Coronavirus (2022) thread

[roubaixtuesday]

Interesting comparison of alpha, delta and omicron waves.

It's a log plot, so equal distance between lines means equal ratio between those measurements.

The graph is normalised to the January '21 alpha peak, so everything else (cases, hospitalisation, ICUs, deaths) is relative to the peak then.

Timeliness are shifted to give the same peak in '21, ie hospitalizations are lagged by 1-2 weeks, deaths are by 3-4 weeks etc, according to how the peaks of each lagged in '21.

Preamble over, what do we see:

Hospitalizations and deaths fell from alpha to delta by a lot relative to cases. This is due to the vaccination programme.

From delta to omicron there's little difference in hospitalisation or death; omicron seems near equally likely to hospitalise or kill you as delta.

What there is a big change in is severe disease needing ICU - the gap between cases to icu admissions widens a lot.




ourworldindata allows you to make your own plots of this sort now, but I've not tried myself. Perhaps the "South Africa Data was ignored" crowd should try it.

From Paul Mainwood on twitter who explains a bit about why it's useful better than I have, I think.

https://mobile.twitter.com/PaulMainwood

 

[unicorn]

Both that and the movie Contagion eleven years ago show very well how we have seen this kind of thing coming for ages and in effect still just sleepwalked into the consequences. Though thankfully science - especially in vaccines - had progressed just enough in that decade since 2011 and was fast tracked through 2020 - to mean we could save possibly hundreds of thousands of lives globally that we might not have otherwise done with Covid.

When I watched Contagion last year I assumed it was made-for-TV movie released in 2020. The fact it was 11 years old and contained all the same references ("r" rates, social distancing etc) was eerie..

 

[BlueAnorak]

Interesting comparison of alpha, delta and omicron waves.

It's a log plot, so equal distance between lines means equal ratio between those measurements.

The graph is normalised to the January '21 alpha peak, so everything else (cases, hospitalisation, ICUs, deaths) is relative to the peak then.

Timeliness are shifted to give the same peak in '21, ie hospitalizations are lagged by 1-2 weeks, deaths are by 3-4 weeks etc, according to how the peaks of each lagged in '21.

Preamble over, what do we see:

Hospitalizations and deaths fell from alpha to delta by a lot relative to cases. This is due to the vaccination programme.

From delta to omicron there's little difference in hospitalisation or death; omicron seems near equally likely to hospitalise or kill you as delta.

What there is a big change in is severe disease needing ICU - the gap between cases to icu admissions widens a lot.

View attachment 34724


ourworldindata allows you to make your own plots of this sort now, but I've not tried myself. Perhaps the "South Africa Data was ignored" crowd should try it.

From Paul Mainwood on twitter who explains a bit about why it's useful better than I have, I think.

https://mobile.twitter.com/PaulMainwood

Nice try but no cigar:
-> 45%+ are admitted to hospital for reasons other than Covid and most of those that die, do so because they tested +ve within 28 days of their death date.
-> 90%+ are on ventilators for Covid because they didn't get vaccinated.
THE PUBLISHED STATS ARE BROKEN. So your diagrams are totally incorrect.

 

[roubaixtuesday]

Nice try but no cigar:
-> 45%+ are admitted to hospital for reasons other than Covid and most of those that die, do so because they tested +ve within 28 days of their death date.
-> 90%+ are on ventilators for Covid because they didn't get vaccinated.
THE PUBLISHED STATS ARE BROKEN. So you diagrams are totally incorrect.

There have always been incidental admissions and deaths. You'd expect them to be proportional to prevalence.

Which part of what I posted specifically do you disagree with, or do you purely wish to express inchoate rage - shouting doesn't make make you correct.

 

[True_Blue69]

Interesting comparison of alpha, delta and omicron waves.

It's a log plot, so equal distance between lines means equal ratio between those measurements.

