d/1m numbers.
Sure,🏴🏴 look similar to 🇧🇷🇵🇪, but just look at the differences <60, 🇵🇪 4x larger.
So what does this mean?
1/9
Basically, fewer >80, means they've had⏫spread, and ⏫younger deaths, but👀equal.
Here ranking⏫2⏬by age are:
▶️20 countries
▶️NY city
▶️The World
That I've 👀at so far.
50% marks the median age, e.g.
🇮🇹 47
🏴🏴41
🌍30
🇳🇬18
So expecting similar deaths overall is silly.
2/9
So how have deaths actually played out?
Here are the props. by age to late Dec for places with detailed data.
Looks like NYC, 🇧🇷 & 🇵🇪 have seen far more in the young.
Now these all have younger pops. so is spread the same? Are diff just down to demographics?
3/9
No, many factors, the biggest age, and the likelihood of death in each age band.
🌍serology studies have sampled a similar risk in each 10yr band, with this going up 3 fold with each band.
Here is a plot of what🌍avgs are.
So what else do we need to worry about?
4/9
Factors like:
▶️healthcare: beds nos, better care, etc
▶️comorbidity rates: e.g. obesity, OECD 4x India, but only effects 15%
▶️lifestyle impacts: carehomes VS elderly@home
etc
But, many cancel out.
e.g. 1st🌍better healthcare, but fatter.
What about a lack of treatment?
5/9
Worst case, 🇬🇧 HFR is 15%, with 50% needing O2, so 3x die without hosps.
But, 🇧🇷🇮🇳etc data is hosp data, they don't have near realtime all-cause like 1st🌍.
So🌍the IFRs of deaths per band likely far more similar.
We'll see for NYC vs 🇧🇷 likely, 🇵🇪 not so sure.
🤏of🧂
6/9
So, keeping that in mind, let's est:
▶️Pop. IFR for equal spread (IFRp)
▶️The wgted IFR of deaths, where avail (IFRd)
Range is:
🇮🇹0.9%
🇳🇬0.09%
Just 1/10 the pop. capacity!
FYI, a⏫dIFR/pIFR means they've had relatively⏫older deaths.
e.g. 🇨🇭🇩🇰, caveat most have⏬deaths.
7/9
Further:
▶️% of possible deaths
▶️% of spread
100% susceptibility unlikely. Sure, IgA/Tcell resistance possible, but, regardless:
▶️implied spread varies hugely
▶️NYC's alone suggests 🇬🇧 more spread likely
▶️If 🇵🇪, not healthcare diffs, likely only one near true HIT.
8/9
Finally, here's how each age fared rel. to🏴🏴
▶️Per 2/9 1/5 >80, means 🇧🇷🇵🇪 much⏫per band
▶️NYC worse, likely⏫density & slower LD speed
▶️NYC&🇧🇷 so similar!? Favellas as dense? Same work ethic?
▶️🇺🇦similar to🏴🏴, protected old better
▶️🇪🇺 more LD, bad at CHs
▶️🇰🇷 best
9/9
Summary, all correlated, not causal.
But, all comparisons must remove big factors for diff🥇
e.g. demographics.
Once you do, assumption flaws become evident.
e.g. 🇵🇪 either
▶️worse healthcare outcomes
▶️or, LD was not effective
Reality, spread⏫in 2nd/3rd🌍than deaths imply.
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