To Jun11 for🏴
👉Lon/Manc/Liv Google Mobility
👉Infs implied from ONS/PHE deaths/cases
👉Gradient of infs from deaths
👉Its correl to Lon mobility
Plotting detail👇
👉1stLD: as this zoom in shows, its reduction occured before so was voluntary, fear induced, but without furlough, and business grants, how could it have been sustained without bankruptcy? If we compare on this outcome to 🇸🇪, our strategy was better.
2/5
👉pre 2ndLD: Liv/Manc were main drivers of deaths going into Tier3++ LD in Sept/Oct, with Liv cases peaking Sep28, hence UK deaths flattening before 2nd LD, mobility clearly fell in both
👉2ndLD: had schools open, so saw less mobility drop, borderline enough to turn infs
3/5
👉pre 3rdLD: per these inlaid maps, Tier4+SchoolsClosed spread across the UK from Dec20. It seems clear compliance was voluntarily around Xmas with the mobility drop stabalising by Dec28
👉3rdLD: Jan4 did not change mobility level, furlough/grants have sustained this since
4/5
It's clear LDs lowered mobility. Annoying only full LDs with school closures, 1st/3rd, solidly turned infs.
But, the 2nd LD was enough, until the Kent variant.
With better adherence to lesser NPIs, masks etc, could we have made tiered local with schools open work?
5/5
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We've all sorted worldometer's table by deaths/1m, seen the data in the blue bars (to Feb6), and thought, wow 🇬🇧's pretty bad.
But, we're all getting our comparisons so wrong.
i.e. red bars are d/1m just for 50-59yr olds.
Why so different?
Follow me to open your eyes.
1/10
Main cause, 2🔑factors:
▶️Demographic: a pop's d/1m figure is still wgted by age, so fewer 80+ it's lower
▶️Policy: e.g. 🇩🇪's just managed spread better
Re-ranking most2least aging, a pattern emerges.
For a younger pop to have a high d/1m, it's had more spread & deaths.
2/10
So how much do demographics vary?
Here for:
▶️the countries so far
▶️adding a few more
▶️plus, the world
Are the props. each 10yr age band make up.
50% marks median age, so:
Italy 🇮🇹 47
Eng🏴&Wal🏴 41
🌍 30
Nigeria🇳🇬 just 18