Preliminary test results suggest 21% of NYC residents have Covid antibodies

https://www.6sqft.com/new-york-covid-antibody-test-preliminary-results/

by kgwgk • 6 years ago

364 646 6 years ago

6sqft.com

cm21879• 6 years ago

Another datapoint suggesting the death rate of this virus is within 0.5%.

Exmoor• 6 years ago

Also another data point suggesting that the virus is much more contagious than the early estimates said.

I personally don't see how the test, track and trace efforts that have been touted as the only way to open things up can work with a virus with these characteristics. You would need to test a huge percentage of the population each day with quick results tests and something like that is many months away from being possible assuming it ever would be possible.

daxfohl5• 6 years ago

I agree. But it seems to have worked in Korea. The math doesn't seem to reconcile somehow. Actually probably the prevalence of masks explains the difference.

istorical2• 6 years ago

More contagious OR began community spread and became endemic much earlier.

r0 is part of the formula for total infected at X/Y/Z date but so is date of initial infection and size of initial infected population.

GVIrish• 6 years ago

The key is testing, contract tracing, and quarantining when the number of cases is small. That's what South Korea, New Zealand, and a few other countries did and they've all suffered relatively few fatalities. You still need a massive amount of tests to contain an outbreak, but the upside is that if you contain it early you don't need toe enact clumsy and broad measures like lockdowns.

Spooks• 6 years ago

I wonder if we did these preliminary tests with the flu if we would see a large death rate drop for influenza as well

nullc2• 6 years ago

The US's influenza mortality figures are a combined influenza and pneumonia figure because they usually don't even bother actually screening for influenza.

Research attempting to determine how much of that figure is infected with influenza have found figures like 1/3rd (though with large differences year to year).

cozzyd6• 6 years ago

I had the opposite conclusion. There are between 10k-15k COVID-19 associated deaths in NYC, depending on how you count (the higher rate is consistent with the excess-mortality data, I believe). That by itself produces a range of ~0.56%-0.86% if you assume 21.2 % of NYC has been infected (larger range if you allow for some error on the infection rate, obviously). Moreover, we don't know what fraction of the currently-infected who will die have already died. A reasonable guess might be 50%, which would mean that the fatality rate for NYC is somewhere between 1.1 and 1.7%.

Either way, based on NYC, 0.5% might be a hard lower bound on the all-population fatality rate (of course, maybe NYC is not a representative sample for some reason)

rubidium3• 6 years ago

“ Moreover, we don't know what fraction of the currently-infected who will die have already died. A reasonable guess might be 50%” I lost you at reasonable guess. Why not ~1%?

cm21879• 6 years ago

0.5% comes from Cuomo’s presentation [1].

Also your 50% seems very high to me. My understanding is that 50% is about the death rate of covid patients requiring ventilation, so the overall death rate of people hospitalised for covid must be well below that.

Also if you factor this timing impact, you have the same timing impact on the denominator, i.e. people who are infected but haven't developped antibodies yet.

[1] https://youtu.be/TisDYYWJgBA?t=967

[edit] in fact for the 50%, we have an idea from Cuomo's presentation charts. The gross daily hostpitalisation rate as of 10-15 days ago was about 2000-2500 per day, and the number of death now is about 500 per day, so that suggests roughly a 20-25% death rate for hospitalised people (I am sure there must be some more precise figures somewhere).

grandmczeb8• 6 years ago

It’s not clear what kind of antibodies they’re testing for, but it can take up to 4 weeks after infection to develop detectable levels of antibodies. It takes on average ~3 weeks after infection to die. There needs to be some time lag adjustment in your calculation, which would likely result in a lower IFR.

IMO the two effects probably about cancel each other out and we’re looking at <1% IFR for the population tested (AFAIK children weren’t included).

Avamander• 6 years ago

Mortality rate, case fatality rate and infection fatality rates are all different things and have different values.

Infection fatality rate of the virus could be within 0.5% (because its the one that tries to take into account everyone who has been infected), mortality rate is very likely still the one WHO has published and the third, case fatality rate is ~38% in the US.

rimliu• 6 years ago

What? 38 out of 100 infected in US die?

vkou5• 6 years ago

15,000 deaths (So far) in NYC. 8.4 million people. If 20% of the population has had it, the death rate is 1%... Assuming that none of the currently infected die. Which is an unreasonable assumption (As the mean time to death from the point of infection seems to be ~2 weeks, and infections have doubled over the past 2 weeks.)

kgwgk8• 6 years ago

But those currently infected are not included in the 20% of the population that has had it. Or maybe some are, but most of those infected now who may still die, do not have antibodies yet.

lukasm• 6 years ago

Yes, but the age is a 10x factor, os CFR would be much different in Nigeria (average age is about 19) and Italy (average age 45). We have two good petri dishes:

USS Theodore Roosevelt - 600 cases out of 4800. 5 sick, one dead (41 years old). which means hospitalisation is at 0.83% and CFR is 0.016% (1% dead or in hospital). Not idea what is the average age, probably around 30-35.

Diamond Princess: 700 of 3711. CFR 1.1%, average age around 50.

What worries me the most though is potential mutations and death rates when you are infected with Covid-19 and flu at the same time (or other pathogens).

https://www.reuters.com/article/us-health-coronavirus-usa-mi...

https://www.nature.com/articles/d41586-020-00885-w?utm_sourc...

rckoepke• 6 years ago

Average age on an aircraft carrier appears to be 19 [0], 20 [1], and/or 24 [2] years old.

0: https://www.nytimes.com/2008/04/20/arts/television/20jens.ht...

1: https://archive.defense.gov/news/newsarticle.aspx?id=15334

2: https://mashable.com/2016/06/23/what-its-really-like-to-live...

rallison4• 6 years ago

which means hospitalisation is at 0.83% and CFR is 0.016% (1% dead or in hospital).

0.16%, not 0.016%.

greedo15• 6 years ago

You can't measure CFR or IFR this quickly in an isolated environment like the Roosevelt due to mortality lag.

Also, the CFR for Diamond Princess is now up to 1.83%.

grumple• 6 years ago

The death rate would go up if more people had the virus at once, which is the entire reasoning behind isolating.

gridlockd3• 6 years ago

I am wondering that number, if the limiting factor is ventilators, but the CFR of people on a ventilator is close to 90% either way.

Other cases may just need oxygen supplementation, which is more manageable.

It is pretty clear now that Germany is not that far from from Italy in terms of CFR when controlled for age.

gok• 6 years ago

…when people are able to get treatment.

JamesBarney• 6 years ago

The reason the tests were randomly taken from those at grocery and big-box stores is that these were people not isolating in their homes and presumably not at work and therefore not essential workers.

cm21879• 6 years ago

I don't know what to make of that. I would expect people at work to have higher infection rate (not the least because many of these jobs involve contact with the population). It also filters out older and sick people. So intuitively I would expect to undershoot the actual rate.

CubsFan10605• 6 years ago

I read it as people shopping, not people that work there. So folks who are out-and-about, but are not in the more likely to have it groups (healthcare workers or people working at the grocery store). You're right about older and sick people.

chrisseaton2• 6 years ago

I don't understand - essential workers still going to work also have to eat, and so go to grocery shops like other people.

istorical2• 6 years ago

The sampling location isn't meant to exclude essential workers, it's meant to avoid only sampling essential workers.

IE: if you measured at workplaces that would capture only essential workers, if you measure at people's homes during work hours, you get people who mostly are quarantining, if you measure at a grocery, you might get a mix of both, etc.

rubidium3• 6 years ago

I’m an essential worker going to the grocery at 10am because there’s less people there. My hours are flexible at work and we’re set up to do staggered shifts to minimize number of people in the building.

guscost8• 6 years ago

While this is great information, a few facts will still confound attempts to speculate based on this number:

- The production of IgG antibodies is mostly delayed until after an infection is cleared.

- This is a random sample of people who were outside, it's not representative of the total population.

- Non-trivial numbers of people may never develop detectable antibodies for SARS-CoV-2:

https://www.medrxiv.org/content/10.1101/2020.04.17.20061440v...

https://www.medrxiv.org/content/10.1101/2020.03.30.20047365v...

