The Count of Corona...

[DMC]

never. People aren't scared of strep like they are of this virus. Do you feel like you need tested for covid? If so, why and how many times or how regular would you want to be tested. I ask because I do not care to be tested.

I am being tested for antibodies. It's not based on fear but on the need to have an better radar image of the impact of the virus and possible immunity to it.

[tholdren]

I am being tested for antibodies. It's not based on fear but on the need to have an better radar image of the impact of the virus and possible immunity to it.

I assume many will want to do that as well. Do you think a majority of the population will be satisfied with 1 test? Aren't tests coming back 90 percent negative? Haven't looked for info on past flu test negative counts.

[hater]

It does mean . You pull statistics right out of your ass.

Their assessment found that the ability to detect antibodies in people who had tested positive for the virus increased over time, rising to 81–100 percent when more than 20 days had elapsed since symptoms began, depending on the product. One of the members of the team, Patrick Hsu, a bioengineer at UCB, notes that this finding highlights why longitudinal antibody testing is important, given that a negative result may mean a person had been exposed to the virus but hadn’t yet developed a detectable level of antibodies. On the specificity side, the proportion of false positives found in the pre–COVID-19 samples ranged from 0–16 percent. The agreement between the findings of LFAs and ELISAs ranged from 75–94 percent. The team posted its results as a preprint on the project website on April 24. Alex Marson, an immunologist at UCSF and a coauthor of the report, cautions that some numbers, especially for tests’ ability to detect antibodies in positive cases, may be revised as his team continues to analyze the data.

You should shut the up you low information chicken little.

statistics are not your forte nancy

let me educate you a bit and you will not embarrass yourself again (hopefully ):

In a population whose infection rate is 5 percent, a test that is 90 percent accurate could deliver a false positive nearly 70 percent of the time.

https://www.nytimes.com/2020/05/13/o...-accuracy.html

[Thread]

The Old Fart thought his Orange God would deliver victory bigly

He did. This changes nothing. He took Clinton, turned her upside down, and shoved her, head first, straight into the earth.

Trump President.
Not Clinton.

& he's President forever, just like the 44 before him.

Put that in your smoke & pipe it, you damn nocker, you.

[baseline bum]

He did. This changes nothing. He took Clinton, turned her upside down, and shoved her, head first, straight into the earth.

Trump President.
Not Clinton.

& he's President forever, just like the 44 before him.

Put that in your smoke & pipe it, you damn nocker, you.

Oh yeah that's going to be a big victory when Katie girl has to drop you into the mass graves.

[Thread]

Oh yeah that's going to be a big victory when Katie girl has to drop you into the mass graves.

- "Don't leave me here."

- Girl

Beats the alternative every day that ends in (y).

[boutons_deux]

90,000 dead / 1,400,000 cases = 6.4% mortality rate for USA, so far

[DMC]

the antibody test is 50% accurate at best

dont mean

statistics are not your forte nancy

let me educate you a bit and you will not embarrass yourself again (hopefully ):

In a population whose infection rate is 5 percent, a test that is 90 percent accurate could deliver a false positive nearly 70 percent of the time.

https://www.nytimes.com/2020/05/13/o...-accuracy.html

Make up your mind

False positives are something the diagnostics community lives with. Its why they have confirmation testing.

out of your league again

[hater]

Make up your mind

False positives are something the diagnostics community lives with. Its why they have confirmation testing.

out of your league again

wow you are really one stupid mother er

let me caps it for you

DELIVER FALSE POSITIVES UP TO 70% IF THE TIME

what a moron

[DarrinS]

90,000 dead / 1,400,000 cases = 6.4% mortality rate for USA, so far

Your denominator is WAY off.

[tholdren]

90,000 dead / 1,400,000 cases = 6.4% mortality rate for USA, so far

Mortality rate from coronavirus or with coronavirus?

[RandomGuy]

Lol years average death.

Sorry, I can't understand the statistics for you.

In order for you to really understand my point, you will have to understand means, medians, standard deviations, and a host of other concepts from probability and statistics.

Your post here was the equivalent of saying "lol adiabatic process".

We will be able to get pretty close to what it was in reality once we get enough data on mortality and incidence, because we can use that to isolate out the causes of the sudden e in deaths.

The only way that would really not work is if there is some sort of unexplained e in other causes of death.

Are you trying to say that we missed some e in heart attacks or a natural disaster that killed a lot of extra people every day for the last few months?

[RandomGuy]

90,000 dead / 1,400,000 cases = 6.4% mortality rate for USA, so far

Your denominator is WAY off.

