Quote from Navid

We don't need vaccine policemen. Millions of lives saved is a laugher - like to see that data.

Most physicians haven't looked at the vaccine data because they are trained in a couple of lectures in medical school. They really take it on faith.

There are no RCTs. Infrequent but serious immediate harms have to be taken to vaccine court. Long term harms are not ever traced to vaccines.

The CDC has been taken to task by many agencies as being an arm of the Vaccine industry. Did you read those reports - what did you think about that?

As for Covid - getting a flu vaccine will increase the odds of getting Corona-virus infection. See: Assessment of temporally-related acute respiratory illness following

influenza vaccination by Rikin et al. They found a 4.8x in kids < 18.

As for adults, Wolf 2020 https://pubmed.ncbi.nlm.nih.gov/31607599/ shows roughly 30% increased risk for coronavirus.

Quote: "Vaccine derived virus interference was significantly associated with coronavirus and human metapneumovirus;"

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I know Navid that you will address my comment on your CDC SCFR table post shortly.

I have to take you to task again for a slightly careless reading of the Rikin et al paper.

Rikin et al do indeed find that vaccinated children are more likely to suffer ARI than non-vaccinated children.

That is a correlation. It does not, as you assume, imply causation.

Here is another argument for causation.

Children do not all get Flu jab. It is highly likely that those who get it will be those who are more likely (for other reasons) to suffer ARIs. After all, the vaccine protects against Flu ARI.

Thus the findings here do not show what you suppose.

We have gone round this enough with COVID therapy tests - I''d expect you to be familiar with the arguments?

Another point to note is that the figure for Flu in the 14 days post-injection. This does not represent realistic Flu protection because vaccines take some 14 days before immunity is formed. In addition the same issue of those who take the vaccine being those at more risk applies.

As in all other things, obtaining meaningful results from anything except RCTs is very difficult. The antivaxer movement seem to be assiduously ignoring this fact of life.

This particular study, because there is no control for known risk factors (and an expectation that those would be positively correlated with vaccination) has very poor methodology. GIGO.

THH

Quote from Navid

A month ago CDC was using case fatality of 3% in their modeling.

They still are, and they still should. It is ~3% without medical intervention. For example, in the slums of Brazil the hospitals turn poor people away, so ~3% of them die.

I just want to say - whatever some might think, I'm not universally in favour of vaccines. They can have problems. Maybe sometimes they are used when the risk/reward is not good. I just don't like poor arguments being used, and the ones I see here against vaccination, of various types, are remarkably poor.

It is everyone's duty to examine arguments they propagate, check that they are sound, and retract or modify them if later discovered to be poor. I'll happily accept specific vaccines are in fact overall bad if proper evidence is advanced, although in that case I would not generalise, nor assume without strong evidence a global conspiracy to push vaccines. (It is pretty difficult to imagine such a thing).

Not OT for this thread because you can see the same issues of extrapolating results from poor data can apply to the evaluation of vaccines and COVID therapies.

Quote from Navid

A month ago CDC was using case fatality of 3% in their modeling.

Looks lame to me.

Navid, I'm still awaiting your answer to my points (1), (2), (3) above. If you like I'll take silence as a tacit admission that you now understand your mistake, but then you will have to stop quoting your erroneous 0.1% population average.

CFR is not SCFR. Read the definitions carefully. In fact just as we know initial CFR in pandemics is always much higher than final value, this adjusted SCFR (which can only be generated now, with more data) is guaranteed lower than the typical CFR at the start of the US pandemic.

Comparing these two quite different numbers is a category mistake, like confusing CFR and IFR. I'll count it as number 4 in the list. I'm counting these mistakes clearly becasue if you are right then a whole load of no doubt hard working and poorly paid CDC epidemiologists are incompetent and wrong. That is a strong accusation and worth a little embarrassment to get it right.

Factors affecting IFR and CFR:

Other than the usual ones:

demographics (Italy older => worse. UK a bit older => a bit worse)

initial dose - there is pretty good evidence that a very high initial dose (e.g. a care worker exposed directly to patient aerosols at close range over some time) increases severity of the disease and hence death rate

malnutrition etc (not sure what evidence, but you would expect it to have a negative effect)

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).

