COVID-19 (2): Turns out it's going to be pretty bad actually

Looks like the vast majority of students at my school will not be returning this school year. Graduating students will have to return. However, I finish teaching them before the day they have to go back. Unless I’m informed otherwise, I only have to go back for the 1st and 2nd week of June to administer school-leaving exams for the graduates. Everything else I can do online.

Know what it’s time for?

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Thanks. There was an article today about the Lazeretto house near the Philly airport. So we took a drive to check it out. it was built in 1799 and served as a quarantine house for 100 years for ship passengers coming up the Delaware. Yellow fever and typhus patients
mostly. Think today it’s township offices.

Here is the river facing side.
image

Here is covid patient Dan

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Hmm, I didn’t see this post, but I guess you and jman were right. Seems weird.

10000 tested

1000 tested positive (10% testing positive)

x actual positive

(1000 - x)/(10000 - x) = .05 (ratio of negative events wrongly categorized as positive to actual negatives = 5%)

1000 - x = 500 - .05x

500 = .95x

x = 526

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I saw you deleted your last post, so I deleted mine saying you were wrong. :slight_smile:

(I posted it and then noticed you had deleted.)

Let’s stick to posting US propaganda

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I figured that. I had a hard time accepting that the denominator was the true negatives rather than the true positives.

True/false positive/negative are just what they sound like. False positive is test positive but person is negative.

Short of DS dropping in to explain (and misspell) Bayes’ rule, there is a tweet with a decent explanation of the issue up thread.

It’s maybe counterintuitive, but in a nutshell - - the smaller the prevalence (of what you’re testing for) in the whole population is, the more likely positives in the tested sample are false.

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So then, is there any reason to believe the testing is so inaccurate that if 1000/10000 people test positive only 526 people are actually positive?

Well in any case, your posts made me think about it from a different perspective rather than just assuming. And that caused me to look it up and know for sure, so that’s a good thing.

LolGenetics? or LOLmutations?

I mean maybe Trump was just guessing that New York’s CV came from Europe??

Thanks for the linkage, I’ll head over to the beef thread :)

Nah, that makes perfect sense. Tiny mistakes over a large population end up with a lot of mistakes compared to the actual number of cases if it’s something rare.

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You mean in the Santa Clara testing? I read that the test they used for that was 99.5% accurate IIRC, but there were concerns with the sample size that had established the testing proficiency.

The problems with the Santa Clara results go well beyond the accuracy of the test used.

Edit: Tested at 99.5%, and at least as good as 98.2%

image

Thanks for the derail derail goofy.

Man, I just can’t see how these dates can kinda be true. Are they assuming that we’re all hardcore social distancing? Apparently people can be contagious for a week+ before feeling sick.

I think you should do a long Twitter thread on the UP account explaining why their model is so terrible. Your account is fine too.

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If anyone needs toilet paper, target has it in stock for shipping. Order quickly!:

https://www.target.com/p/scott-comfort-plus-toilet-paper-mega-rolls/-/A-54617519?preselect=79768115#lnk=sametab

Edit: nevermind, it went out of stock already. That was really quick.

How are the LIBERATE homies doing today? Needing to feel good and seeing pictures of these people suicide themselves for Daddy is about the closest it gets these days.

Don’t go back to work

It’s not worth dying.

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To add to this, you state ‘wife can get job back after’ and there may be a few vacancies (in the region) for obvious reasons (to not be too grim)

My mom too - although she never liked Trump anyway but I think voted for him because of the chopping up little babies thing.

She swears she’s not voting for him this time but I have my doubts. Rs can always hammer on abortion for a few months leading up to the election and get her back in the fold.

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