5 ms·

This is with the "Nowcast" projections on. You can disable them in the page, and this shows a measured 0.7% of cases (less than one percent) as Omicron. That's

by tibbar 5y ago

This is with the "Nowcast" projections on. You can disable them in the page, and this shows a measured 0.7% of cases (less than one percent) as Omicron. That's some aggressive projection model...

Mountain_Skies 5y ago
Probably no worse than the Imperial College London model that was used at the beginning of the pandemic to seed the response path we're all on.
- deleted 5y ago
  [deleted]
- ipspam 5y ago
hn_throwaway_99 5y ago
Agreed, I think it's important to highlight that the 73% is a projection. That said, to be clear, the 0.7% is what was measured the week of 12/4, not more recently.
- ehsankia 5y ago
  Is there a place where we can see the raw count of samples that were sequenced in the last week and what % of them were Omicron vs Delta?
  - sndean 5y ago
    Just sticking to places with it in a simple format, there's S gene target failure rates for San Diego [0] and University of Washington [1]. I don't know if Kristian Andersen's lab has that info anywhere else, but UW has it online somewhere else, just can't reach it on my phone. It looks like both Scripps and UW are listing SGTF rates at >70% now, as of yesterday. Given that San Diego and certain counties within Washington are >70% omicron, the CDC nowcast listing it as 73% (for the nation?) doesn't seem crazy as an average. Edit: I just noticed you asked for sequencing info, but SGTF seems to be a good enough measure. Sequencing is slow, so you'll always be ~1 week out. Andersen's data is particularly good IMHO because they list Ct values <=30 and >30. It's been a pet peeve of mine for some time that certain labs run the PCR tests to Ct >40, since that could be positive with ~1 RNA molecule meaning it's unlikely that's a real infection (at least at the time of the test). [0] https://github.com/andersen-lab/SARS-CoV-2_SGTF_San-Diego https://github.com/andersen-lab/SARS-CoV-2_SGTF_San-Diego [1] https://github.com/proychou/sgtf https://github.com/proychou/sgtf
    - selimthegrim 5y ago
      There's another Omicron strain that evades the S gene failure litmus test
  - r721 5y ago
    https://covariants.org/per-country https://covariants.org/per-country ("The raw data behind these charts comes from GISAID")
deleted 5y ago
[deleted]
throw8932894 5y ago
CDC should remove note about Newcast from website. It gives wrong impression and may confuse people.
ISL 5y ago
If you disable "Nowcast", you go two weeks backward in time. The CDC is doing its very best to give you information here. I've been making Covid-projections since ~May using these data. This is the first time I've seen them emerge on a day other than Tuesday in months -- they got this one to market because it matters. It is my ongoing impression that the people behind these projections are doing the very best they can with the very best data available in the US. If you compare last-week's data in today's release with those released last week, you'll see a substantial refinement as new sequencing data roll in. If you're forecasting covid-trends in the US, this is one of the very best resources you've got. (Also, shout-out to the UK HSA. When the next variant comes, I hope we've gotten our latency and reporting up to your daily Omicron-report and weekly Technical Briefing level. Y'all are helping the whole world, too.)
- dragontamer 5y ago
  > If you compare last-week's data in today's release with those released last week, you'll see a substantial refinement as new sequencing data roll in. They're doing their best, but these "Nowcast" numbers are horribly unreliable. Fortunately, that's not a big deal but hear my whole post out... Last week, two weeks ago was Nowcast as 2.something%. Now the revised numbers is like 11% for two weeks ago. To be fair: the error bars were like 0.1% to 16% on that estimate (so they "weren't wrong"... but with error bars this huge, there's no point trying to get into the nitty gritty). But even today, we can see the "73% Nowcast estimate" as an error bar of 35% to 95%. --------- The error bars are huge, but given the rate at which Omicron outcompetes Delta, we know that Omicron is doubling in roughly every 3 days. With an estimate of 30% (smallest case scenario for Omicron), we'll be at 99.9% by next week. It doesn't matter if we're at 30% today or 95% today. 99.9% Omicron is certain in the near future. We don't know if we're at 30% now or 95% now. But the era of Omicron dominance is among us right now, or maybe even a few days ago. That's incredibly important news, we may not know the exact time or day, but this is the best advanced warning we're gonna get. Omicron is here. Hopefully we all know what the new rules are by now...
  - ISL 5y ago
    Agreed on all points. The SGTF sampling by UW, Yale, and others have been more than sufficient to get a good-enough estimation, in combination with the really excellent work from the UK and Denmark, of what we're facing. Our trajectory for the next ~10+ days is largely locked-in, but strident (and empathetic) leadership may help to blunt the impact in the weeks that follow. It might be Christmas week, but if you limit contacts for the next week or two, you'll put yourself in a much-better place to be able to manage the month to come . May this be the last time humans have to pay so dearly to learn the lesson that exponentially-scaling adversaries are best-confronted when they are small.
asdfasgasdgasdg 5y ago
95% CI includes 35%-95% . . . with intervals that wide, the statistic seems to be questionably useful.
- kristjansson 5y ago
  For a variant that represented 0.0% percent of cases a few weeks ago, that CI is pretty astounding.
  - asdfasgasdgasdg 5y ago
    Sure but, like, we knew this was going to happen either this week or next week, right? It was only a question of when. You know the most interesting thing about this to me is how the absolute number of delta infections decreases so much when omicron comes on the scene. This kinda implies that for at least a significant fraction of the infected, they were exposed to both delta and omicron, and omicron won. I'm really curious how that works. Does anyone know of a clear explanation of the mechanism behind that?

by tibbar 5y ago

This is with the "Nowcast" projections on. You can disable them in the page, and this shows a measured 0.7% of cases (less than one percent) as Omicron. That's some aggressive projection model...