CubsFan10605• 6 years ago

If I follow, your first and third points would indicate the number may actually be higher?

Additionally, does your third point also indicate that they will never be immune, or just that we won't be able to test for it?

guscost8• 6 years ago

All three could push the true total higher, but number two easily could push it lower instead. And I'm not a microbiologist but I think lack of antibodies only means that we won't be able to test for past infection. The seronegative patients (determined by a very precise method for measuring antibodies) in the second cited paper were still able to clear their infections.

tempsy• 6 years ago

Also don’t know if people with antibodies can still spread the virus to others or whether antibody levels (not just presence) determines whether you can be reinfected.

zucker4212• 6 years ago

I'm sorry, I don't know much about medicine so maybe you could clear up what those studies found. If I understand correctly, they both looked at COVID-19 patients and the first one found 83% had detectable antibodies and the second one found 163 / 173 had detectable antibodies? Or maybe I just completely don't understand it.

Also it looks like they chose people with symptoms (i.e. "COVID-19 patients"). Would we expect the amount of detectable antibodies to be less, more, or the same among asymptomatic/mildly symptomatic people, or do we not know?

guscost8• 6 years ago

I'm not a professional and some of this interpretation may be wrong:

In the first report, 83% of people who tested positive for viral RNA (an active infection) had immune T cells that seem able to neutralize the virus, possibly without antibodies. I don't see any information on whether these patients were also tested for antibodies later, but in theory some of them could have cleared the infection without developing any.

Another cohort of healthy blood donors was tested for SARS-CoV-2 antibodies, and among the samples that did not have them, 34% had T cells that also seem able to neutralize the virus. They note that these cells appeared to work in only one of the two ways that were observed with the PCR-test-positive patients' T cells. The idea is that this one method of neutralizing SARS-CoV-2 could be a carry-over from other human coronavirus infections in the past, and any antibodies generated by this method would be ignored by tests specific to SARS-CoV-2.

Also the seronegative healthy donors skewed female and younger compared to the PCR-test-positive patients, but I'm not sure if that is significant.

In the second report, around 5% of people who tested positive for viral RNA (had active infections), and then recovered, still developed no detectable antibodies. It's possible that more than 5% of exposed people are clearing the infection without developing antibodies, because this sample was taken from confirmed cases, and someone with pre-existing immunity may be less likely to develop symptoms.

Of course, keep in mind that both of these are preprints, and may contain methodological errors.

ccleve• 6 years ago

This study doesn't appear to suffer from the same methodology problems as the Stanford study of a few days ago. In that study, they recruited people through Facebook, and reported an infection rate that was low enough that it could have been caused by false positives.

Here, it's closer to a random sample, but more importantly it shows really high rates. Those rates overwhelm any error due to false positives.

Also, it shows numbers that are in line with our intuition. It shows higher infections in NYC, and higher infections among blacks. That reflects what the hospitals are seeing.

This study may well be really good news.

3fe9a03ccd14ca52• 6 years ago

What's weird is that the Stanford study was suggested to have exaggerated the results, since those who suspected themselves as having the virus at one time were more likely to volunteer (allegedly). However, those results were nowhere near as big as this (I think like 2%-3% versus the 20%!)

jdm22126• 6 years ago

Roughly 1/1000 New Yorkers have died of coronavirus. At a 1% IFR, that suggests at least 10% of the state has gotten the virus. Probably more, because deaths are undercounted and many people who will die of the virus already have it but haven't died yet.

In the Bay Area, almost no one has died of coronavirus so the infection rate should be next to nil.

rubidium3• 6 years ago

But we already know the actual infection rate is higher in NYC than CA. The main point that the antibody tests help uncover is death rate.

bhouston• 6 years ago

NYC and standord are markably different scenarios. But in each case the percentage of baseline infection to deaths is similarish, even though the percent compared to total pop is quite different.

TheBlight7• 6 years ago

What's interesting is if you look at the rest of NY numbers (-NYC,LI,Westchester). That has infection at 3.6%. Santa Clara was estimated to be 3% and LA county 4%. So it's in strong agreement with those areas.

cma6• 6 years ago

Exaggerated in that the California study predicted a flu like IFR (Ioannidis, one of the authors, has been pushing that as his pet theory for over a month). This shows it is more likely several times that.

dwaltrip• 6 years ago

I agree with everything you are saying. This does look like good news.

However, we should remember that this is probably a mild overestimate, as the study population was assembled from those who were out and about (shopping at the grocery store, etc). People who are more strictly staying home -- and thus less likely to have been infected -- wouldn't be included in the survey.

bob33212• 6 years ago

Another way to look at it is that 20% of people most likely to contribute to a high transmission rate already have had it, in turn flattening the curve by a considerable amount

cjhopman• 6 years ago

Sure, but a person who goes to the store 7 times a week is ~7 times as likely to have been sampled compared to someone who goes only once a week. They are also ~7 times as likely to have contracted covid-19 at the grocery store. It's likely that they are also, in general, isolating less than the other.

This sampling would have a (possibly slight, but still unknown) bias towards people who are isolating less (who you would expect to then have a higher than average percent positive for antibodies, assuming isolating is helpful).

I don't think anyone knows whether or not this is a more representative sample than the stanford study.

WrtCdEvrydy2• 6 years ago

Unfortunately, unless you go door to door knocking... you're gonna get biased data.

alkibiades• 6 years ago

going 7 times doesn’t actually increase the likelihood 7x but your point still stands that they would be far more likely to get it

ferzul3• 6 years ago

otoh, it gives about the same ifr as the recent study in geneva. at the end of the day, it looks like the first wave will have an ifr of about 0.6% - more than ten times greater than the flu, but not the bubonic plague

fyp• 6 years ago

Even with worst-case scenario of bias, this is still extremely good news. My worry was always with super spreaders who refuse to isolate but the data is suggesting that those spreaders will still soon achieve herd immunity among themselves. As long as the rest of the society behaves we will still hit zero cases relatively quickly.

(which wasn't always clear to me before since I initially predicted that this will take years to work out)

JetSetWilly• 6 years ago

In the other direction, people who are sick or have recently been sick may well isolate and avoid going to the grocery store, dragging the detection rate back down.

vkou5• 6 years ago

The major methodology problem with the Stanford study was not that they recruited participants through Facebook.

The major problem in the Stanford study was that they ran a test that has a 3% false positive rate, and found that 3% of the test-takers tested positive. (And that apparently the asymptomatic COVID-19 rate is 90+% - which does not square with the Diamond princess data).

They could have ran that same study back in 2018, and would have gotten the exact same garbage results.

zucker4212• 6 years ago

Is there a write-up for this study? Or anywhere with data/methodology released?

Also, is this particularly good news? Using the raw numbers from the headline and the deaths from here https://www1.nyc.gov/site/doh/covid/covid-19-data.page we can make coarse fatality rate estimates. I assume population of NYC is 8,400,000.

10290 / (.212 * 8.4e6) = 0.6%

Including probable deaths (which makes the death count line up more closely with excess deaths)

15411 / (.212 * 8.4e6) = 0.9%.

So it seems consistent with a IFR of 0.5%-1%. However, this doesn't account for the lag between antibody presence and death. Also, we don't know what bias sampling from grocery stores introduces, it could affect the results in either direction. Hopefully, New York releases a paper so we can get more accurate estimates.

It's good to see a prevalence study with presumably less flaws.

tunesmith5• 6 years ago

Sorry, can someone spell out how this might be good news? 21% is still a long way from herd immunity, and NYC's hospital system has been severely strained getting to this point. On top of that, the hospitalization rate still seems disproportionate to someone getting the flu - maybe it's five times as fatal, but it's > 5x the flu hospitalization rate. It's not like the virus has become less dangerous, we're just realizing how dangerous it has been, what with the impact we've already experienced.

Besides, generally if a virus is less fatal than previously expected, it means it's more contagious, meaning that much harder to get to herd immunity.

