Originally Posted by blueash (Post 1750133)

I don't know what "relative testing" means to you. But I can reply to your misunderstanding of the Stanford study. Click if you want to read it yourself.

None of the tests were for the Wuhan virus That is not a medical term. The CDC has not ever produced a daily number. The numbers are produced by states individually and reported on media sources.

The Stanford study was NOT random. It was done in a county with the 4th highest number of COVID cases in California. They did not go out and randomly sample people for antibodies. Instead they placed an ad on Facebook to recruit people who volunteered to have their blood drawn for antibodies. Does this seem to be a good representation of the population, or maybe, just maybe, it would interest people who wanted to know if they'd been infected because of a mild illness or exposure where they couldn't get nasal swab tests done?

The study likely includes more positive people than a random sample would contain. The authors report that their volunteers were not representative of the county at large. It included far too many middle age white females. Of 3330 samples, only 50 were positive, a rate of 1.5% on a sample I believe tested higher than a random sample.

But there is more: The test kit being used is not FDA approved. The kit was tested for accuracy using known blood samples.


Sensitivity means it says positive if you are positive. So between 13 and 28% of people who are positive are mistakenly reported as negative. You are missing positives.
More importantly between 0.1 and 1.7% of negative are being mistakenly reported as positives.
If you test report 3330 tests, from 3 to 56 of your true negatives are being reported a positive. Guess how many positive tests they got.. 50. All of their positives could be false positives within the margin of error of the test. If you use the 99.5% specificity, then 16 of your positives are really negative, a full 1/3 wrong. Be very cautious when your finding is entirely in the margin of error.

And there's more to follow:

Originally Posted by blueash (Post 1750206)

Lastly, and thanks for your patience and persistence..
Your choice to mention the death rate
is so misleading. I believe the point you are making is that influenza has an estimated death rate of 0.1%, so if that is the "true death percentage" for COVID, it is no worse than seasonal flu.

Fail.
The calculation by the CDC of the fatality rate for influenza is complex. You can read about how they do it HERE and HERE. Please do so and return. I'll wait

Welcome back. As you learned the flu estimate is based on a calculation, a model, which has as its inputs many factors. How many people are presenting to hospitals and selected outpatient clinics with flu-like illness, how many people after the end of flu season report that had significant flu symptoms even if they did not go for medical care, how many excess deaths there are from diseases known to have flu be a possible trigger, such as death from pneumonia, and information about how often flu tests are being done and how often they are positive at selected hospitals.

The influenza illness death rate is not a count based on what is on a death certificate. It is a much much higher number based on a statistical process looking for any deaths that might be, perhaps for lack of a better term, flu adjacent. The estimate of how many people had the flu includes in its number a best guess of all those with flu, not just those seen in a hospital, or those with a positive flu test, but everyone who had a flu-like illness. This give a large number for the denominator, with estimated deaths as the numerator.

This is totally, completely, astronomically, amazingly, different than the way COVID is now being calculated. At this time, except in some places, only deaths where there is a proven positive test are being listed as COVID deaths. This is the case in Florida. If you have all the COVID symptoms but you didn't get tested, you are NOT a COVID death. This of course artificially keeps the numbers down. Things look better than they really are. And this is especially true if the COVID tests miss a significant number of people who are really positive. This is widely reported. Note that in the Stanford study they missed about 20% of known positive controls. If these had been real patients who died, the official records of that 20% would not have COVID as a cause of death.

This is not how flu deaths were calculated, see above. Flu rate of death is an estimate of how many people died with influenza even if they never knew that had flu divided by an estimate of every person who had influenza like illness over the entire flu season. . It might be interesting to do a community wide test for antibodies to a particular circulating strain of influenza to see how many minimally ill or symptom free people were actually infected. It is not typically done. But that is what the Stanford Study is trying to do. Don't you think the denominator on the flu death calculation would be so much higher if asymptomatic people were included. Yup.
And HERE is an article asking the same question as the Stanford study.. How different is the evidence from blood testing for flu from the patient report of a flu illness

And that is the asymptomatic people, not including the low symptomatic people. None of these asymptomatic people are captured in the CDC's estimate of the number of persons who had influenza. And they need not be for the purposes of what the CDC is following. The CDC is very clear that the usual 0.1 % death rate is for persons with influenza like illnesses, and does not included lesser illness or no illness. You are of course saying you'd like to include lesser and no illness in your calculation to prove COVID is just like influenza. It is not. You are in error.

Originally Posted by Aloha1 (Post 1751103)

The Stanford test was for ANTIBODIES, not to determine positive or not . Are you saying that Dr. John Ioannidis of Stanford Med went on national TV and lied? However the data on Wuhan Virus cases is gathered, it is the CDC that is providing the aggregate numbers.

Did you bother to research a similar test conducted by USC in LA County that corrected some of the sample population criticisms from the Stanford Study ( over representation of white females)? That test had similar conclusions to the Stanford study. There are also serology tests being done internationally in the UK and Germany showing the same. Another test currently under way in Colorado will provide another reference point.

I have no patience with "politically correct" statements and prefer to use the standard nomenclature in effect before WHO changed it in 2015 so as "not to offend" anyone. The virus originated in Wuhan and therefore it IS the Wuhan Virus.

These studies give us HOPE that we may be a lot closer to herd immunity than currently thought. Throw all the cold water on that you want. I prefer optimism over negativism any day of the week.

Originally Posted by allus70 (Post 1749045)

The virus has killed more than 1,800 Americans almost every day since April 7, and the official toll may be an undercount.

By comparison, heart disease typically kills 1,774 Americans a day, and cancer kills 1,641.

The virus in now spreading to the suburbs and rural areas.

Originally Posted by OrangeBlossomBaby (Post 1749462)

I wish they'd eliminate the end-dates for everything. The answer to "when will these things re-open" should be "when the virus tapers off and/or a working vaccine is made available to the public."

And anyone who is not at *medical risk* who refuses to take the vaccine, would have to continue isolation/quarantine, until the virus is gone - whether for the season, or forever - whichever comes first.

Originally Posted by graciegirl (Post 1751120)

Aloha. I am trying to keep all of this straight and I know Blueash to be a retired M.D. Are you a person who has also been involved in medicine? You sound very smart as well. I was a preschool teacher who has always been interested in medicine since our youngest was born with a syndrome. I just read posts and wonder at the person's background. I try very hard to sift through information and trust only valid sources. I keep wondering about Goodlife too. I hope he/she shares their medical background, if any.