That is reasonably in line with numbers from Japan and Korea, where the epidemic effectively ended weeks ago. Just about everyone there who is likely to die has died. There are now only 148 critically ill patients in Japan. 5% of total cases died in Japan, but their definition of a case was narrow at first. I think there were many "probable" cases. That is, people who were probably infected but not included in the totals. That does not mean those people were ignored. I believe nearly all were quarantined, and the case trackers looked for people they might have infected. No case brought to the attention of doctors has been ignored, as far as I know.

There are now very few undetected cases in Japan. We know that because there are so few cases, 20 to 40 per day, and they are nearly all traceable. If there were many undetected ones, and asymptomatic people inadvertently spreading the disease, you would see many more untraceable cases appearing.

https://covid19japan.com/

In other news from Japan, the "soft" lockdown ended in Tokyo, the last place it was still in force. Things are not back to normal, but people are back to work, and I think all business and stores are now open. (Many of them never closed.)

Here is an interesting take on the risk of dying from the coronavirus:

https://www.nytimes.com/2020/0…id-19-in-perspective.html

Putting the Risk of Covid-19 in Perspective

Is the risk of dying from Covid-19 comparable to driving to work every day, skydiving or being a soldier in a war?

[Answer: all of the above. Depending . . .]

QUOTE:

. . . Michigan had approximately 6,200 excess deaths during this same time period. That is roughly the same risk of dying as driving a motorcycle 44 miles every day (11 micromorts per day). Living in Maryland during this time would be roughly as risky as doing one skydiving jump a day for that duration (7 micromorts per jump).

Now, if you’re infected with the virus, your odds of dying jump dramatically. Estimates of the fatality rate vary as doctors continue to learn more about this virus and how to care for people sickened by it, but let’s assume it is 1 percent for sake of this discussion. That translates into 10,000 micromorts. That risk is comparable to your chances of dying on a climb in the Himalayas if you go above 26,000 feet, where the tallest peaks, such as Everest and K2, stand (using climbing data taken between 1990 and 2006).

But that risk estimate is for the entire population, with an average age of 38. If you happen to be older, the fatality rate can be as much as 10 times higher, which is just slightly less than flying four Royal Air Force bombing missions over Germany during World War II. . . .

Quote from JedRothwell

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).

That is reasonably in line with numbers from Japan and Korea, where the epidemic effectively ended weeks ago. Just about everyone there who is likely to die has died. There are now only 148 critically ill patients in Japan. 5% of total cases died in Japan, but their definition of a case was narrow at first. I think there were many "probable" cases. That is, people who were probably infected but not included in the totals. That does not mean those people were ignored. I believe nearly all were quarantined, and the case trackers looked for people they might have infected. No case brought to the attention of doctors has been ignored, as far as I know.

There are now very few undetected cases. We know that because there are so few detected cases: 20 to 40 per day. If there were many undetected ones, and asymptomatic people inadvertently spreading the disease, you would see many more untraceable cases appearing.

https://covid19japan.com/

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Welcome to the Jed and THH forum where they ignore data posted, and thrash around.

THHuxley why don't you and Jed figure out what you think the IFR is and then post it to this forum - looks like you disagree again.

Quote from THHuxleynew

In fact just as we know initial CFR in pandemics is always much higher than final value, this adjusted SCFR (which can only be generated now, with more data) is guaranteed lower than the typical CFR at the start of the US pandemic.

Excess mortality in the US was (until now) about 50'000 people during the CoV-9 pandemic. Thus half of dead are just dying with CoV-9 and not because of CoV-9. Switzerland does not even see an excess mortality same for Germany.

So all this talk is based on very shaky ground. Latest data makes us also believe that people having a classic corona infection are protected of CoV-9. Thus 50% are more or less immune. The other good news the CoV-9 antibody produced seems to be long time stable- thus no need for a vaccination - or just try to get a corona cold!

Quote from JedRothwell

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).

This only holds if you believe you do see all infected, what is obviously totally wrong.

Quote from Wyttenbach

This only holds if you believe you do see all infected, what is obviously totally wrong.

