Addiction LXXVIII
#3326
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#3327
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#3328
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#3329
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After weeks of below normal temps and miraculous rain it's supposed to be in the 90s on Friday.
#3330
Señor Member
Someone earlier mentioned that in their area that landscape services weren't operating. But that's not the case in our area. As we walk through the neighborhood, we see lawn cutting, landscaping (weeding, mulching), lawn treatment (fertilizer, kill weeds, I guess), and sprinkler maintenance. A lot of these are just a one-man crew in a truck, there there is negligible risk. I have also seen trucks for HVAC and roofing contractors, and it looked like someone was getting their kitchen done (new countertops).
Some of the yard work is being done by homeowners - I guess it depends on the scale of the yard and how much effort you want to put into it.
Once again it is cold here - this morning temps were in the 30s, but it might get up to the mid 60s during the day.
Some of the yard work is being done by homeowners - I guess it depends on the scale of the yard and how much effort you want to put into it.
Once again it is cold here - this morning temps were in the 30s, but it might get up to the mid 60s during the day.
#3331
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#3332
Administrator
Thread Starter
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Fixed.
__________________
See, this is why we can't have nice things. - - smarkinson
Where else but the internet can a bunch of cyclists go and be the tough guy? - - jdon
#3333
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#3334
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#3335
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#3336
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Hey Bah Humbug - have you waded in to the wild waters of Japanese natural stones? I'm thinking about picking one up.
#3337
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#3338
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First world problem; I'd like to do some flat spinning for a couple hours but there's nothing flat around here and I live on a small hill. I could drive 10-12 miles to a nice bike path network but it might be crowded. That's probably what I'll do though.
#3339
Señor Member
The latest seems to be that putting someone on a ventilator is really a last resort. There was something interesting the other day that suggested that they can detect people getting into trouble before there are any real symptoms of breathing problems:
https://www.nytimes.com/2020/04/20/o...pneumonia.html
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#3340
cowboy, steel horse, etc
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#3341
cowboy, steel horse, etc
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#3342
Should Be More Popular
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#3343
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Santa Clara. There were 50 positives in a sample of >3000 asymptomatic responders to a FB ad. Also interesting was a >13% positive rate in women admitted to a labor and delivery service at a Manhattan hospital. Both of these are likely overestimates of the prevalence of antibodies in the population. The NIAID has a 10,000 person serosurvey underway too. We'll have a better understanding soon. All that said, there is major concern about the specificity of the existing antibody tests, all of which may cross-react with other coronaviruses, thereby inflating the estimates.
#3344
cowboy, steel horse, etc
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#3345
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#3346
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Santa Clara. There were 50 positives in a sample of >3000 asymptomatic responders to a FB ad. Also interesting was a >13% positive rate in women admitted to a labor and delivery service at a Manhattan hospital. Both of these are likely overestimates of the prevalence of antibodies in the population. The NIAID has a 10,000 person serosurvey underway too. We'll have a better understanding soon. All that said, there is major concern about the specificity of the existing antibody tests, all of which may cross-react with other coronaviruses, thereby inflating the estimates.
https://www.cnbc.com/2020/04/22/roch...rs-ethics.html
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#3347
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#3348
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It would probably be pretty empty at 4:30 am. You might have to take dawn patrol ride lessons from @Heathpack
#3349
Has a magic bike
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Santa Clara. There were 50 positives in a sample of >3000 asymptomatic responders to a FB ad. Also interesting was a >13% positive rate in women admitted to a labor and delivery service at a Manhattan hospital. Both of these are likely overestimates of the prevalence of antibodies in the population. The NIAID has a 10,000 person serosurvey underway too. We'll have a better understanding soon. All that said, there is major concern about the specificity of the existing antibody tests, all of which may cross-react with other coronaviruses, thereby inflating the estimates.
However as I understand it they both used the same test methodology and there are some questions as to its reliability.
Have you read the not-yet-peer-reviewed draft of the NoCal study? I have and I was confused by something in their methods section. In determining specificity of the test, they ran it on three groups of blood samples. Two of these control sample groups were small, in the 30 sample range, and the test had no false negatives. The other sample group was larger, almost 400 samples. These were preCOVID samples (whatever that means, I’d make them define that if I were reviewing the paper! But presumably blood samples collected from a time far enough in the past that the patients from who the samples were taken could not possibly have been infected with this novel corona virus). In this larger sample, they had 4 positives, so a false positive rate of 10.1%. Yet they calculate their test specificity to be something like 97.7%. Seems to me like that’s too high of a specificity for a test that had a 10% false positive rate in the largest control group tested. But I’m bad at stats.
Since their study group was something just under 4000 people, if we apply the 10% false positive rate to that group, you’d get 40 positives. The study subject group had far less positives than that- ie *all* the positives in the study sample could have been false positives. So it’s seems like a hugely flawed study to me, it will be interesting to see if it makes it through review.
