Display MoreOverall our Canadian Politicians have been
doing a good job leading the
Country fighting CV.
But this report does not look good
for Toronto and surrounding area.
How about we stop putting an army of patrol officers out - and suit them up to go help these people in the nursing homes. 77% of deaths are from nursing homes.
All you need to know is that this is not about helping the old people, they are collateral damage. Hope someone is held accountable, I highly doubt it.
We haven't even begun to discuss what goes on in a Moderna vaccine. It is a living experiment.
Apparently, a lot more goes on than making the vaccine: https://www.nydailynews.com/co…xaqw2s5gd3etvu-story.html
Researchers from Stanford Medicine are testing the drug interferon-lambda to see if t’s effective in treating mild cases of COVID-19.
The data just presented in Lancet's HCQ debunking paper --
"HCQ or CQ with or without a macrolide treatment of COVID-19: a multinational registry analysis"
-- appears suspicious.
The French HCQ proponent, Didier Raoult, examined the data and points out that the nation-to-nation
and continent-to-continent comparison data look improbably uniform and "massaged".
Peak Properity Video - Grim Milestone: 100k+ US Coronavirus Deaths
Here is an excellent analysis of the death rate in the U.S., based on stats from New York. This covers a variety of topics such as age, comorbidity, and herd immunity.
https://www.worldometers.info/…s/coronavirus-death-rate/
Conclusion:
Infection Fatality Rate (IFR) = Deaths / Cases = 23,430 / 1,694,781 = 1.4% (1.4% of people infected with SARS-CoV-2 have a fatal outcome, while 98.6% recover).
I believe that 1.4% IFR only applies to New York, which is one of the hardest hit areas in the world. Everywhere else, the IFR is lower, and in most cases much lower. The latest CDC "Symptomatic Case Fatality Rate (SCFR)" for the US is .4%. If they (CDC) would have included the ~35% asymptomatic cases they excluded for some reason I do not understand, it would be an IFR (not a SCFR) of .26%, as noted by Navid, and THH.
That CDC IFR of .26%, is in line with the latest studies, which are falling within the range of IFR 0.2 - 0.4 worldwide. Of course, if broken down by age group, the IFR is much higher for those >65.
IMO, there has been some confusion created by the various terms used by Epidemiolgists since the beginning. They seemed to have taken notice, and simplified the issue by settling on IFR/CFR, so those relying on their data could compare apples to apples. That is why I am scratching my head over the CDC's using this SCFR.
And the only people who do get the flu are those who are too stupid to get a vaccine.
Painting with a pretty broad brush there Jed
My wife gets a flu vaccine and I don’t,
Neither of us have had the flu in over 15 years.
I’m not stupid, I’m an engineer, most people think I’m a pretty sharp guy.
I think maybe you should switch to decaf.
Good humor!
Display MoreNavid - I am so sorry. I posted earlier detailing why you are very wrong about the CDC planning document. It was quite long. I think I never submitted it!
OK - so your errors are as follows:
(1) You say CDC take an average of stratified age-group figures. WRONG. The Scenario 5 figures would average to 0.66% were that true, they give 0.4% - there are quantisation errors but they cannot be that big. You accuse CDC of incompetence, I'd say not checking what they actually did, and assuming it is something (wrong) that the figure show it could not be, is wrong. See (2) below to see what CDC acttually did and why it is correct.
(2) You say that correct average is a population-weighted average. WRONG. Look at the legend in the table. This is SCFR "Symptomatic case fatality ratio". That is not the same as IFR, and you need to weight the symptomatic cases by how many symptomatic cases in each stratified by age bin have occurred. Now, as we know, symptomatic cases are more likely for older bins, hence this explains why your population average is completely wrong. The CDC average is correct, it is a symptomatic case number weighted average
THHuxleynew your eyes see what they want to see. The average would be 0.52%, not 0.66% as you state. Your eyes missed a zero in the first value of 0.0005.
Navid is right in the fact that the "overall" value of 0.004 doesn't properly match the age distribution. Their calculation also proves that the age distribution of symptomatic cases does not match the age distribution of the whole population.
The data just presented in Lancet's HCQ debunking paper --
What was the Lancet editor smoking?
No timing... No zinc..
Like an airbag acting after the accident..
Malaysia and Costa Rica are thinking...
"we cease HCQ .. and the deaths go up?"
" WHO will resurrect us? "
Thanks Lou..
Nigeria to continue with CQ, HCQ.