Indeed.

Sort of a pointless calculation, given how little we are testing.

90000/.0066 implies 13M cases.

We have diagnosed only 1.4M, meaning we are falling farther and farther behind where we really need to be testing wise.

The lag used to be about 7 times, now the lag is almost 10 times

It is spreading faster than we think it is, by a large margin, if this simple calculation is correct.

[RandomGuy]

the antibody test is 50% accurate at best

dont mean

statistics are not your forte nancy

let me educate you a bit and you will not embarrass yourself again (hopefully ):

In a population whose infection rate is 5 percent, a test that is 90 percent accurate could deliver a false positive nearly 70 percent of the time.

https://www.nytimes.com/2020/05/13/o...-accuracy.html

Make up your mind

False positives are something the diagnostics community lives with. Its why they have confirmation testing.

out of your league again

"make up your mind"

Dude, his first post was about a real test, the second was a hypothetical posed by the op-ed author to make a point about statistics, which was exactly valid. Your rush to ding him, showed you didn't really understand what he posted. Self-pwnage.

Even with a high confidence (hypothetical) test, if only 5% of the population has it then the vast majority of your positives will be false.

If the real test is only 50% accurate, almost all of your positives would be false, and even testing two or three times would still not barely narrow that down to the point of meaninglessness.

Bayes Theorem ftw. I'll let you google that. or not. Plenty of good primers on it in youtube.

[tholdren]

Sorry, I can't understand the statistics for you.

In order for you to really understand my point, you will have to understand means, medians, standard deviations, and a host of other concepts from probability and statistics.

Your post here was the equivalent of saying "lol adiabatic process".

We will be able to get pretty close to what it was in reality once we get enough data on mortality and incidence, because we can use that to isolate out the causes of the sudden e in deaths.

The only way that would really not work is if there is some sort of unexplained e in other causes of death.

Are you trying to say that we missed some e in heart attacks or a natural disaster that killed a lot of extra people every day for the last few months?

I said. You will never figure out the true number of deaths. Which you wont/can't. Then you respond with a deviation of an average. Not sure what you dont get about that.

[boutons_deux]

Indeed.

Sort of a pointless calculation, given how little we are testing.

90000/.0066 implies 13M cases.

We have diagnosed only 1.4M, meaning we are falling farther and farther behind where we really need to be testing wise.

The lag used to be about 7 times, now the lag is almost 10 times

It is spreading faster than we think it is, by a large margin, if this simple calculation is correct.

90,000 dead / 1,400,000 cases = 6.4% mortality

90000 / 0.064 = 1.4M

[DarrinS]

90,000 dead / 1,400,000 cases = 6.4% mortality

90000 / 0.064 = 1.4M

There are millions of mild/asymptomatic cases that aren't included in your 1.4M denominator.

[tholdren]

There are millions of mild/asymptomatic cases that aren't included in your 1.4M denominator.

Some people believe that people who are tested and confirmed as well as those who died that haven't been counted are the only people in the data.

They seemingly forget that over 85 percent of people infected will have mild symptoms. They think that these people do not count. But they also argue that the virus is extremely transmissible. Lots of strange "points" being made

[baseline bum]

There are millions of mild/asymptomatic cases that aren't included in your 1.4M denominator.

Yeah case fatality rate doesn't tell much if you're not doing at least randomized testing. From NYC's antibody testing COVID19 appeared to have about a 0.5% mortality rate, though that's likely an undercount since it only counts those who have died vs those infected instead of those who have died or will die from infections they already have vs those infected, since the time between first infection and death seems to be around 3-6 weeks for those who die. So a total morality rate of around 0.7% or 0.8% wouldn't surprise me much.

[tholdren]

Some people believe that people who are tested and confirmed as well as those who died that haven't been counted are the only people in the data.

They seemingly forget that over 85 percent of people infected will have mild symptoms. They think that these people do not count. But they also argue that the virus is extremely transmissible. Lots of strange "points" being made

Above, right on cue

[hater]

There are millions of mild/asymptomatic cases that aren't included in your 1.4M denominator.

nice theory with no facts to back it up

[tholdren]

nice theory with no facts to back it up

Models needed no theory when 140k beds were needed in ny, or 94 million deaths, inexplicably that was believed.

[hater]

Models needed no theory when 140k beds were needed in ny, or 94 million deaths, inexplicably that was believed.

precautions != facts

[tholdren]

precautions != facts

? They said that was going to happen. It was facts to them.

[baseline bum]

This message is hidden because tholdren is on your ignore list.