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Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

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Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#61

Post by ejstronge »

subroutine wrote: post #46
DenisM wrote: post #28

Earlier quoted context omitted.

Yes, it's 10% false positive. But it's not "really low" in the sense that it's typical for antibody tests. Which is one reason not to do wide-spread testing.

Or you could flip that around and make testing so plentiful everyone is tested 3x (perhaps by independent labs), so the FP rate is more like... 1/10 * 1/10 * 1/10 (1/1000)

This would require that false positives are truly random and not influenced by sample-specific factors. Is this the case? In antibody testing, I would imagine that false positives result from cross-reactivity instead of random chance.

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#62

Post by contravariant »

cameldrv wrote: post #34

Has anyone been able to figure out what the number of COVID deaths are in Chelsea specifically?

The article claims 712 detected cases resulting in (at least) 39 deaths.

Chelsea has a population of about 40k, this isn't mentioned in the article but matches the article's figure of around 1900 cases per 100,000.

Assuming 30% of the population is infected this puts the current number of deaths at around 0.3% of the total infected. There is some bias due to the rate of false positives of the test and the lag in the number of deaths, so the actual fatality rate may well be higher, but the order of magnitude seems consistent with the numbers discussed in previous threads [1].

[1]: https://news.ycombinator.com/item?id=22901311

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#63

Post by Retric »

School-Cotton wrote: post #41
Retric wrote: post #38

Earlier quoted context omitted.

It’s normal to randomly sample multiple locations. Random samples from even 10 random locations are much more useful.

Not really... more data can't fix sampling bias.

It’s not a question of ‘more data’ as I could take 50 or 50,000 samples from a single person and I gain nothing about the overall population.

Similarly if I sample 50 or 50,000 people from a single city I learn nothing about people outside of that city. But, by sampling N random locations I at worst have N samples to work with.

PS: At the extreme, if I sample every single member of a population then ‘more data’ solved any bias problems. Smaller samples are subject to a wider range of biases.

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#65

Post by youareostriches »

hinkley wrote: post #26
bitcurious wrote: post #19

Earlier quoted context omitted.

Out, about, and willing to speak to a stranger, which I think is the biggest bias. Pretty much everyone I know goes on the occasional walk, but we all stay the fuck away from other people.

My Hollywood movie plot theory is that Covid affects inhibitions.

It’s certainly not a hollywood movie—for the flu, it’s already the case!

Change in Human Social Behavior in Response to a Common Vaccine

https://pubmed.ncbi.nlm.nih.gov/20816312/

Conclusions: These results show that there is an immediate active behavioral response to infection before the expected onset of symptoms or sickness behavior.

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#67

Post by fapjacks »

adtechperson wrote: post #54
arenaninja wrote: post #33

Earlier quoted context omitted.

Yep.. I saw a similar headline claiming LA infections are 55x the reported rate. I think the math is likely simpler, and the infection is somewhere between 3x-5x (10x tops). I've read a few reports saying about 50% of people are asymptomatic, 30% show symptoms that aren't bad enough for hospitalization and 20% require hospitalization. I can't find the source I got it from but I believe it was a Chinese study

This also came out today. http://publichealth.lacounty.gov/phcommon/public/media/media... We really have no idea what the IFR is, just that is probably in the .1% to 1% range. Also, it takes around 2 weeks to develop antibodies, so the tests are showing how many people had covid 2 weeks before testing.

That antibody timeline was an estimate derived from data obtained from the "original" SARS virus, but it isn't accurate with the SARS-CoV-2 virus. IgM antibodies are present within hours of the onset of symptoms, and IgG antibodies after a few days.

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#68

Post by subroutine »

ejstronge wrote: post #61
subroutine wrote: post #46

Earlier quoted context omitted.

Or you could flip that around and make testing so plentiful everyone is tested 3x (perhaps by independent labs), so the FP rate is more like... 1/10 * 1/10 * 1/10 (1/1000)

This would require that false positives are truly random and not influenced by sample-specific factors. Is this the case? In antibody testing, I would imagine that false positives result from cross-reactivity instead of random chance.

Sure, there are certainly protocols that could be made that would almost ensure FP is due to sample factors.... or even test related factors that would maximize 3x FP (same lab, same lab tech, same machine, same day, back to back, same reagent stock).

We shouldn't adopt those protocols.

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#69

Post by Gibbon1 »

retsibsi wrote: post #39
james_s_tayler wrote: post #17

Earlier quoted context omitted.

My understanding is it's (R0 - 1)/R0 So if R0 is 4 then 3/4 of the population is required to be immune before herd immunity kicks in.

Yeah, I'm not an epidemiologist but I think the principle is simple: it's just a matter of getting the actual transmission rate below 1, so that any outbreak will naturally die out. If in the absence of any immunity the average infected person infects 3 others, but now 2/3 of people are immune, then the average infected person will actually only infect one other. Ditto for a transmission rate of four and 3/4 immunity…

> herd immunity overshoot

I saw that too when mucking with simple models. The percent infected overshoots (R0 - 1)/R0. So that is a threshold for herd immunity not the ultimate infection ratio. They're only equivalent under steady state conditions.

Also saw an study released by the CDC that estimated that the initial r0 in Wuhan was 5.8. Explains what happened in Northern Italy and New York. The epidemic achieved break out while most infected were still mildly ill or asymptomatic.

Re: Nearly a third of blood samples taken in Chelsea show exposure to coronavirus

#70

Post by jfnixon »

fapjacks wrote: post #67
adtechperson wrote: post #54

Earlier quoted context omitted.

This also came out today. http://publichealth.lacounty.gov/phcommon/public/media/media... We really have no idea what the IFR is, just that is probably in the .1% to 1% range. Also, it takes around 2 weeks to develop antibodies, so the tests are showing how many people had covid 2 weeks before testing.

That antibody timeline was an estimate derived from data obtained from the "original" SARS virus, but it isn't accurate with the SARS-CoV-2 virus. IgM antibodies are present within hours of the onset of symptoms, and IgG antibodies after a few days.

Source?
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