Good news would be things like: evidence the virus has mutated into something less severe; evidence of an anti-viral treatment that improves outcomes for everyone so it's not as big a deal to catch it; evidence that community spread has halted in an area and the boundaries are controlled so people in that area can feel secure they won't catch it; evidence of an impending vaccine.

Is this good news just because we're finally establishing that people have caught it once can't re-catch it for now? I guess I can see that as good news but that is so expected that it's more like it would be horrendously bad news if we found evidence that recovered people didn't have antibodies. But generally I don't really see what policy impact this has, other than identifying a pool of workers that can go work in meat-packing factories without fear of catching it again.

cm21879• 6 years ago

I don't know if the hospitalisation rate is so out of whack vs the flu. It should be higher. But does 20% of the population catches the flu in a matter of weeks?

revnode• 6 years ago

Sorry, can someone spell out how this might be good news?

It's good news because it strongly suggests that mortality is much less than previously suspected. There were numbers floating around from anywhere between 10% to 3% a few weeks back. A mortality rate < 1% is very good news because it means fewer people will die in the long run.

qqqwerty9• 6 years ago

The only good news that I am getting out of this, is that NYC seems to have avoided the dreaded 3-5% fatality rate that was the presumed worse case scenario (massive community spread, overloaded healthcare system). But the lockdown likely helped a lot, and it seems like they are seeing around 1% IFR, so I am not sure this really changes anything. Our understanding of the disease and how to treat it may also be getting better, but it still seems like if we let this thing run wild through the population (as some people on here are proposing) local health care systems will collapse and we will have a IFR orders of magnitude higher than the flu.

And as you pointed out, if the study came back with an infection rate of 50%, I am not sure I would consider that good news either. That means it would be nearly impossible to isolate vulnerable populations. So while a 50% infection rate would mean the IFR is lower, it also means opening things back up and only isolating the vulnerable would not work to protect them.

exclipy• 6 years ago

21% sounds much closer (eg. months) to herd immunity than previous estimates (eg. up to a decade).

standardUser2• 6 years ago

Every person who is infected that we don't know about lowers the estimated hospitalization and mortality rates and reduces the ability of the virus to spread (for as long as immunity lasts in the individual).

ineedasername10• 6 years ago

I couldn't find any detailed write up about their selection methods for participants, only the basics of where they found them. Without that, it is very hard to determine whether or not there's some flavor of selection bias: If it is voluntary, and they do not screen out people who report having had cold/flu symptoms, then they run the risk of attracting a disproportionate number of people who volunteer because they're curious if their prior symptoms were actually coronavirus. That would make it far from a random sample. The fact that they sampled only people actually leaving their house is also a form of selection bias: these are the people more likely to be exposed and may represent a disproportionately high infection rate as well. So I await further information.

That said, even if it's overall 0.6%, that is still 6x higher than flu, and higher than H1N1 which had a CFR around 0.1 for areas with adequate health care. (much higher when there was not adequate care, but that is not dissimilar to Covid.)

So no matter what, no one should be walking away from this study saying "See it's no big deal! Just the Flu/Cold etc!"

Retric2• 6 years ago

Flu is generally well under 0.1% of those infected on average. If you’re comparing them you want to either include or exclude asymptotic people from both populations. “Symptomatic Illnesses” https://www.cdc.gov/flu/about/burden/index.html

As to NYC deaths, many people currently infected will die in the future. You can make various estimates to account for this but a reasonable first approximation is to double current deaths based on NYC’s infection curve vs South Korea’s.

ferzul3• 6 years ago

0.6% this is the estimated ifr. comparing it to the cfr of flu is not right, which is about ten times less than the flu ifr - or about 60 times less than this figure. your conclusion is upheld, but even moreso

CodeWriter232• 6 years ago

I argue there is inherently less sampling bias in this study than testing people at the hospital who have shown up due to severe symptoms.

credit_guy4• 6 years ago

Yes, the study is really good news for NYC. My thinking is that the state of emergency, currently in place until 5/15, will be extended at most once to 6/15. After that we'll be somewhat open for business. I imagine everyone will be advised to wear mask/gloves, to keep the social distance and to keep washing hands. Lots of people will continue to work from home, others will bike to work. Being summer, the virus will not be that contagious. When the November rebound is forecast to happen, the herd immunity will be much higher, hospitals better prepared, the medical world will have learned the most effective ways to treat this disease, so the fatality rate will go down to levels seen in Germany, or lower. Bottom line, I don't think we'll have another shelter-in-place in November-December.

robocat4• 6 years ago

Being summer, the virus will not be that contagious.

I think that is still scientifically debatable, good overview: https://www.newscientist.com/article/2239380-will-the-spread...

Certainly it is still transmissible in hot countries.

laurencerowe• 6 years ago

It's really difficult to compare the currently reported fatality rates between different countries and regions since the amount of testing varies so greatly.

Compared to many other countries, Germany has likely confirmed through testing a higher proportion of its total number of cases in the country, lowering the reported fatality rate.

In countries where testing is less widely available only those already showing severe symptoms get tested disproportionately, so confirmed cases are more likely to be fatal even if they get good hospital care.

greedo15• 6 years ago

CFR has been steadily rising in Germany. Perhaps you want to cherry pick another country?

godelski2• 6 years ago

Why does recruiting through Facebook invalidate the results? If it is a representative sample it is a representative sample regardless of how people were recruited.

alteria• 6 years ago

One critique was that the segment of the population who would respond to the ad and actually test may be more likely to have experienced COVID-like symptoms.

zucker4212• 6 years ago

The Facebook ad essentially said "get tested for COVID-19 here", so very plausibly infected people could be more likely to respond.

dragonwriter5• 6 years ago

Why does recruiting through Facebook invalidate the results? If

Because “people who both use Facebook and don't automatically discount every ad or other solicitation on Facebook not from someone they personally know, especially if it invokes a major news story, because of the risk of it being a scam looking to steal personal information or do something similarly nefarious” are not representative of “people”.

eanzenberg• 6 years ago

This study is good news... I'd be interested to project the rate of infections WITHOUT shutting down the economy for what's now going on 6 weeks. Seems like it was all in vain.

8ytecoder• 6 years ago

(Reposting my comment again here)

This one's from a different company (BioMedomics) and it was a random test of people pulled straight off the streets. Happened at an entirely different geographical area (Chelsea, Massachusetts) as well. I don't want to be too optimistic but there are some signs that we are heavily under-counting the actual number of cases (at least in the US).

https://www.bostonglobe.com/2020/04/17/business/nearly-third...

mlthoughts20185• 6 years ago

The rates being this high actually casts doubt on the study. It’s very very implausible, and suggests almost surely a selection bias in the sample towards a population much more likely to have contracted it.

mlthoughts20185• 6 years ago

Actually in reading closer and seeing the data is collected at big box & grocery stores, it’s almost surely very biased.

This cohort would skew younger and wealthier, which correlates with better preexisting health and fewer risk factors, and would exclude populations who systematically left the city, or who have known heightened risk factors.

Comparing the death rate overall with the infection rate of this skewed sample would be likely to greatly underestimate the actual death rate of the virus.

zucker4212• 6 years ago

Why is it implausible? The resulting fatality rate seems close to other scientific results I've seen.

dboreham2• 6 years ago

Only 60k more deaths to go until herd immunity.

dchichkov• 6 years ago

What is the percentage of people with innate immunity to COVID-19?

Symmetry3• 6 years ago

And the specificity of the test might be worse than advertised but it wouldn't be credible that it could be making a big different with the 20% positive rate here.

smartmic• 6 years ago

What I learned from an article of a major German newspaper is that in order to really estimate the quality of testing, two criteria are important: sensitivity and specifity of the applied test.

If the real infection rate is still low throughout the population, a random sampling will not lead to reliable results (you could also toss a coin).

Although the article is in German, it is worth to have a look on the graphic in the middle of the page, it should be understandable.

https://www.sueddeutsche.de/gesundheit/corona-test-antikoerp...

hsitz• 6 years ago

Here, it's closer to a random sample, but more importantly it shows really high rates. Those rates overwhelm any error due to false positives.

I'm not seeing that, at least not from what I've seen. Whether false positives skew results significantly is highly dependent on how accurate the antibody test they used is (in addition to how large a subset of the population is positive).

