COVID-19 (artist formerly known as Wuhan strain novel Corona virus)

If you test a group of 100 people who have COVID-19 symptoms and a group of 100 people who don't have COVID-19 symptoms, which group will have a higher percentage of people test positive for COVID-19?

The asymptomatic group will likely have a percentage of people test positive. No one is denying that. But that percentage will be much lower than the percentage of people who test positive in the group of people showing symptoms.

So if you base your numbers 100% on the people showing symptoms, your numbers, once extrapolated for the rest of the population, are going to be skewed towards showing that more people have it than what is likely accurate. That, by default, lowers the death rate because the numerator (number of deaths) stays the same but the denominator (number of cases) increases substantially. But you can't do that because the rest of the population isn't showing symptoms.

This isn't an opinion thing. It's math.

 

The death rate is very likely between 0.55 and 0.8. This is based on New York's antibody test. You can put more stock in the NYC numbers because there is less likelihood of selection bias. In California, they are not getting a random sample because people who believe they have been exposed are more likely to show up for the antibody test. In NYC, almost everyone has reason to believe that they have been exposed. The lower bound on NYC death rate is 0.55. But it is likely higher due to undercounted deaths and those who had not yet succumbed to the virus (but would/will eventually) when the antibody test was conducted.

 

And which math is correct Indy, the one sent out by worldometer and fed by media to you all day, or the math these guys are using. Fact is there are many who believe they are much closer to true numbers than what media and cdc send out.
On a secondary note, i also find it odd when someone who isnt seeing patients, tells drs what they are and arent seeing or doing. From behind a desk, waiting on someone to official prove something before believing it exists.
They are either right or wrong, but apparanlty their methodology gets them closer to real numbers than is reported.

 

I think people don't [itch bay] about him enough. His is incessant, so should be the rebuke.

How many of those types of death were reflecting the type of pandemic outbreak of which he was speaking about at that moment, or any of the moments since tbis began, in which he pisses and moans about how unfair everyone is to him?

Meanwhile, his pissiness and pettiness you find amusing as he whines and punches down with stupid 3rd grade childishness, but feel the need to chastise my repeated condemnations of his behavior and the support for it from some people on this board.

Ohhhkaaaayy.

In any event, the discussion on the numbers of Covid are more pertinent and interesting.

 

This must be what frustrates so many people about how you post/argue.

You've posted 3 times since I explained the problems with their methodology, and not one of those three posts has addressed those problems. You've talked about the state of TN, thrown out random numbers without any backup or stating where they are coming from, talked about how these guys' numbers fall in line with other numbers (as if they can't all be wrong, at the same time), and implied that the media has something to do with whether these guys are to be believed or not.

None of that shit matters, man. The way these guys went about collecting their data and then applying it to a much larger population does not make sense, mathematically, and their results are skewed and unreliable as a result, regardless of what anyone else, anywhere, has or will report.

 

They are not correct in how they take high-end modeled flu estimates from a full season, compare that to deaths/total population over a 6 week period in California, and conclude your risk of dying from CV in CA is x% and therefore less than flu. It's faulty logic and they likely know better.

 

We'll end up correcting the cases through modeling once we get antibody results.

We'll also end up revising deaths upwards. If you look at abnormal death rates across the US, the deaths attributed to CV only fill 30-70% of the gap. That means deaths from CV could be 3x higher than we are counting in some places, 50% higher in others. I do not know if they filter homicides and car accidents out of this. It would make it better if they do. If they do filter that out, then it isn't 50%-200% higher in these cities/states. Because, I'm sure the death rate due to natural causes is likely higher than normal due to some people not seeking treatment for certain critical ailments is down right now.

 

So you didn't listen to them or read these articles...but want to know what they're wrong about?

 

I agree that .55 is likely the floor, and the ceiling must not be too far above 1.

 

Remdesivir getting the same emergency use authorization that HCQ got.

 

TT people have thrown shit against the wall from the get go wirh this virus. Ive read many articles arguing against some points those 2 made, and others agreeing with them, as far as severity of the virus and estimated population with it.
Nobody knows. Including poaters here qho will have zero anecdotal wvidence with patients but insist drs are wrong. Sure question methodology. Question is are they right or wrong and nobody knows

 

I will be interested to know if the real change from this epidemic relates to how health care is instituted in this country as opposed to some of the predictions about behavior, which I don't think will change.

 

Zero anecdotal evidence? Sounds serious.

 

When you take numbers - inaccurate or not - and extend those ILLOGICALLY to make a conclusion, then that conclusion is just wrong.

There is a difference between taking uncertain numbers with error bars and reasoning through what they mean and arriving at a conclusion with error bars - and taking different uncertain numbers, applying bad methodology, and arriving at fundamentally faulty conclusions.

In what I have posted here, I have assumed the number of people that have it are 10x what have been reported and the death rate closer to 0.6. I have been using a death rate assumption of 0.8 since around March 13th, roughly - which I later pushed down to 0.66 after the Lancet paper came out. I was not using 2-3%. Recognizing that the likely number of cases was probably 10x what we were counting came later once I was able to do more modeling.

With the New York testing, these numbers still seem to be reasonable.

 

You are a scientist and need to see it on a test tube or rat to know it exists. Not everyone is the same. Thank goodness.

 

You have no idea how silly you sound.

 

Take out a couple of their comments and youll find many who think along the same lines as them, and have felt from the start this was the most media hyped even in the history of the world.

 

I’m also a scientist. Their data is biased. Regardless of what is going on with COVID19 in the US, up, down, less, more.

 

Post another VA article to fit your slant. Thats where you are the best.

 

Obviously. But are their conclusions wrong?