Coronavirus science and statistics(no politics)

Snicky

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This certainly seems to go against the narrative.

 

sliper

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The red lines are 14 days after each of your lockdown dates. What's your reasoning that a lockdown on the 5th November with falling rates didn't combine to produce a complete drop in hospital patients? Purely because it was a variant (that then responded within 14 days of the next lockdown in exactly the same way with hospital figures?)

View attachment 3784

All three peaks clearly show the rate of increase starting to slow down BEFORE lockdown. The "inflection point" is that point where an exponential upward curve starts to flatten.. And this occurs before each peak. If lockdowns caused the decline you would expect an inverted V shape with rates continuing to climb exponentially AFTER lockdown.. Because it would take at least two weeks after lockdown for patients in hospital/infections to start falling. If it was lockdown that caused the decline why did the rate of increase start to decline BEFORE lockdown ?
 
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jakehake

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All three peaks clearly show the rate of increase starting to slow down BEFORE lockdown. The "inflection point" is that point where an exponential upward curve starts to flatten.. And this occurs before each peak. If lockdowns caused the decline you would expect an inverted V shape with rates continuing to climb exponentially AFTER lockdown.. Because it would take at least two weeks after lockdown for patients in hospital/infections to start falling. If it was lockdown that caused the decline why did the rate of increase start to decline BEFORE lockdown ?
Welcome back. According to Snicky the dates of lockdown I’ve added are in green. Mine and your definitions of “flatten” would appear to differ as I’d personally say the lines look much flatter 2 weeks after lockdown than in the first week after a lockdown. I’d also go do far as saying rates continued to increase exponentially after lockdown looking at those charts. What is your definition of “flatten” at the point the green line intersects?
I assume the stats are on the dashboard too that produce the image2CC2DA7E-CD3D-4059-B2B3-D2A6D726D25B.jpeg
 

Snicky

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Welcome back. According to Snicky the dates of lockdown I’ve added are in green. Mine and your definitions of “flatten” would appear to differ as I’d personally say the lines look much flatter 2 weeks after lockdown than in the first week after a lockdown. I assume the stats are on the dashboard too that produce the imageView attachment 3798
The article did mention infections, not hospital admissions. There is a lag of a couple of weeks I think.
 
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jakehake

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The article did mention infections, not hospital admissions. There is a lag of a couple of weeks I think.
Also just to quote sliper “Because it would take at least two weeks after lockdown for patients in hospital/infections to start falling.”

the green and red line are two weeks apart. So according to that “two weeks after lockdown, patients in hospital started falling”

so I’m kind of lost what point sliper has argued against?
 
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jakehake

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But to be honest Me and my kids have met my parents and family for the first time in 18 months today.

If people still want to argue that lockdowns didn’t have a desired impact on hospital numbers then knock yourselves out.

The December/January wave and government wavering showed exactly what happens when lockdowns were on and off and if people really want to pretend they contributed nothing then knock yourselves out.

They might not have been the right answer or they might not be the long term answer but they made a difference to what was happening with infections and hospital usage, that much is clear
 

Snicky

Thorium Indium Potassium
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But to be honest Me and my kids have met my parents and family for the first time in 18 months today.

If people still want to argue that lockdowns didn’t have a desired impact on hospital numbers then knock yourselves out.

The December/January wave and government wavering showed exactly what happens when lockdowns were on and off and if people really want to pretend they contributed nothing then knock yourselves out.

They might not have been the right answer or they might not be the long term answer but they made a difference to what was happening with infections and hospital usage, that much is clear
I’m not sure anyone is arguing that Jake, not on here anyway. More like it’s not as cut and dried as it seems and that the chances of them happening again in the same way are low. There may be a better way.
 
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jakehake

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I’m not sure anyone is arguing that Jake, not on here anyway. More like it’s not as cut and dried as it seems and that the chances of them happening again in the same way are low. There may be a better way.

I think you’ve made a giant leap there. We’ve (including myself)already stated that the long term impacts and comparative results are going to take some time to establish.

“there may be a better way” No doubt. That’s what research, time and hindsight give you along with all the other analysis and again, I’ve not disputed that in any of my last posts.

All I’ve pointed out based on the dates you provided earlier is that the statistics provided by the NHS show some form of correlation to those dates. It isn’t perfect, nor is it definitive, but any form of analysis can show that especially with the second and third lockdown imposed, and the shape of the graph it shows it had an evident impact when/if a lockdown was in place.

25205CE1-0FCB-46F8-B644-49AF7FCDF436.jpeg

If that chart was put in a GCSE paper last week and the question was give one feature of the trend/line between the green and red line pairs I can bet your bottom dollar that the Mark scheme would say more along the lines “increasing, rising, many more people in hospital by the second line”. I bet you wouldn’t get a Mark for saying “flat, already flattened, not increasing as much”, yet apparently that’s what it shows according to some
 

sliper

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Also just to quote sliper “Because it would take at least two weeks after lockdown for patients in hospital/infections to start falling.”

the green and red line are two weeks apart. So according to that “two weeks after lockdown, patients in hospital started falling”

so I’m kind of lost what point sliper has argued against?

I'll concede on the point...that graph doesn't show that. I assumed the red lines were lockdown.

From the Spectator..

"In a peer-reviewed paper now published in Biometrics, I find that, in all three cases, Covid-19 levels were probably falling before lockdown. A separate paper, with colleague Ernst Wit, comes to the same conclusion for the first two lockdowns, by the alternative approach of re-doing Imperial College’s major modelling study of the epidemic in 2020. In light of this, the Imperial College claim that new infections were surging right up until lockdown one — causing about 20,000 avoidable deaths — seems rather questionable."

I had in mind a similar analysis to the peer reviewed data I had seen earlier and linked to in the quote.. and assumed wrongly that the red lines were the dates of lockdown.

 
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