This guy has an interesting visual tool that helps you to see how much a study could be affected. [1] Also, he says "Here's an interesting relationship. When a test with 95% sensitivity and 95% specificity is applied to a population with <5% prevalence of disease, MOST of the patients with positive tests are FALSE POSITIVEs." I.e., positive rate shows up as greater than 10%, when it's actually less than 5%.

Do we know the sensitivity and specificity accuracies for the antibody tests used in NY?

You'd like to think they know what they're doing. But this Bayesian stuff can be tricky, especially if they're rushing something through (esp. regarding testing of accuracy of the antibody tests themselves). And the California studies, although they seem to have some competent people behind them, seem to inflate/exaggerate the lower bound of uncertainty in their projection. [2]

[1] https://sites.google.com/view/tgmteststat/home

[2] https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...

3fe9a03ccd14ca52• 6 years ago

At what point have we scientifically reached "herd immunity"? Is it 50%, 90%, 99%?

caiobegotti• 6 years ago

https://en.wikipedia.org/wiki/Herd_immunity#Mechanics

SpicyLemonZest3• 6 years ago

Although it should be noted that incomplete herd immunity will still help, by reducing the number of other containment measures which must be taken.

grey-area2• 6 years ago

More like 50-80%, you just need spread to be impeded so that r falls below 1, but for that many people to get it would mean very high deaths, in the US 1% of 80% of 320m is > 2m deaths.

nullc2• 6 years ago

Keep in mind that if 21% of NYC residence have been infected this probably implies R0 in that population was higher than in most prior estimates of R0, which increases the threshold of immune people before R0 falls below 1.

jaynetics• 6 years ago

60-85%

1-1/R0

Most commonly the R0 of is assumed to be 2.5-3.0, but estimates range up to 6.5.

https://academic.oup.com/jtm/article/27/2/taaa021/5735319

pkaye• 6 years ago

Probably in the 80-90% range depending on the reproduction number. It would be 1-1/R0 from my understanding.

disillusioned• 6 years ago

The percentage scales with the R0 of the virus. The more infectious the disease, the higher the percentage of infected people for herd immunity to take shape and effectively push the Rt/R0 < 1.

buboard• 6 years ago

i think people misunderstand what herd immunity is. If NYC has 80% infection rate, then people within NYC can assume immunity. People outside NYC having 5% are still vulnerable

standardUser2• 6 years ago

An important thing to keep in mind is that even without herd immunity, the transmission rate gets lower every time a person obtain long-lasting immunity (assuming such a thing typically occurs with this virus). Keeping the transmission rate down around 1 becomes increasingly easier and requires less severe protocols.

vkou5• 6 years ago

If this study is accurate, and is not just working on garbage data, and if these antibodies actually mean long-term immunity, this means one of two things:

1. If the lockdown is lifted, we will see another ~60,000 to 100,000 deaths in NYC, before it will hit herd immunity.

2. Or, the lockdown will continue.

The accuracy of antibody studies has been called into doubt, and as far as I know, nobody has ever followed up on whether or not people with study-detected antibodies can catch the virus. The data for the latter is unlikely to be available until the second wave hits.

grey-area2• 6 years ago

That would be a very useful follow up study with this same population.

CubsFan10605• 6 years ago

There is no reason why an all or none approach is necessary here, is there?

By my count, 10,120/15,740 of deaths have been folks over 70. If you kept people over 70 locked down (including their caretakers), you could significantly reduce the number of deaths while increasing the percentage that have had it.

In fact, only 9% of New York's population is over 70. So theoretically (though clearly not practically), you could get over the percentage required for herd immunity while reducing the deaths by 66%

joe_maley2• 6 years ago

if these antibodies actually mean long-term immunity

This is the big unknown that seems to be largely ignored, thank you for bringing it up. I am frequently seeing "herd immunity" thrown around without any qualification on the durability of the associated antibodies.

DeonPenny12• 6 years ago

We'd also need to make the decsision to continue a lockdown over a virus with a 99.5% survival rate or not. Seeing at the flu has a 99.9% survival rate does it make sense to destroy the economy over that.

tunesmith5• 6 years ago

Hospitalization rates per infection are greater for covid than for flu. What matters is hospital capacity, to protect against greater non-covid death rates.

vkou5• 6 years ago

First of all, it's not 99.5%. A naive interpretation of these numbers is a 1% death rate, not 0.5%. 15,000 dead, out of an estimated ~1,680,000 with antibodies.

Second of all, deaths lag infections, and the actual death rate is closer to double the current death rate.

Third of all, you have no idea that if someone has antibodies, they are immune. As far as I know, nobody has tried infecting antibody-positive people... Or released studies that followed up on them, compared to an antibody-negative control group.

Fourth of all, World War II 'only' killed 3% of the world's population.

And lastly, if you lift the lockdown, and everyone gets sick all at once, the infection rate will spike dramatically. Because when hospitals are overloaded, people who can be saved are left to die. Not to mention that you'll be killing thousands of doctors, due to the high viral load they are exposed to.

legulere2• 6 years ago

Stating the survival rate really hides how there is around an order of magnitude difference in the death rate.

And that ignoring that while immunity towards various types of influenza is widespread, there is no previous immunity against COVID-19 apart from a handful of people that had SARS or MERS before.

Jeema101• 6 years ago

It's possible that a less interventionist approach by the government would also have the exact opposite effect by reducing public confidence in the response, and in the safety of going outside, since nothing is being enforced.

As Joseph Stiglitz said the other day "In those circumstances it won’t be the government enforcing the lockdown, it will be fear. The concern is that people are not going to be spending on anything other than food and that’s the definition of a Great Depression."

djrogers3• 6 years ago

The purpose of the lockdown isn't to hide until the virus magically disappears, it's to flatten the curve and allow the virus to spread slowly enough that it doesn't overwhelm the healthcare system in any given place.

Maintaining a lockdown will not lower the number of people who get the virus, it will merely extend how long it takes to get there.

lbeltrame2• 6 years ago

At least if you heard the statements of my government (Italy) from a couple weeks ago, they were hoping (or so the press said) to "reduce infections to zero".

Since then, quite obviously, they backtracked from those statements.

legulere2• 6 years ago

Flattening the curve until there is a vaccine might be the right plan for a influenza pandemic. For COVID-19 we can go further: we can bring down infection rates so much that contact tracing becomes feasible again.

usaar3335• 6 years ago

Matters where you are. The Bay Area is keeping their lockdown up so they can contact trace and crush any infection spike. Otherwise, we're going to be locked down until a vaccine at the current new case rates.

glofish9• 6 years ago

Well, it looks like in the end that much-criticized imperial model might be right on transmission rates but way off on the fatality rate and with that predicted deaths.

It pretty much looks like none of the epidemiological models are reasonably accurate on both, case numbers and fatally rates

guscost8• 6 years ago

If you're fitting a model to observations, they'll have something of an inverse (but of course non-linear) relationship. So if your virulence estimates are worse than your transmissivity estimates, or vice versa, the bad measurement is going to push the model out of whack.

zucker4212• 6 years ago

Which model and what fatality rates did they predict?

cycrutchfield4• 6 years ago

How are they off on fatality rates? Also note that the fatality rate is an input to the model, not a prediction of the model.

rallison4• 6 years ago

If the results from this NY study hold, the numbers are basically exactly in line with the Imperial College study. That study assumed an IFR of 0.9%, and the NY results imply an IFR right around that.

sjg007• 6 years ago

Is this antibody test specific for covid-19 or would it be positive on other coronaviruses? That's a real concern since the other 4 coronaviruses are endemic.

hitchhiker999• 6 years ago

What's terrifying is with all these professional analysts in here, yours is the first comment I've seen that asks this obvious question.

daxfohl5• 6 years ago

I find myself reconsidering the original proposition by England to isolate the most vulnerable for a couple months and let the virus work its course through the less vulnerable population.

If death rate is substantially lower among the under 50 crowd, this could work its way through with a fairly low death toll, and result in a herd immunity within a couple months. This slow burn approach we're doing however seems possibly to be the precise worst way to handle it, leaving the virus in the population for as long as possible, reducing the ability for our vulnerable population to avoid it.

