'The first New York patient was in...January?'

[Cow Poke]

Apparently the thinking is

I predict this post will prove your lack of thinking...

anyone who has some underlying illness, or is just old, they were going to die anyway, as if they know that, so let's not count them.

Yep - absolutely moronic.

Anything to defend Trumps messaging to them that it's a hoax!

You're smoking the funny stuff, Jim.

[oxmixmudd]

It is useless because without serology you don't know the total number of cases. The first patient was found sick 11 days after the cruise began, and how many patients got it and recovered within that period are unknown.



Stop crying and parroting R0 values. There have been no full test studies with serology, so R0 has not been measured accurately, and neither has fatality rate.

You didn't even read the article (or the many others available on the topic) did you? You're shooting from the 'we can't know anything all because <insert excuse here>' hip that YEC's hail from. It is what it is - but you do yourself and everyone that might take you seriously a great disservice by doing so.

[Sparko]

Let's try this analogy. Compare a candle that you burn from both ends to the same candle that you burn from one end. One burns faster, but the same amount of wax is burnt when all is said and done.

Fatality rate is about number of deaths/number of cases. Faster spread increases both the numerator and denominator and doesn't necessarily mean a higher fatality rate.

yeah but again, the problem is the number of sick people at once. Which is why we are running out of masks, ventilators, doctors are working around the clock, etc. That is why they are trying to spread it out more.

When you burn a candle at both ends you get a shorter length of light and you will likely get burned.

[Sparko]

And how much of this is because testing is increasing?

testing doesn't affect how many are dying. Look at the deaths. We are at flu level deaths in just over a month.

[JimL]

What an incredibly moronic misguided conclusion.

True, and it came from you. Oh, they died from a heart attack so they shouldn't be counted as coronavirus victims. That's your moronic conclusion.

[demi-conservative]

testing doesn't affect how many are dying. Look at the deaths. We are at flu level deaths in just over a month.

Testing absolutely affects the deaths recorded. If you're not tested before or after you die but you're positive, you're just not recorded.

[demi-conservative]

yeah but again, the problem is the number of sick people at once.

In other parts of the country, doctors are being laid off because of insufficient patients. With good management, doctor overload is not an issue.

[demi-conservative]

You didn't even read the article (or the many others available on the topic) did you? You're shooting from the 'we can't know anything all because <insert excuse here>' hip that YEC's hail from. It is what it is - but you do yourself and everyone that might take you seriously a great disservice by doing so.

You have nothing of worth to contribute, leave now.

[simplicio]

True, and it came from you. Oh, they died from a heart attack so they shouldn't be counted as coronavirus victims. That's your moronic conclusion.

Ummmm, wow. Do you really think you can take a true Christian's argument seriously, as if he actually believes it?

Just because a poster makes an argument does not mean he actually believes it, especially when it is used to put down others.

[Juvenal]

It means all the models and projections ...

... need to be updated with better data, and not just this time, every time better data becomes available. We don't throw out an equation because a number needs to be adjusted. That's a general principle. In this case, we could go further and note the wrong number doesn't appear to be an egregious error. The infection arrived in Seattle in January, and spread from there, independent of the date the first infection arrived in New York.

[Juvenal]

I don't need to 'parrot' demi. I go to the data, I do the calculations.

R0 is the number of patients infected by a single patient. that and the available population defines what the peak number of cases will be. But Hospitals are not overrun by the peak number of cases, they are overrun by the peak number of seriously ill and dying patients. And that is defined by both the mortality and R[0]. For example, 95% mortality will overwhelm a hospital with an R0 far less that that of the flu. But .00001% mortality may not overwhelm a hospital even with a measles like r0 of 8 to 15.

Okay, that needs adjusting.

R is the number infected by the average case. "R" is the "reproduction" rate, which varies over time, R(t). R0 was the number being infected before any mitigation strategies were in place, the initial value, R(t=0).

[Sparko]

Testing absolutely affects the deaths recorded. If you're not tested before or after you die but you're positive, you're just not recorded.

Your initial point was that testing reveals more people who have it without symptoms, thus raising the total who are positive. But we are talking about the number of deaths. Anyone sick enough to die of it will have been tested.

[demi-conservative]

Anyone sick enough to die of it will have been tested.

Lots of people have died, at home or otherwise, and not been tested because of insufficient test kits. Every data point is undercounted.

Just face it, the models are useless. Garbage in, garbage out.

[Sparko]

Lots of people have died, at home or otherwise, and not been tested because of insufficient test kits. Every data point is undercounted.

Just face it, the models are useless. Garbage in, garbage out.

Then the numbers of deaths are even higher than reported, confirming my point that this is worse than the flu because of more deaths in a shorter period of time.

[demi-conservative]

Then the numbers of deaths are even higher than reported, confirming my point that this is worse than the flu because of more deaths in a shorter period of time.

Fatality rate is defined as number of deaths/number of total cases, not more deaths in a shorter period of time. The total number of cases is highly underreported, so the fatality rate is probably similar to a bad flu season.