No, it does not. Read the document. They estimated total infections, based on excess deaths and other factors.

Quote from THHuxleynew

Navid - 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

(3) You assume that SCFR is the same as IFR. It is not. It is higher (by an assumed 35% under scenario 5 due to asymptomatic cases). It is lower, because shielding of those most likely to die can make the SCFR lower than the whole population mortality rate (IFR). But even if you define IFR as SCFR adjusted for asymptomatic cases you get 0.3% from these figures, not the 0.1% you expect.

I'd like you to address these in detail: I will respond in case you do not understand the above. I've condensed a previously longer post so I'm aware you may need more detail: apologise just i can't bear to type it all again!

PS - accusing others of incompetence, lame math, etc means that your own competence and math needs to be impeccable. I'm sure it will be after you have looked again at the CDC work (and noted what SCFR means and why population average is not correct).

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Let's start with one thing. How did CDC come up with their 0.4% number. You expressed confidence in their numbers, so you understand them. Explain it.

Quote from JedRothwell

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'm afraid not Jed.

CFR = deaths / cases

IFR = deaths / infections

This is much more difficult to calculate because many infections are never recorded as cases. Some, we know, are asymptomatic and will never be detected unless you have widespread whole population testing.

Quote from Navid

Let's start with one thing. How did CDC come up with their 0.4% number. You expressed confidence in their numbers, so you understand them. Explain it.

Sure you weight the 3 SCFR numbers by the number of cases in each age category to get the overall SCFR. I said it above in my post.

Another take on HCQ --

Debunking Fauci's study on Hydroxychloroquine - not a real study (Dr. Chris Martenson)

Another HCQ item --

India backs hydroxychloroquine for virus prevention

https://medicalxpress.com/news…oxychloroquine-virus.html

The Times of India --

HCQ should be continued as preventive treatment for Covid-19: ICMR

Quote from THHuxleynew

I'm afraid not Jed.

CFR = deaths / cases

Not me. I am quoting Worldmeters. Go read their document: https://www.worldometers.info/…s/coronavirus-death-rate/

Quote from THHuxleynew

This is much more difficult to calculate because many infections are never recorded as cases.

They took that into account.

As I said above, it is not likely you will find a large, obvious error in a professionally prepared document. Unless it is from the Georgia Dept. of Health. But hey, at least our governor himself has apologized for the most recent mistakes!

Quote from Lou Pagnucco

Debunking Fauci's study

It wasn't Fauci's.. or the Veteran's Affairs'.. someone else financed this hitpiece on HCQ..

The content of this article is solely the responsibility of the authors and does not
necessarily represent the official views of the National Institutes of Health,"

Quote from THHuxleynew

Sure you weight the 3 SCFR numbers by the number of cases in each age category to get the overall SCFR. I said it above in my post.

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.

Overall 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.

https://www.cbc.ca/news/canada…o-update-may-26-1.5584665

Quote from JedRothwell

You can see that data anywhere!....and millions worldwide.

They don't need to look. Any doctor has seen serious influenza cases. Doctors know damn well that vaccines work, and they are very safe. That's common knowledge.

You need to stop spreading dangerous, pernicious lies. This is not the place for them. If I were in charge here, I would insist you stop.

Your screeds are full of emotion but lack data. Eugenics was a science - and it was common knowledge "what was good for society" based on science that was "damn well proven."

What is dangerous is people who tell you what to believe - like you - and want to silence the debate. A month ago it was all but settled for you, that we have to close down civilization for vaccines. The overblown fear tactics guised as "our best models and science."

This has locked down millions - and will lead to much more death, suffering, and damage than you know about - with millions internationally affected. People who try to stop the conversation are the threat - that is the real threat. Anyone who says "trade your freedom for our safety" is a far more dangerous threat. People have died for freedom; but dying for someone's call to your safety history has shown over and over is from the worst kinds of evil. I'm not going to threaten you - as you have - but I would say as people wake up they too will call you out.

You don't know what the true risk profile of getting more and more vaccines. You don't. We have good evidence they are far less safe than advertised.

We haven't even begun to discuss what goes on in a Moderna vaccine. It is a living experiment.