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Thank you for holding the 
#Lockdown!
So important, as ~1 in 12 UK people (5.5 million) might have #COVID19. ~1 in 7 in London.
That would mean there are infected people in every park, in every shop, in every street. It might include you!
Thread w/calculations if interested:
#Lockdown!So important, as ~1 in 12 UK people (5.5 million) might have #COVID19. ~1 in 7 in London.
That would mean there are infected people in every park, in every shop, in every street. It might include you!
Thread w/calculations if interested:
Assume: 14,333 deaths (8958 hosp deaths + 60% for lag + non hosp)
Infection (not case) Fatality Rate: 1%
Days infection to death ~23.5
So 1.4m infected up to 23.5 days ago
~12 days to double (adj. for recovery) so ~2 doublings since
So infections now: ~5.5m. ~1m recovered
Infection (not case) Fatality Rate: 1%
Days infection to death ~23.5
So 1.4m infected up to 23.5 days ago
~12 days to double (adj. for recovery) so ~2 doublings since
So infections now: ~5.5m. ~1m recovered
Model is v.sensitive to inputs, so low confidence + wide ranges apply.
More deaths --> more infections
Higher IFR% --> fewer infs (don't need as many for same deaths)
Longer days to death --> more infs (more time to double)
Higher doubling rate --> more infs
More deaths --> more infections
Higher IFR% --> fewer infs (don't need as many for same deaths)
Longer days to death --> more infs (more time to double)
Higher doubling rate --> more infs
I've added 60% to the DHSC hospital deaths to account for reporting lag + non-hospital deaths.
27 Mar reports were 78% too low. Gap should have narrowed now but non-hosp increasing?
https://ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregisteredweeklyinenglandandwalesprovisional/weekending27march2020 https://twitter.com/ChrisGiles_/status/1247458186300456960?s=20
27 Mar reports were 78% too low. Gap should have narrowed now but non-hosp increasing?
https://ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregisteredweeklyinenglandandwalesprovisional/weekending27march2020 https://twitter.com/ChrisGiles_/status/1247458186300456960?s=20
We were adjusting the infection to death days to account for exponential skew. No longer necessary now growth has slowed. Thanks @cheianov as ever.
12 day doubling is assumed from recent case growth adjusted for assumed recoveries + assumption we're slowing similar to Italy.
12 day doubling is assumed from recent case growth adjusted for assumed recoveries + assumption we're slowing similar to Italy.
UK Government (bizarrely) don't report recovery rates. I'm assuming 18 day average illness duration so counting new cases from past 18 days at 91% and extrapolating to assume "live infections" as 85%, given cases are the more serious.
~1m recovered to date.
~1m recovered to date.
This is a top-down model.
For pro versions that work from deaths, see these from @Imperial_JIDEA, @uniGoettingen, @cmmid_lshtm:
https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-30-COVID19-Report-13.pdf
https://cmmid.github.io/topics/covid19/severity/global_cfr_estimates.html
https://www.uni-goettingen.de/en/606540.html
All low given deaths/growth since + non-hospital + reporting lag additions
For pro versions that work from deaths, see these from @Imperial_JIDEA, @uniGoettingen, @cmmid_lshtm:
https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-30-COVID19-Report-13.pdf
https://cmmid.github.io/topics/covid19/severity/global_cfr_estimates.html
https://www.uni-goettingen.de/en/606540.html
All low given deaths/growth since + non-hospital + reporting lag additions
Another interesting approach via symptom tracking.
Estimates 1.4m symptomatic infections (down from 1.9m).
Then need to add 0-20 yrs and over 69 years infected, all asymptomatic infected (50%?) and change since.
@Join_ZOE @timspector @KingsCollegeLon https://covid.joinzoe.com/post/covid-isolation
Estimates 1.4m symptomatic infections (down from 1.9m).
Then need to add 0-20 yrs and over 69 years infected, all asymptomatic infected (50%?) and change since.
@Join_ZOE @timspector @KingsCollegeLon https://covid.joinzoe.com/post/covid-isolation
It's heartening to see more press references to % infected, not just the "confirmed cases" iceberg tip.
https://unherd.com/2020/04/how-likely-are-you-to-die-of-coronavirus/ @TomChivers
https://news.sky.com/story/coronavirus-the-data-suggests-the-uk-is-on-course-for-many-thousands-of-deaths-11966517
https://telegraph.co.uk/news/2020/03/29/least-16m-people-could-infected-coronavirus-uk-new-estimates/
https://metro.co.uk/2020/03/30/coronavirus-slowing-uk-thanks-social-distancing-measures-12476442/
https://ftalphaville.ft.com/2020/04/04/1586015208000/Imperial-s-Neil-Ferguson---We-don-t-have-a-clear-exit-strategy-/ @jemimajoanna
https://unherd.com/2020/04/how-likely-are-you-to-die-of-coronavirus/ @TomChivers
https://news.sky.com/story/coronavirus-the-data-suggests-the-uk-is-on-course-for-many-thousands-of-deaths-11966517
https://telegraph.co.uk/news/2020/03/29/least-16m-people-could-infected-coronavirus-uk-new-estimates/
https://metro.co.uk/2020/03/30/coronavirus-slowing-uk-thanks-social-distancing-measures-12476442/
https://ftalphaville.ft.com/2020/04/04/1586015208000/Imperial-s-Neil-Ferguson---We-don-t-have-a-clear-exit-strategy-/ @jemimajoanna
Illustration implies total UK death toll of ~69k...