Note I think the best possible solution is a complete lock down for a couple months until the virus is more or less eradicated, as Wuhan did. But I don't think it's a realistic option in our society.

jdm22126• 6 years ago

The outcomes aren't just death and recovery. There's also the possibility of long-term heart, lung, and kidney damage. And the blood thinners used to prevent coronavirus blood clots can cause brain bleeding. Those happen in younger people, too.

And realistically there's no way to isolate those over 50. They generally live with, work with, or are cared for by younger people.

taeric27• 6 years ago

This feels like fear talking. As more data comes in, we are seeing more people with no affects. Not just mild, but nigh non existent.

It is agreed that something gives people severe cases. Severe includes death and recovered with damage. We don't seem to have data letting you know who or what would land there.

eloff5• 6 years ago

Yes, recovery is not binary. Even if you recover fully you've expended some percent of your finite lifetime capacity to heal your organs. It may well have taken years off your life. That's true for other illnesses to. The flu doesn't just cost you a week of productivity.

DeonPenny12• 6 years ago

Wouldnt that mean quartine would never work because it make sense that those younger people going outside would make those 60 olds sick regardless of the quarantine.

daxfohl5• 6 years ago

But that's going to happen anyway because people will catch it until we hit herd immunity. Unless a vaccine comes out before we get there, which seems pretty iffy at this point.

I do think we can plan for the isolation of that population for a couple of months if we have some strong leadership. Unfortunately that seems to be lacking right now.

eloff5• 6 years ago

All things equal, it would be better to get it out of the way sooner. However, what it doesn't account for is:

1) can we flatten the curve enough that some people never get it because we get a vaccine?

2) can we flatten it until we find an effective treatment protocol, saving lives?

3) if we did nothing would the hospitals be overwhelmed leading to additional loss of life and a higher death rate?

The first two are speculative, but the last one is pretty much certain looking at Italy and NYC. Without lockdown it could have been so much worse.

luckylion2• 6 years ago

If we prolong it a lot with all the associated cost and 1 and 2 never happen, we've lost not just a large part of the economy, but also lives without anything to show for it.

daxfohl5• 6 years ago

Yeah, I have less and less hope in a vaccine. We'll likely be well on the way to herd immunity before one is ready.

For #3, I agree. I'd be interested to see the math on how many under-50's need hospitalization, ventilation, and how severe of an additional effect would that have. It may be that it requires less medical capacity to support a high percentage of the healthy population contracting the virus, than a far lower percentage of the general population (including over-50 crowd) contracting it. Or it may require vastly more capacity. I have no idea.

The other thing to take into account is the effect dragging this out has on developing economies. It seems like this is shutting down international supply chains and food shortages could result. So that's what's got me feeling like more aggressive action should be considered.

lbeltrame2• 6 years ago

Option 2 can be the most realistic, depending on the outcome of the currently-going clinical trials. There quite a bunch closing by June (although most of these are on repurposed drugs, and with not too large sample sizes).

Reedx• 6 years ago

Sweden didn't lockdown and might have herd immunity in weeks, according to their chief epidemiologist. It'll be interesting to see how this plays out in the long run.

“In major parts of Sweden, around Stockholm, we have reached a plateau (in new cases) and we’re already seeing the effect of herd immunity and in a few weeks’ time we’ll see even more of the effects of that. And in the rest of the country, the situation is stable,” Dr. Anders Tegnell, chief epidemiologist at Sweden’s Public Health Agency

Tegnell said sampling and modeling data indicated that 20% of Stockholm’s population is already immune to the virus, and that “in a few weeks’ time we might reach herd immunity and we believe that is why we’re seeing a slow decline in cases, in spite of sampling (testing for the coronavirus) more and more.”

https://www.cnbc.com/2020/04/22/no-lockdown-in-sweden-but-st...

cm21879• 6 years ago

It might be herd immunity. If might also be that this disease is seasonal. Either way it is an interesting metric.

m4rtink• 6 years ago

I would not really call the Swedish model successful - Czech Republic and Sweden have both about 10 million inhabitants.

Things moved pretty quickly to pretty comprehensive lockdown here in Czech Republic, including mandatory mask wearing. So far this seem to be effective, with combined death toll currently at 210. In comparison Sweden has almost 10x as much, 2010 dead.

Looks like if more has been done less people could have died, not to mention the alarming news about organ damage, virus resurgence and questionable long term immunity.

deanclatworthy• 6 years ago

I don't get it. We have numerous reports of the antibody tests being inaccurate. We have numerous reports suggesting you can get the disease twice => once does not equal immunity. So how exactly are these Swedish scientists testing for immunity?

greedo15• 6 years ago

Sweden hasn't done a government mandated lockdown, but has a lot of social distancing occurring. Also, I wouldn't use Sweden as an example of herd immunity since antibody tests are only coming on line, and many are unreliable. Besides look at Sweden's CFR. Not something I'd like to see in a modern country.

klmadfejno4• 6 years ago

I've been making many posts arguing against the efficacy of lockdowns (and been getting shat on by points I find mostly naive). I think something like this is probably the best approach because it minimizes economic harm while also trying to minimize hospitalization rates among the elderly.

But even if we pretend we could implement a perfect bubble for everyone over 50, they're not especially safe when the lockdown is lifted for them. The virus will still exist, and people over 50 tend to spend time with people over 50 (see: homophily). Once it enters the social network, herd immunity doesn't exist because your local community of old people are both super vulnerable to acquiring the disease and few of them have immunity from past exposure because of the lockdown.

Locking down the country until the virus is eradicated is not a realistic option and its incorrect to think Wuhan has "done" this

formercoder2• 6 years ago

Any time I try and make counterpoints to lockdowns or even logical evaluations of them online the downvotes and hate start flowing. There is a huge bias among those in our circles towards locking down as long as possible, because all of us can work from home and aren’t worried about feeding our families.

TheCowboy3• 6 years ago

I've been making many posts arguing against the efficacy of lockdowns (and been getting shat on by points I find mostly naive).

I skimmed some of your comment history. Your comments aren't as rock solid as you believe, and there are many points either glossing over things or complete ignorance.

More people will die if the lockdown is lifted, and many of those who would have died anyway will die sooner.

Are you really arguing many would have died anyways? How many? What percent? You're ignoring the reality that in regions with overwhelmed healthcare systems they're having to engage in triage (read: many people are dying who would not have died anyways) since they cannot treat everyone. This isn't just for covid-19, but for people with other treatable conditions.

wvenable• 6 years ago

But even if we pretend we could implement a perfect bubble for everyone over 50, they're not especially safe when the lockdown is lifted for them. The virus will still exist, and people over 50 tend to spend time with people over 50 (see: homophily).

The point of the lock down is to prevent the spread of the virus from happening too fast and overwhelming the healthcare system. It is not to prevent people from ever getting it as that's clearly not possible. You seem to be missing that point in your argument.

djrogers3• 6 years ago

I'm starting to wonder if there aren't 2 (or more) transmission methods for this virus with differing symptoms. Aerosol transmission with 'I got a cold' type symptoms, and droplet transmission with 'I got the worst cold I've ever had' type symptoms.

grandmczeb8• 6 years ago

Why would different transmission methods result in different symptoms?

taeric27• 6 years ago

Viral load, is what this typically refers to. Akin to an allergic person seeing one cat versus a room full of them.

And, of course, for some people with allergies, contact where a cat has been is enough. ;)

So... Complicated.

Edit: was corrected down thread that this is infection dose, not viral load.

etimberg• 6 years ago

Perhaps different amount of viral load

gridlockd3• 6 years ago

Another factor couldd be where the virus load lands - in the lung or the throat.

TechBro8615• 6 years ago

So, at what point can we declare the lockdown to be a harmful overreaction and start opening countries up? Will we hold anyone accountable for models which proved to be pessimistic by orders of magnitude, causing implosion of economies around the world?

chasd004• 6 years ago

has anyone modeled at one point deaths from economic collapse overtake deaths from Covid19?

bbarn2• 6 years ago

That was the first thing I said, 2 months ago, and got told I was a selfish asshole and had no clue what I'm talking about. This is going to be a real big history lesson for our grandchildren on how not to handle a situation in one way or another, unless the media rewrites the narrative.

