Covid - 19

[Guisslapp]

I'm in agreement with you that there is a lag time in positive test versus death. I think Cuomo indicated people were staying on a ventilator an average of 10 days. Don't know if that's how long before they die, recover, or a combination of the two. However, as we continue to test more and more people, I'm assuming with less sever cases then the denominator should grow at a faster rate than the numerator. While the number of deaths per day should flatten out, the number of positive cases should continue to increase. Either way that's of little comfort to those in the numerator.

It would be unusual for a disease with a 1.3% mortality rate to kill 4 people from a family gathering.

Obviously the big question is whether cases will exceed ventilator capacity for any community. Where that happens, you will have a multiplier effect on the mortality.

[MoonPieBlue]

It would be unusual for a disease with a 1.3% mortality rate to kill 4 people from a family gathering.

Obviously the big question is whether cases will exceed ventilator capacity for any community. Where that happens, you will have a multiplier effect on the mortality.

It would be interesting to know how many of those placed on ventilators have died or have recovered. I did a little googling but couldn't find much information. Working with a complete data set, like I typically do at work, is definitely better than trying to piece information from here or there.

[MoonPieBlue]

It would be unusual for a disease with a 1.3% mortality rate to kill 4 people from a family gathering.

Would make for an interesting study to see what was unique about them. I think each had an underlying condition, but it is still rather strange.

[detltu]

If you look at the data for countries where you can see a more defined peak in the curve (like China) you can see the delay in the peak of death vs reported cases.

https://www.worldometers.info/corona...country/china/

The variability of the testing delay introduces some noise (as does the change in how cases were calculated in China over a few days leading to an odd data point), but the bottom line is that there is in fact a delay between the cases that are reported and the deaths, so before we reach the peak new cases the mortality rate will look lower than it actually is and will be once the pandemic is over.

Basic data science principles.

Yes, and yet 10 days is not necessarily the correct number. That was my point. 10 days will not make your number more correct than 0 days. Just worse. Basic data science principles indeed.

[detltu]

It would be unusual for a disease with a 1.3% mortality rate to kill 4 people from a family gathering.

Obviously the big question is whether cases will exceed ventilator capacity for any community. Where that happens, you will have a multiplier effect on the mortality.

It would be unusual for sure, but not out of the questions. Particularly when you factor in how differently the disease affects different people with different underlying conditions. The way this attacks people over 80 and people with lung issues is pretty crazy.

[Guisslapp]

Yes, and yet 10 days is not necessarily the correct number. That was my point. 10 days will not make your number more correct than 0 days. Just worse. Basic data science principles indeed.

If you take deaths at t(0) and positive cases at t(-10 days), that would be a far more accurate way to estimate mortality rate at this point in the curve than if you were to compute mortality rate by taking total deaths to date divided by total positive cases to date.

[Blue Dawg]

Trump issued DPA requirement on GM to produce ventilators after suggesting that they weren’t really needed just yesterday.

All all the small-government Republicans were up in arms, right? Right?

[CARTEK]

It would be unusual for a disease with a 1.3% mortality rate to kill 4 people from a family gathering.

Obviously the big question is whether cases will exceed ventilator capacity for any community. Where that happens, you will have a multiplier effect on the mortality.

...not if the all had the same genetic predispositions. The NJ/PA family of five: all diabetic, all overweight, and all older then 50.

[Guisslapp]

...not if the all had the same genetic predispositions. The NJ/PA family of five: all diabetic, all overweight, and all older then 50.

Isn’t that the Trump demographic?

[dawg80]

If you take deaths at t(0) and positive cases at t(-10 days), that would be a far more accurate way to estimate mortality rate at this point in the curve than if you were to compute mortality rate by taking total deaths to date divided by total positive cases to date.

Agreed. Except I have a question...where did this 10-day figure come from? Seems to me we really don't know enough about C-19 and how it will react in populations to declare...Okay, 10 days is it!!! But otherwise, I agree with your bigger point.

[Guisslapp]

Agreed. Except I have a question...where did this 10-day figure come from? Seems to me we really don't know enough about C-19 and how it will react in populations to declare...Okay, 10 days is it!!! But otherwise, I agree with your bigger point.

That is the approximate delay in the peak new cases and peak new deaths in countries that have peaked. It is also based on the general length of time people have been hospitalized before they die.

It isn’t a rough estimate given the variability in data sources and quality and noise around testing and reporting.

[Guisslapp]

It “is” a rough estimate. Not “isn’t”

[Guisslapp]

1 out of 334 people in NOLA have it

1 out of 315 people in NYC have it

[FriscoDog]

Been wondering.. several new quick result test kits are hitting the field literally days after being developed. I was wondering if some of the positives and spikes we are seeing are due to possibly some false positives. What I mean by that is, could the test be showing positive, for the common flu, another COVID virus, or respiratory illness? I mean it's better to show a false positive than the reverse just to be safe.

[TYLERTECHSAS]

Of course, and hundreds of hospitals were closed due to Obama/Bide and their Obamacare as well.

Obama admin repeatedly sought millions in CDC funding cuts, despite Biden's attacks on Trump preparedness