But only if IFR is 1% + we see zero new infections.
If our ICU capacity is overrun, the IFR% will spike.
New infections depends on hard #Lockdown + test/trace/quarantine.
Similar to: http://covid19.healthdata.org/united-kingdom
@IHME_UW
But only if IFR is 1% + we see zero new infections.
If our ICU capacity is overrun, the IFR% will spike.
New infections depends on hard #Lockdown + test/trace/quarantine.
Similar to: http://covid19.healthdata.org/united-kingdom
@IHME_UW
A wave is crashing over our ICUs.
We can't reduce the size of that wave because it's caused by infections from 2-5 weeks ago.
We can improve our readiness by scaling ICUs + protecting NHS staff.
We can stop the wave getting bigger + longer by hard #Lockdown + test/trace/quar.
We can't reduce the size of that wave because it's caused by infections from 2-5 weeks ago.
We can improve our readiness by scaling ICUs + protecting NHS staff.
We can stop the wave getting bigger + longer by hard #Lockdown + test/trace/quar.
It's tempting to think... "There's 14k deaths and #Covid19 kills about 1 in 100, so there must be ~1.4 infections".
The problem is you're nearly right. But those ~1.4m infections were ~3 weeks ago. That's how long it takes to kill.
They've been doubling every ~12 days since
The problem is you're nearly right. But those ~1.4m infections were ~3 weeks ago. That's how long it takes to kill.
They've been doubling every ~12 days since
This isn't the best way of estimating % infected!
We're waiting for people to die, assuming fatality rate to judge how many infections drove those deaths, then using doubling rates to judge infections today.
A better way? Random pop. sample testing! https://twitter.com/JamieWoodhouse/status/1247187400876580864?s=20
We're waiting for people to die, assuming fatality rate to judge how many infections drove those deaths, then using doubling rates to judge infections today.
A better way? Random pop. sample testing! https://twitter.com/JamieWoodhouse/status/1247187400876580864?s=20
Why is estimating # infected more important than just tested "cases"?
Infected people are doing the infecting. The "cases" are in hospital/dead/immune
If you know # infected and # deaths you can assess how deadly this thing really is (IFR%, not just "case" fatality)
Infected people are doing the infecting. The "cases" are in hospital/dead/immune If you know # infected and # deaths you can assess how deadly this thing really is (IFR%, not just "case" fatality)
Telling public % infected helps us comply with #LockdownBJ's 23 Mar speech should have started:
"There are infected people in every train, in every shop, in every park, in every tube... you might even be one of them... please take what I am about to say very seriously..."
This poll shows a dangerous level of complacency across the UK. I suspect this is worse in the real world.
Most people think less than a million are infected! That's what happens when govt + press only talk about the "confirmed cases" iceberg tip. https://twitter.com/JamieWoodhouse/status/1245291470107672576?s=20
Most people think less than a million are infected! That's what happens when govt + press only talk about the "confirmed cases" iceberg tip. https://twitter.com/JamieWoodhouse/status/1245291470107672576?s=20
"Total infected" tells us how many people are going to be coming through our ICU capacity in the next few weeks and whether that will be overrun.If it is, #Covid19 will kill more than 1%. When you run out of ICU beds / ventilators, many more die as in Italy/Spain.
If we'd started projecting total infected from day one (ideally via. regular pop. sample tests), we might have acted sooner.
We might also have persuaded people to comply better with our weak #Lockdown.
Instead... "a national scandal" @richardhorton1 https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30727-3/fulltext
We might also have persuaded people to comply better with our weak #Lockdown.
Instead... "a national scandal" @richardhorton1 https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30727-3/fulltext
A powerful visualisation of deadly UK #Covid19 complacency:
"Right things... at the right time..." or "Too little, too late"?
H/t @Imperial_JIDEA
"Right things... at the right time..." or "Too little, too late"?
H/t @Imperial_JIDEA
Amateur epidemiologists like me are annoying, but as long as we have pro epidemiologists saying things like:
- 1000x deaths or
- "2-5x cases" or
- 734k or
- 50%+ or
- "We have no way of knowing" (we do - pop sample tests!)
It feels useful to have a top down sanity check?
- 1000x deaths or
- "2-5x cases" or
- 734k or
- 50%+ or
- "We have no way of knowing" (we do - pop sample tests!)
It feels useful to have a top down sanity check?
Thanks to data people grappling w/this critical estimate - how many are really infected?
@TomChivers @EdConwaySky @alexwickham @Ashley_J_Kirk @PaulNuki @AlbertoNardelli @nicholascecil @jburnmurdoch @jemimajoanna @MaxCRoser @AdamJKucharski @tomaspueyo @StefanFSchubert @cheianov
@TomChivers @EdConwaySky @alexwickham @Ashley_J_Kirk @PaulNuki @AlbertoNardelli @nicholascecil @jburnmurdoch @jemimajoanna @MaxCRoser @AdamJKucharski @tomaspueyo @StefanFSchubert @cheianov