I don't understand this logic. What is the point of doing this other than to goose numbers higher? Are you saying that if there was a 10% fatality rate in the group aged 80+ (w/ 100 cases) and 1% fatality rate in group 0-60 (w/ 10 cases) -- you would weight the 80+ group higher? Thus this would mean a (.1 * 100/110 + 0.01 * 10/110) weighting = 0.0918 = 9.18% aggregate fatality rate?
What I do believe is that these numbers are goosed. I went back over the math and it actually was 0.27% fatality rate if you take their numbers and apply to the population.
However, the 35% Percent of infections that are asymptomatic seems to be a gross under-statement given population data we have already.
Navid.
If you bother to read the table you are critiquing, it explains this is a symptomatic case fatality ratio. This includes (estimated) people with symptoms who do not go to hospital, but not asymptomatic cases. They do comment on the proportion of asymptomatics.
It is good detailed work but more subtle and complex than you were thinking when you made that "they are incompetent and have got it wrong" critique.
In fact, they got it right (as far as I can tell) and you (I am sure) got it wrong.
Why do they want SCFR, rather than some "if 100% caught it what is the death rate IFR"? Because it is the best figure for estimating likely future use of health resources and propagation of the epidemic.
Another recent report on ivermectin ---
Breakthrough Drug: Ivermectin Shows 'Astounding' Results Against Coronavirus
THHuxleynewyour eyes see what they want to see. The average would be 0.52%, not 0.66% as you state. Your eyes missed a zero in the first value of 0.0005.
Navidis right in the fact that the "overall" value of 0.004 doesn't properly match the age distribution. Their calculation also proves that the age distribution of symptomatic cases does not match the age distribution of the whole population.
Julian - thanks for the 0.0005 correction which I agree, and which does not, interestingly, alter my argument at all, unless you reckon rounding of all numbers could possibly generate 0.004 by rounding the straight average of the unrounded figures. In that case you cannot prove that Navid's assertion that CDC incorrectly took a straight average is wrong, though equally he has no evidence that assertion is right.
I know, and have been explicitly saying, that 0.4% does not match the age distribution. That is the whole point, because you need to average over cases, not people. And cases are highly skewed WRT age. Which I said in my original post...
Ok maybe I was wrong about the solar radiation, apparently we are in a solar minimum, I am no astrophysics. Testing it on some seedlings. If they grow fine then it is ok. But did anyone get round to a spectral analysis? I just worried about skin cancer if they are out in it too much, horrible illness. And people think high factor sunscreen it totally effective when it's not that good at blocking shortwave UV radiation.
Sorry to be boring repeating myself, all the scientific evidence is in the Wang et al and Gordon et al papers, you can't argue with dose response curves. Ivermectin will potentiate the effect of HCQ with Zn and avigan and remdesivir. Simple as that. Run a clinical trial please get in with it, I might test it here if anyone if is up for it? Can't your contact with David King do it, I have had not much luck with UCL, all my close friends there have passed away now. Sad, but but Gertrude was my closest friend.
Here some real data about Excess Mortality from theEconomist posted on a GitHub archive file.
All countries:
https://github.com/TheEconomis…output-data/excess-deaths
Just the USA compiled:
united_states_excess_deaths.pdf
New York is dramatic with a factor 3 in the worst weeks!
https://www.biorxiv.org/conten…26.116020v1.full.pdf+html
simprevir potentiates remdesivir - combinations have better than additive suppression of COVID in vitro.
This type of drug combination repurposing is likley to lead to much better therapies eventually (even though remdesivir itself is pretty much rubbish).
Everywhere else, the IFR is lower, and in most cases much lower.
some much lower...… true. Often it seem that NYC and cost areas try to control the narratives
and the "fly over" parts are ignored. One size does not fit all.
not a lot of cases or apparent infection in this area.
but still in lockdown.
FYI, here are the numbers for my county (way out W)
deaths/cases = 11.3%
deaths/tests (of those requesting testing) =0.07%
verified cases / population = 0.025%
cases / testing ( of those requesting testing) = 0.64%
tests/population 3.9%
deaths/ population 0.0030%
and the ages vs cases (for this county are
| 0-9 | 0.00% |
| 10-19 | 16.67% |
| 20-29 | 11.11% |
| 30-39 | 16.67% |
| 40-49 | 11.11% |
| 50-59 | 16.67% |
| 60-69 | 5.56% |
| 70-79 | 16.67% |
| 80-89 | 5.56% |
| 90+ | 0.00% |
Because it is the best figure for estimating likely future use of health resources and propagation of the epidemic.
How did they come up with the 0.4% number and what value is there in it? (I know you said the # of cases was involved - where is that data?)