Oh, wait.

robocat4• 6 years ago

I would be very sceptical about any models produced in the US, since the issue is so partisan, and one can tweak variables to prove whatever outcome one wants from a model.

I think the lost life-years of economic hardship could easily outweigh the lost life-years of Covid deaths. That is because economic hardship affects younger people, while Covid deaths primarily affect people with not many years left to live. But there are many other external costs (social costs if your grandma dies) and economic benefits to deaths (lower pension payments, home availability?).

However, given current information, a lockdown for weeks to months seems to make sense, since the consensus is that economic collapse is not yet immanent, and that steps can be taken to help keep the economy spinning when lockdown restrictions start to be relaxed.

sacred_numbers• 6 years ago

I think,if anything, that this new data validates the lockdown. New York City has been hit hard by this virus (0.2% of the population; for comparison 0.3% of the US population died in WW2) and there are still approximately 80% of the population that hasn't gotten it yet. If 70% of the population of NYC ends up getting it over the next few months, that would mean something like 50k to 60k dead just in NYC. If 70% of the US population ends up getting it that would be 1-2 million dead. Locking down in the face of those numbers is not an overreaction, although maintaining lockdown until a vaccine may be an overreaction. I think we should be devoting huge amounts of resources to manufacturing face masks and testing kits so that we can safely ease out of lockdown without causing more outbreaks like we saw in New York or Italy. Ending the lockdown without a plan, though, is highly unethical in my opinion

outworlder• 6 years ago

Sure, let's ignore the hospitals getting overloaded.

luckydata• 6 years ago

you're getting the wrong message from all of this.

thehappypm2• 6 years ago

This data might suggest that the lockdowns suppressed the infection rate down to 20% at this moment in time.

Without a lockdown, a month more of infections would have likely bumped NYC to achieving herd immunity, or 60-ish percent, since 20% to 60% does not take long with exponential growth.

This means two things. One, it would mean that we would have almost certainly overwhelmed the hospitals with triple the rate of infections. We've be leaving people dead in the streets and it would be a humanitarian disaster as every hospital was at double capacity.

It would also have meant that the curve would be flattened for good.

joe_maley2• 6 years ago

It would also have meant that the curve would be flattened for good.

I have yet to see any evidence that covid antibodies provide long-term immunity. We can't say with any certainty that the curve would be permanently flattened. It may just be flattened for a few weeks, a few months, or a few years.

esoterica2• 6 years ago

0.18% of the entire NYC population is already dead from the coronavirus and by the time this is over the number will probably reach or exceed 0.3%.

If you want the whole country to get herd immunity you will probably see similar mortality rates across the country. 0.3% of the US population is 1 million people. How have the models been proven to be "pessimistic by orders of magnitude?

cdash• 6 years ago

Just so you know, around 3 million people die in the US every year, many of the million people you expect to die would have ended up being counted in that 3 million background statistic.

More importantly, herd immunity is the ONLY solution on the table right now, the lockdown is not about stopping the virus in its tracks. It is about spreading it out over a period of time.

bbarn2• 6 years ago

At the point where more deaths are caused by the global socio-economic collapse than COVID-19 would have caused at even pessimistic projections.

At this point, I'm not convinced in either direction.

greedo15• 6 years ago

You're assuming the economy wouldn't have collapsed in the faced of the pandemic.

amalter• 6 years ago

That the 0.5% death rate in NYC is not higher is _because_ of the pause. We saw the death rates spike at the peak of the curve. We saw the hospitals near total collapse. We even have an example of what would happen if we didn't flatten the curve (Northern Italy). We have another counterexample of California that shows NY's pause was late.

I guess Sweden is the counter-counter example. I think the US would have needed to have built out a far different medical system to achieve what they have.

For a few days at the end of March and beginning of April, the hospitals came so, so close to collapsing. Just a few more days up the curve and we would have run out of beds. (In reality, we did run out of beds, as you can see stories of many turned away from hospitals in those dark days, but it wasn't quite a systematic collapse).

All of this happened, we were here to record it. Models are models, and we're in the early days of a deadly, virulent, confusing pandemic. But there is no doubt that our reactions and solidarity saved lives. The imperfect models helped us get there.

Now, there is a more reasonable question of where do we go from here. For urban metropolis like NYC, I think a slow re-open like Germany. We slightly open the spigit so that 20% becomes 40% becomes 60% (and hopefully immunity is immunity) and we achieve herd protection (at great cost).

And likely the less dense, the slower we'll need to go (depending on hospital saturation).

I certainly will cheer the scientists who took the best information they had at the time and worked with the leaders to make the best decisions they could. Yes, I will indeed hold them "accountable".

greedo15• 6 years ago

I'm holding judgement on Sweden since their numbers don't look as good as people are claiming, and the pandemic is still young.

ineedasername10• 6 years ago

So I await further information.

So no matter what, no one should be walking away from this study saying "See it's no big deal! Just the Flu/Cold etc!"

SketchySeaBeast4• 6 years ago

Do you have a source for the CFR of 0.1 for H1N1? I could only find this[1], which is a much smaller number.

[1] http://news.bbc.co.uk/2/hi/health/8406723.stm

ineedasername10• 6 years ago

You may be looking at "settled" numbers when all was said & done and all facts were known. That's not an "apples to apples" comparison with current covid-19 knowledge.

Here's my source [0] and the relevant quote, below. It is the CFR during the H1N1 pandemic, 10 weeks into it, which is why it is a much more appropriate (though not perfect) "apples to apples" comparison with Covid-19:

"The overall case fatality rate as of 16 July 2009 (10 weeks after the first international alert) with pandemic H1N1 influenza varied from 0.1% to 5.1% depending on the country."

[0] https://www.cebm.net/covid-19/global-covid-19-case-fatality-...

mrb3• 6 years ago

If this study is accurate, then 1.8 million NYC resident are infected. So 15 411 deaths (as of today, including 5 121 probable deaths) suggests COVID-19 has a fatality rate of MINIMUM 0.9% which is in line with previous estimates (between 0.5 and 1.6%) and this is MINIMUM 9 times more fatal than the flu (0.1%).

Edited to add "MINIMUM", as there is a lag between case detection and death (I should have known better to mention it, as I blogged about it: https://blog.zorinaq.com/case-fatality-ratio-ncov/)

izend• 6 years ago

Making it the worse pandemic in decades but no where near the Spanish Flu.

mmastrac• 6 years ago

Hard to compare directly against the Spanish Flu as medicine has had 100 years of progress, but assuming you are talking about overall impact, agreed.

vladislav• 6 years ago

The Spanish flu had a smaller outbreak in the Spring and came back with a vengeance the following Fall, so hold that thought.

https://www.history.com/news/spanish-flu-second-wave-resurge...

rechristened• 6 years ago

Or as bad as the 1957-8 "Asian Flu" that most people haven't even heard of.

dragonwriter5• 6 years ago

Well, sure, but the “Spanish” flu (only called that because Spain is the first country severely hit that didn't lie and cover it up because of WWI) was accelerated by both the physical conditions created by WWI and the fact that covering it up to avoid revealing weakness to wartime opponents hampered response in many early-hit countries and obstructed information flow.

It's also nowhere near the HIV/AIDS global epidemic in likely total impact, but it's a lot more acute in it's impact than HIV/AIDS.

mrb3• 6 years ago

I disagree. It's simply too early to make that determination.

The Spanish Flu had a estimated infection fatality ratio of >2.5% (https://wwwnc.cdc.gov/eid/article/12/1/05-0979_article). As another commenter pointed out, the COVID-19 IFR is 0.9% in NYC. The difference between 2.5% and 0.9% is only 2.8x. However the IFR is not only underestimated due to the lag between case detection and death, but it's also probably a lot worse in many other parts of the world (third world countries, etc). So it's possible the difference is only 2-fold, which would make both pandemics relatively comparable.

disantlor• 6 years ago

these comparisons to the flu usually don't seem to factor in transmissibility. seems you cant leave that out of the equation and only look at death rate

formercoder2• 6 years ago

It’s important to know how risky it is to get this thing. That way we can make informed decisions about opening up.