Mountain_Skies 5y ago

Probably no worse than the Imperial College London model that was used at the beginning of the pandemic to seed the response path we're all on.

deleted 5y ago
[deleted]
ipspam 5y ago

hn_throwaway_99 5y ago

Agreed, I think it's important to highlight that the 73% is a projection. That said, to be clear, the 0.7% is what was measured the week of 12/4, not more recently.

ehsankia 5y ago
Is there a place where we can see the raw count of samples that were sequenced in the last week and what % of them were Omicron vs Delta?
- sndean 5y ago
  Just sticking to places with it in a simple format, there's S gene target failure rates for San Diego [0] and University of Washington [1]. I don't know if Kristian Andersen's lab has that info anywhere else, but UW has it online somewhere else, just can't reach it on my phone. It looks like both Scripps and UW are listing SGTF rates at >70% now, as of yesterday. Given that San Diego and certain counties within Washington are >70% omicron, the CDC nowcast listing it as 73% (for the nation?) doesn't seem crazy as an average. Edit: I just noticed you asked for sequencing info, but SGTF seems to be a good enough measure. Sequencing is slow, so you'll always be ~1 week out. Andersen's data is particularly good IMHO because they list Ct values <=30 and >30. It's been a pet peeve of mine for some time that certain labs run the PCR tests to Ct >40, since that could be positive with ~1 RNA molecule meaning it's unlikely that's a real infection (at least at the time of the test). [0] https://github.com/andersen-lab/SARS-CoV-2_SGTF_San-Diego https://github.com/andersen-lab/SARS-CoV-2_SGTF_San-Diego [1] https://github.com/proychou/sgtf https://github.com/proychou/sgtf
  - selimthegrim 5y ago
    There's another Omicron strain that evades the S gene failure litmus test
- r721 5y ago
  https://covariants.org/per-country https://covariants.org/per-country ("The raw data behind these charts comes from GISAID")

deleted 5y ago

[deleted]

throw8932894 5y ago

CDC should remove note about Newcast from website. It gives wrong impression and may confuse people.

ISL 5y ago

If you disable "Nowcast", you go two weeks backward in time. The CDC is doing its very best to give you information here. I've been making Covid-projections since ~May using these data. This is the first time I've seen them emerge on a day other than Tuesday in months -- they got this one to market because it matters. It is my ongoing impression that the people behind these projections are doing the very best they can with the very best data available in the US. If you compare last-week's data in today's release with those released last week, you'll see a substantial refinement as new sequencing data roll in. If you're forecasting covid-trends in the US, this is one of the very best resources you've got. (Also, shout-out to the UK HSA. When the next variant comes, I hope we've gotten our latency and reporting up to your daily Omicron-report and weekly Technical Briefing level. Y'all are helping the whole world, too.)

dragontamer 5y ago
> If you compare last-week's data in today's release with those released last week, you'll see a substantial refinement as new sequencing data roll in. They're doing their best, but these "Nowcast" numbers are horribly unreliable. Fortunately, that's not a big deal but hear my whole post out... Last week, two weeks ago was Nowcast as 2.something%. Now the revised numbers is like 11% for two weeks ago. To be fair: the error bars were like 0.1% to 16% on that estimate (so they "weren't wrong"... but with error bars this huge, there's no point trying to get into the nitty gritty). But even today, we can see the "73% Nowcast estimate" as an error bar of 35% to 95%. --------- The error bars are huge, but given the rate at which Omicron outcompetes Delta, we know that Omicron is doubling in roughly every 3 days. With an estimate of 30% (smallest case scenario for Omicron), we'll be at 99.9% by next week. It doesn't matter if we're at 30% today or 95% today. 99.9% Omicron is certain in the near future. We don't know if we're at 30% now or 95% now. But the era of Omicron dominance is among us right now, or maybe even a few days ago. That's incredibly important news, we may not know the exact time or day, but this is the best advanced warning we're gonna get. Omicron is here. Hopefully we all know what the new rules are by now...
- ISL 5y ago
  Agreed on all points. The SGTF sampling by UW, Yale, and others have been more than sufficient to get a good-enough estimation, in combination with the really excellent work from the UK and Denmark, of what we're facing. Our trajectory for the next ~10+ days is largely locked-in, but strident (and empathetic) leadership may help to blunt the impact in the weeks that follow. It might be Christmas week, but if you limit contacts for the next week or two, you'll put yourself in a much-better place to be able to manage the month to come . May this be the last time humans have to pay so dearly to learn the lesson that exponentially-scaling adversaries are best-confronted when they are small.

asdfasgasdgasdg 5y ago

95% CI includes 35%-95% . . . with intervals that wide, the statistic seems to be questionably useful.

kristjansson 5y ago
For a variant that represented 0.0% percent of cases a few weeks ago, that CI is pretty astounding.
- asdfasgasdgasdg 5y ago
  Sure but, like, we knew this was going to happen either this week or next week, right? It was only a question of when. You know the most interesting thing about this to me is how the absolute number of delta infections decreases so much when omicron comes on the scene. This kinda implies that for at least a significant fraction of the infected, they were exposed to both delta and omicron, and omicron won. I'm really curious how that works. Does anyone know of a clear explanation of the mechanism behind that?