The graph is normalised to the January '21 alpha peak, so everything else (cases, hospitalisation, ICUs, deaths) is relative to the peak then.

Timeliness are shifted to give the same peak in '21, ie hospitalizations are lagged by 1-2 weeks, deaths are by 3-4 weeks etc, according to how the peaks of each lagged in '21.

Preamble over, what do we see:

Hospitalizations and deaths fell from alpha to delta by a lot relative to cases. This is due to the vaccination programme.

From delta to omicron there's little difference in hospitalisation or death; omicron seems near equally likely to hospitalise or kill you as delta.

What there is a big change in is severe disease needing ICU - the gap between cases to icu admissions widens a lot.

View attachment 34724


ourworldindata allows you to make your own plots of this sort now, but I've not tried myself. Perhaps the "South Africa Data was ignored" crowd should try it.

From Paul Mainwood on twitter who explains a bit about why it's useful better than I have, I think.

https://mobile.twitter.com/PaulMainwood

Youre dragging the arse out of this now mate. It’s over, we’ve got through what will hopefully be there final wave and we should all move on.

 

[roubaixtuesday]

Youre dragging the arse out of this now mate. It’s over, we’ve got through what will hopefully be there final wave and we should all move on.

Bizarre. In what way is that dressing the star out of anything. The desire to stop people posting about Covid is weird.

 

[The Light Was Yellow Sir]

Interesting comparison of alpha, delta and omicron waves.

It's a log plot, so equal distance between lines means equal ratio between those measurements.

The graph is normalised to the January '21 alpha peak, so everything else (cases, hospitalisation, ICUs, deaths) is relative to the peak then.

Timeliness are shifted to give the same peak in '21, ie hospitalizations are lagged by 1-2 weeks, deaths are by 3-4 weeks etc, according to how the peaks of each lagged in '21.

Preamble over, what do we see:

Hospitalizations and deaths fell from alpha to delta by a lot relative to cases. This is due to the vaccination programme.

From delta to omicron there's little difference in hospitalisation or death; omicron seems near equally likely to hospitalise or kill you as delta.

What there is a big change in is severe disease needing ICU - the gap between cases to icu admissions widens a lot.

View attachment 34724


ourworldindata allows you to make your own plots of this sort now, but I've not tried myself. Perhaps the "South Africa Data was ignored" crowd should try it.

From Paul Mainwood on twitter who explains a bit about why it's useful better than I have, I think.

https://mobile.twitter.com/PaulMainwood

Are you sure that’s what it says?

 

[roubaixtuesday]

Are you sure that’s what it says?

View attachment 34735

The reason for using the log plot is that the ratios are clearer. Impossible to judge the linear one by eye. I pointed at Mainwood's that which exclaims better than I did, as I said.

But to answer the question, no, I'm not sure that's what it shows, it's just the impression it gives to me. Do you take something different from it?

 

[feedthegoat27]

When I watched Contagion last year I assumed it was made-for-TV movie released in 2020. The fact it was 11 years old and contained all the same references ("r" rates, social distancing etc) was eerie..

Yeah I only watched it for the first time sometime last year.
Pre-Covid I'd never even heard the term 'social distancing' in any context that I can remember.
It's almost a little too close to a documentary for comfort.

Maybe Hollywood knew something we all didn't?
Maybe it's all one massive conspiracy that has been brewing since 2011?
Maybe the conspiracy theory nutjobs are on the money about all their other batshit crazy ideas?!

Nahhhhhhh.

Wouldn't be surprised to see a Contagion 2 in the pipeline before long.

 

[The Light Was Yellow Sir]

The reason for using the log plot is that the ratios are clearer. Impossible to judge the linear one by eye. I pointed at Mainwood's that which exclaims better than I did, as I said.

But to answer the question, no, I'm not sure that's what it shows, it's just the impression it gives to me. Do you take something different from it?

The linear scale visually demonstrates a powerful how measures the vaccines have severely weakened the link between the measures, is my take.