SAI_Peregrinus• 6 years ago

And also the risks of non-death injury from it. Long-term reduced lung function isn't good.

vikramkr• 6 years ago

Cuomo made the caveat during the press conference that these samples were collected in grocery stores etc, so might be higher than people at home etc

edit: and also potentially lower than in the essential worker populations. So some caveats to keep in mind

asah• 6 years ago

omg yes - tons of people switched to grocery delivery esp since NYC has so many terrific options and virtually every grocery, market & specialty store already delivered, even before COVID.

DeonPenny12• 6 years ago

It's also lower than the 3% that was predicted that people used to justify the shutdown and closer inline with the swine flu or rotovirus.

empath75• 6 years ago

Nobody ever seriously suggested it was 3%. The estimates were always around 1%

rallison4• 6 years ago

An IFR of 0.6%, with 2/3 of the US infected (about what you'd need for herd immunity at an R0 of 3), means ~1.3 million deaths. That's well in line with the models. The distinction between CFR and IFR was not news to the experts.

SketchySeaBeast4• 6 years ago

Regardless of initial estimates, how is 0.6% - 1% "closer inline" to 0.026%[1]? Even based upon the low range that's 30X more fatal.

[1] http://news.bbc.co.uk/2/hi/health/8406723.stm

gdulli• 6 years ago

The shutdown addresses more qualitative aspects of the situation. Even if flattening the curve doesn't reduce the area under the curve, it still avoids a potential large numbers of otherwise avoidable deaths because fewer people have it at once, keeping hospitals under capacity, and more people will get it later when we know better how to treat it.

And the earliest predictions have to be the least accurate, because they're based on the least amount of data. But early on is when you need to act.

dragonwriter5• 6 years ago

It's also lower than the 3% that was predicted that people used to justify the shutdown and closer inline with the swine flu or rotovirus.

The shutdown wasn't, and isn't, based on the fatality rate under current conditions as much as the shape of the curve of various medical resources being required (total hospital beds, ICU beds, ventilators, PPE for healthcare workers, etc.), the anticipated speed of being able to bring more online, and the likely impact of exceeding available supply on death rates and other health outcomes, both for COVID-19 victims and patients with other health conditions. (A potential problem which was significantly realized in Italy, where things like ventilators were for a while allocated based on other factors besides medical need, since the number with need exceeded the supply.)

It's important to remember that the fatality rate of a disease isn't a constant, and changes to conditions (like, we can no longer provide ventilators to everyone who needs one) can change that rate.

greedo15• 6 years ago

You're conflating CFR with IFR.

ashaiber• 6 years ago

The city itself actually estimates a total of 15,411 deaths so far the the figure is already closer to 0.9%, and there are still people dying in the city every day so will likely end up a bit higher (of course, all of this assuming the study actually represents reality).

https://www1.nyc.gov/site/doh/covid/covid-19-data.page

pjc50• 6 years ago

So .. drawing a line between two points, if NY had 20% immunity for 15k dead, that implies there will be 60k dead by the end of the process. Roughly one 9/11 every week or so?

Merrill• 6 years ago

You also have to adjust for the people who are already sick but haven't died yet. That would likely get you somewhere between 1 and 1.5%. So for herd immunity in the US at 200,000,000 recovered, that would be 2 to 3 million. That's consistent with earlier projections.

dragonwriter5• 6 years ago

If this study is accurate, then 1.8 million NYC resident are infected. So 10 290 deaths (as of today) suggests COVID-19 has a fatality rate of 0.6%

No, it doesn't, because the usual time to death, if it causes death, isn't zero, so you need to compare the number of deaths a couple weeks from now with the number of infections today to get a closer-to-accurate number.

Also, you are using the 10,290 confirmed deaths and i ignoring the 5,121+ additional identified probable COVID-19 deaths. So, between those two things, the actual fatality rate if the current infection estimate from this study is right is probably 2-3 times the figure you cite.

mediaman• 6 years ago

Interesting thought experiment: if NY daily deaths over the next two weeks average 400, that's 5,600 upcoming deaths from people presumably infected now. If about one-third of deaths are not accounted for (5,121 unidentified as a portion of identified+unidentified), then we'd have about 8,400 new deaths projected over two weeks including the likely unidentified deaths.

As a percentage of those who were infected as of this study, that's a 1.3% infection fatality rate.

Obviously some conjecture and estimates there, but it seems to be on the high range of early estimates (though much lower than the 3%+ rates derived from CFR with undercounted denominator).

mrb3• 6 years ago

You are correct, edited.

gridlockd3• 6 years ago

The time to go positive on an antibody test is not zero either, probably 7 to 14 days. Also the infection rate is lower now than it was in the past. I doubt this adds up to more than 50% higher mortality.

joe_the_user• 6 years ago

Also,

I don't the flu's fatality is calculated against every exposed to the flu but against everyone who gets sick with the flu. If the flu also 50% asymptomatic exposed individuals, that would know it's fatality rate down further for comparison's sake.

mdavidn• 6 years ago

We calculate both. Case fatality rate (CFR) is based on patients who test positive, whereas infection fatality rate (IFR) is based on all infections. We don't yet have adequate random sampling to have confidence in IFR estimates.

bo1024• 6 years ago

Note that deaths lag positive cases by some time (2 weeks maybe?).

wtvanhest6• 6 years ago

The study is biased in that it pulled samples from a grocery store based on people opting in. If I walk in to a grocery store and someone offers to give me this test, I am going to say no for 2 reasons:

1) I have not been sick since last fall

2) I don't want to take additional risk getting bloodwork done by someone who is testing people for covid19 antibodies. I want to take a little risk as possible and return home to my family.

So basically this test only possibly grabs people who are willing to risk going to the grocery store rather than having food delivered, and who are willing to take on additional risk of getting tested. It is even less likely that a person not taking risk, who never had any symptoms would get tested than a person who had had symptoms.

The entire premise that this represents the population as a whole is completely flawed.

Symmetry3• 6 years ago

I hope that the numbers stay at .6% and that the difference from previous estimates might even be improvements we've made in figuring out how to care for people suffering from Covid-19. But I remember being happy at how low South Korea's numbers were when their epidemic peaked and receded then watching the case fatality rate slowly climb up to the 2.2% it's at today. So I'm not counting any chickens just yet.

greedo15• 6 years ago

Be careful not to conflate CFR with IFR. CFR is the number of deaths divided by the number of confirmed cases. IFR is deaths divided by total infections. It's hard to determine IFR, but CFR is almost always an exaggeration of the risk.

LandR• 6 years ago

I feel a blanket IFR figure isn't all that helpful.

Won't there be a high level of age stratification in there. Over 60, death rate will be way higher than if you are younger and probably close to zero under 20.

It seems better if we could have a risk per age group to see who can go back to a somewhat normal life and protect the most vulnerable.

urda• 6 years ago

Please don't use uppercase for emphasis. If you want to emphasize a word or phrase, put asterisks around it and it will get italicized.

duxup• 6 years ago

It sure would be nice to find out the virus is far more widespread / exposure is higher than expected if only that would seem to indicate that the light at the end of the tunnel is nearer than we think ... and a lot of people have been exposed and doing well.

cryptonector4• 6 years ago

At 21% it would be time to end the shutdown.

EDIT: Read the comments below.

zucker4212• 6 years ago

That doesn't make sense to me. I would think you'd want to get to the point where you've reached the carrying capacity, so that "overshoot" of the equilibrium doesn't result.

cryptonector4• 6 years ago

See my other reply below. You can't overshoot 100%, and long before we get there herd immunity takes hold, and there's no question of the disease being kept from working its way through -- only a question of managing the rate at which it does. All in all the economic damage of continued shutdown does not make sense at this point (at 21% of the population exposed). We should stop now.