Also the interesting thing with their case recruitment being through FB ads. That seems to me like they really could have biased their study sample towards people who thought they’d been sick with COVID but couldn’t get tested. Those would be the people IMO who would be most motivated to seek out testing, and the way FB works it’s easy to be connected to likeminded people in the same boat as you. So I could see that the study participants were skewed towards people who suspected they’d had the disease.
Then did you catch the fact that signing up for the study was first come first served, and if you got in, you were allowed to bring a child from your household. When you look at the number of children in the study, you realize that around 50% of the study samples were from two people in the same household. So if you’d already selected inavertently for COVID suspects, now you’ve just doubled your expected number of positives because you’ve included some many in-contact samples from the same household.
Bottom line: I think that study is such as mess, or at least it is as I can understand it fromhow it’s written now, that it may be impossible to get much of anything out of it. If you haven’t seen the released early draft of the study, I can link to it.
Last edited by Heathpack; 04-22-20 at 10:11 AM.
#3350
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LA County has done a better designed study too, just announced results yesterday. They found greater seroprevalence than expected but not as high as in the NoCal study.
However as I understand it they both used the same test methodology and there are some questions as to its reliability.
Have you read the not-yet-peer-reviewed draft of the NoCal study? I have and I was confused by something in their methods section. In determining specificity of the test, they ran it on three groups of blood samples. Two of these control sample groups were small, in the 30 sample range, and the test had no false negatives. The other sample group was larger, almost 400 samples. These were preCOVID samples (whatever that means, I’d make them define that if I were reviewing the paper! But presumably blood samples collected from a time far enough in the past that the patients from who the samples were taken could not possibly have been infected with this novel corona virus). In this larger sample, they had 4 positives, so a false positive rate of 10.1%. Yet they calculate their test specificity to be something like 97.7%. Seems to me like that’s too high of a specificity for a test that had a 10% false positive rate in the largest control group tested. But I’m bad at stats.
Since their study group was something just under 4000 people, if we apply the 10% false positive rate to that group, you’d get 40 positives. The study subjects had far less positives than that. So it’s seems like a hugely flawed study to me, it will be interesting to see if it makes it through review.
Also the interesting thing with their case recruitment being through FB ads. That seems to me like they really could have biased their study sample towards people who thought they’d been sick with COVID but couldn’t get tested. Those would be the people IMO who would be most motivated to seek out testing, and the way FB works it’s easy to be connected to likeminded people in the same boat as you. So I could see that the study participants were skewed towards people who suspected they’d had the disease.
Then did you catch the fact that signing up for the study was first come first served, and if you got in, you were allowed to bring a child from your household. When you look at the number of children in the study, you realize that around 50% of the study samples were from two people in the same household. So if you’d already selected inavertently for COVID suspects, now you’ve just doubled your expected number of positives because you’ve included some many in-contact samples from the same household.
Bottom line: I think that study is such as mess, or at least it is as I can understand it fromhow it’s written now, that it may be impossible to get much of anything out of it. If you haven’t seen the released early draft of the study, I can link to it.
However as I understand it they both used the same test methodology and there are some questions as to its reliability.
Have you read the not-yet-peer-reviewed draft of the NoCal study? I have and I was confused by something in their methods section. In determining specificity of the test, they ran it on three groups of blood samples. Two of these control sample groups were small, in the 30 sample range, and the test had no false negatives. The other sample group was larger, almost 400 samples. These were preCOVID samples (whatever that means, I’d make them define that if I were reviewing the paper! But presumably blood samples collected from a time far enough in the past that the patients from who the samples were taken could not possibly have been infected with this novel corona virus). In this larger sample, they had 4 positives, so a false positive rate of 10.1%. Yet they calculate their test specificity to be something like 97.7%. Seems to me like that’s too high of a specificity for a test that had a 10% false positive rate in the largest control group tested. But I’m bad at stats.
Since their study group was something just under 4000 people, if we apply the 10% false positive rate to that group, you’d get 40 positives. The study subjects had far less positives than that. So it’s seems like a hugely flawed study to me, it will be interesting to see if it makes it through review.
Also the interesting thing with their case recruitment being through FB ads. That seems to me like they really could have biased their study sample towards people who thought they’d been sick with COVID but couldn’t get tested. Those would be the people IMO who would be most motivated to seek out testing, and the way FB works it’s easy to be connected to likeminded people in the same boat as you. So I could see that the study participants were skewed towards people who suspected they’d had the disease.
Then did you catch the fact that signing up for the study was first come first served, and if you got in, you were allowed to bring a child from your household. When you look at the number of children in the study, you realize that around 50% of the study samples were from two people in the same household. So if you’d already selected inavertently for COVID suspects, now you’ve just doubled your expected number of positives because you’ve included some many in-contact samples from the same household.
Bottom line: I think that study is such as mess, or at least it is as I can understand it fromhow it’s written now, that it may be impossible to get much of anything out of it. If you haven’t seen the released early draft of the study, I can link to it.
Yes, I saw about the kids. Huge selection bias there. The NIAID study is trying to avoid this by telling everyone upfront that they won't get their results.