E
Ed Lee
Guest
On Friday, February 4, 2022 at 1:10:24 PM UTC-8, gnuarm.del...@gmail.com wrote:
OK, quick pull of some rough estimates:
01: [30893] | 07%(00045501) 92%(00614241) 01%(00004077) (00670000)
02: [13434] | 03%(00021676) 76%(00637099) 16%(00132164) (00832000)
03: [15960] | 04%(00037127) 52%(00444495) 38%(00330206) (00860000)
04: [07619] | 02%(00035285) 32%(00457022) 59%(00848353) (01430000)
05: [06773] | 12%(00339820) 19%(00523786) 60%(01675535) (02800000)
06: [08068] | 03%(00066001) 08%(00204822) 85%(02134978) (02500000)
07: [10431] | 06%(00111590) 17%(00335155) 71%(01417314) (02000000)
Column:
1: [sample size] 2:Xi/B ratio(cases) 3:Xi/C ratio(cases) 4: Omicron ratio(cases) 5weekly cases)
On Thursday, February 3, 2022 at 11:21:59 AM UTC-5, Ed Lee wrote:
On Friday, January 28, 2022 at 6:41:17 PM UTC-8, gnuarm.del...@gmail.com wrote:
On Friday, January 28, 2022 at 6:08:05 PM UTC-4, Ed Lee wrote:
On Friday, January 28, 2022 at 12:26:25 PM UTC-8, gnuarm.del...@gmail.com wrote:
On Friday, January 28, 2022 at 2:57:45 PM UTC-4, Ed Lee wrote:
On Friday, January 28, 2022 at 10:42:16 AM UTC-8, gnuarm.del...@gmail.com wrote:
The ppm number may be the more relevant number if comparing different population centers, but while comparing the same population at different times the count is sufficient and essentially the same thing. At least until the pandemic starts killing enough people that it reduces the size of the population significantly.
Yeah, it looks like the death rate will be increasing for a bit longer though.
This makes me wonder about the rate of infection from strains other than omicron. Until the rates of infection get large enough to impact the number of available hosts, viral strains do not compete. I would love to see a curve of US infections that excludes the omicron strain or any similar strains allowing view of delta and the earlier strains so the progression of non-omicron strains can be compared.
I think it would provide useful insight to see if there is indeed a human response to the pandemic when a new strain spreads. It may result in more measures to not spread the disease so that the earlier strains have lower infection rates while the new strain proceeds to grow until the measures are effective enough to lower that. I can\'t think of another reason why the omicron variant would be reversing so quickly. But I have my doubts as I don\'t see where many restrictions have been enacted where I spend time.
Yes, i am watching closely how the two strains are coexisting. During the Delta wave, Xi (D614G) was fairly constant, and almost recovering in Nov, while Delta disappeared. If Omicron can exhaust Xi, by using up all the fuel, perhaps the end is in-sight.
CDC claims Omicron is 99.9%. I am not ready to confirm it yet. According to latest data, Omicron is close to 85%, but Xi is still around 11%.
Fuel? What are you talking about?
Yes, vulnerable people.
That term is used to refer not to people who can catch the virus, but to people who will be suffer morbidity or death. In any event, the total infected by omicron in the US is only around 23 million, still far from enough to impact infection rates of other strains.
If you mean uninfected people, there\'s no evidence we have even approximated this yet. It\'s not even clear as to which strains provide immunity to which other strains that I\'ve seen. I have read that some funny things are going on with omicron in that regard.
Just like fighting fire with fire, you don\'t need to exhaust all fuel. As long as you stop the path of motion, it could be stopped.
Whatever. I\'m trying to talk about the virus. The omicron variant has not impacted the population enough to cause it\'s own spread to be impacted.. Even if it had, the slowdown and reversal would not be this quick. There are other issues at play.
It\'s slowing down in dense population area. The peak was around 85% Omicron, but Xi is coming back at 25%. I believe Xi is doing most of the killings.
Week:
1: (30893) | 7% 92% 1%
2: (13434) | 3% 76% 16%
3: (15960) | 4% 52% 38%
4: ( 7619) | 2% 32% 59%
5: ( 6773) | 12% 19% 60%
6: ( 8068) | 3% 8% 85%
7: ( 7273) | 6% 19% 68%
Column:
1: Samples
2: Xi Class B
3: Xi Class C
4: Omicron
No evidence of Xi Class A (Alpha/Wuhan) or Delta.
When you work with percentages, it tells you a lot less than working with absolute numbers. But the data you have is strange and you can\'t explain to anyone else how you come up with it, so...
OK, quick pull of some rough estimates:
01: [30893] | 07%(00045501) 92%(00614241) 01%(00004077) (00670000)
02: [13434] | 03%(00021676) 76%(00637099) 16%(00132164) (00832000)
03: [15960] | 04%(00037127) 52%(00444495) 38%(00330206) (00860000)
04: [07619] | 02%(00035285) 32%(00457022) 59%(00848353) (01430000)
05: [06773] | 12%(00339820) 19%(00523786) 60%(01675535) (02800000)
06: [08068] | 03%(00066001) 08%(00204822) 85%(02134978) (02500000)
07: [10431] | 06%(00111590) 17%(00335155) 71%(01417314) (02000000)
Column:
1: [sample size] 2:Xi/B ratio(cases) 3:Xi/C ratio(cases) 4: Omicron ratio(cases) 5weekly cases)