SketchySeaBeast4• 6 years ago

I'd think it'd be decided based upon the new cases and hospitalization and death rates, not an estimate of population with exposure.

cryptonector4• 6 years ago

Sorry, but that's dumb. If 1/5th of the population has been exposed, then you know the total strain on the healthcare system is extremely unlikely to top an additional 4x what it has been, but not only it has 1/5th the population being exposed not in fact been enough to overwhelm the healthcare system, as more of the population is exposed you begin to get herd immunity, so in fact the total strain on the healthcare system is extremely unlikely to reach a total of 5x what it has been, very likely not even half that.

Give all of that, it makes no sense to continue the shutdown considering how costly the shutdown is.

To those who think this is a question of saving lives, that's not so. At this point the disease will work its way through the population because there's no time to finish testing, producing, and distributing a vaccine, which means the only question is of managing the maximum load on the healthcare system. Moreover, many of the most vulnerable have been hit already, and those who haven't can be protected by measures far short of a shutdown.

No, at 21% it is most definitely time to stop the shutdown. (Note: not all the measures, just the shutdown.)

ummonk4• 6 years ago

0.2% of people in NYC has died from Covid-19, so this is exactly what we would expect.

lettergram• 6 years ago

I’ve continuously questioned the antibody tests...

My understanding (from NBC news) was that at least some of the antibody tests were derived from a couple who were on the princes cruise. They never showed symptoms, but tested positive. IMO it’s quite possible that they never had it and those tests were inaccurate (right at the start of the outbreak, no symptoms, etc).

Further, these antibody tests likely weren’t fully vetted nor were the samples they derived it from. For instance how often does another coronavirus set off this antibody test?

Personally, I’m just waiting to see. I actually do suspect 20% have been infected, so it fits my expectations, but that’s not validation.

aazaa• 6 years ago

In his press conference today, Governor Cuomo revealed the preliminary results of a first-phase antibody test that surveyed 3,000 New Yorkers over two days in 19 counties at 40 locations that included grocery and big-box stores. The sample suggests that 13.9% of New York State residents have the antibodies, meaning they had the virus at one point and recovered. Of the regions tested–Long Island, NYC, Westchester/Rockland, and the rest of the State–New York City had the highest positive rate at 21.2%. The potential good news to come to light is that the death rate may be far lower than some estimates, at 0.5%.

This still is not a random sampling. It only samples from shoppers at grocery stores and big-box retailers. Imagine doing the same study, but of people who ordered groceries online only. Would you expect to see big differences in exposure rate? I think so.

The study itself isn't linked anywhere, nor have I seen it elsewhere. Science is all about the details. It's not hard to imagine half a dozen ways that the bottom line result of this study could have been skewed by decisions made by the study authors and ground team.

t2riRXawYxLGGYb• 6 years ago

This was my thought exactly. Some of my friends in the Bay area got COVID-19 (confirmed positive tests) after quarantining for over two weeks at home and taking all of the precautions. The only place they had been was the grocery store, so they suspect that they got it there.

usaar3335• 6 years ago

Are they not taking public transit? Your friends must be some of the most unlucky people ever. The Bay Area has had under 3k cases since the start of April outside group living settings (nursing homes, homeless shelters, etc.). That's ~1/2000 chance of getting covid from anywhere outside.

mhandley• 6 years ago

The incubation period runs out to around 27 days, though above 2 weeks is uncommon. It seems possible one of them already had it before quarantine, and just happened to be one of those who had a long incubation period.

https://www.worldometers.info/coronavirus/coronavirus-incuba...

killion• 6 years ago

I'm in the East Bay and was quarantining for almost a month before my symptoms showed. I also assume I got it at the grocery store since that was my only outing.

arrrg• 6 years ago

The death rate of 0.5% falls right in the range of what modelers have been using, by the way. Not exactly very positive news.

nikolay2• 6 years ago

Yeah, still 150,000 death toll if everybody gets infected. And this is not considering the permanent lung and other tissue damage that's getting reported from "recovered" patients.

newacct5837• 6 years ago

Right. Really this study is just confirming (with higher error bars than we'd like) what we already strongly suspected.

Note that as others are pointing out, that 0.5% isn't really extrapolated correctly. The tested case deaths are looking like they're only 70% of the total or so. Also using a current death count with contemporary infection counts is a mismatch, because it forgets that ~35% of the people currently in the hospital won't ever leave, which is about 5k more deaths.

So a better calibrated CFR might be 1% or so, which is even closer to the range we've all been assuming.

hcknwscommenter7• 6 years ago

It is very positive in that we can be more confident that our assumptions are close to reality. 0.5%*330M still equals 1.65M deaths, or (very roughly) 5M ICU beds. Spread out over 52 weeks, that's a lot of ventilators and ICU beds and PPE, but it is a target. A very big juicy target that we can and should aim directly at, and HIT.

shironineja• 6 years ago

So if 100% of the USA gets it at 330 M people that amounts to:

1,650,000 deaths.

It is unlikely 100% will catch it from a single wave however.

CubsFan10605• 6 years ago

Which is about 1/2 of what die in a normal year. The real question is how much do those circles overlap.

Are we saving lives, or are people now dying in June that would have died in November anyway?

wh1t3n01s3• 6 years ago

Herd immunity will cap the total %! The second wave will be less contagious where current infection rate is higher.

TheBlight7• 6 years ago

Sure all of these studies are potentially flawed but they're all generally pointing in the same direction. There are many more infections than we know about and the CFR is not anywhere close to the actual IFR.

NYC is an outlier with a 21% infection estimate but for the rest of NY (outside NYC metro/Westchester/LI) the estimate is 3.6%. Santa Clara estimate was 3%. LA County estimate was 4%. Seems like a trend is developing.

slg9• 6 years ago

There are many more infections than we know about and the CFR is not anywhere close to the actual IFR.

That is the optimistic takeaway.

The pessimistic takeaway is that even the hardest hit areas are nowhere near herd immunity levels and that we are either going to be isolating until a vaccine is created or we can expect to see a lot more death once nonessential people are forced back to work.

jnbiche2• 6 years ago

The CFR will be much higher than the IFR. For example, approximate flu IFR is 0.05%.

Karrot_Kream• 6 years ago

Sure all of these studies are potentially flawed but they're all generally pointing in the same direction

That's unfortunately not the way statistics works. Combining multiple bad tests just makes the results incorrect or highly uncertain; the devil often is in the details. The Stanford/Santa Clara County study is a good example of how the details can really undermine a study.

Things do indeed seem to be converging to the idea that the CFR is not near the IFR, but none of this is new news, and the IFR remains very close to what most epidemiological predictions indicated early last month. If anything, it confirms that COVID is a difficult beast to tame.

monadic22• 6 years ago

Sure all of these studies are potentially flawed but they're all generally pointing in the same direction.

How on earth could you differentiate this from the sample bias?

wtvanhest6• 6 years ago

"Preliminary test results suggest 21% of NYC residents have Covid antibodies"

Should be re-written as:

"Preliminary test results suggest 21% of of people approached in a crowded grocery store and who would agree to give blood have Covid antibodies"

All of these tests suffer the same sample bias, and that sample bias is massive.

People who are already in a grocery store (risky behavior), who are willing to give a blood sample (believes they may have been previously exposed) are not the same as people who are leaving their house only for very limited purposes and ordering food online.

If we assume that the % of people shopping in grocery stores and willing to take the test are in risk group A, and the people not shopping are in risk group B. We can run the following quick analysis.

First, assume risk group A is 5 times as likely to have had COVID than Risk group B (but plug any assumption in there necessary)

Then assume that risk group A is only 10% of the population, then rerun the numbers as follows:

For every 100 people in risk group A who tested, 21 were positive.

Risk group A is 100 people, and risk group B is 900.

Risk group A's 100 were 21 prior positive. Risk group B's 900 could be estimated that 4.2 people per 100 were positive, so in total of the 900 people 37.8 were positive.

21+37.8 = 59 people of 1000, or 5.8%.

Plug any numbers you want in the analysis, but the assumptions drive huge variability in the % of New Yorkers infected. Without a less biased sample, we really don't know much other than that way less than 21% of New Yorkers have anti-bodies.

ummonk4• 6 years ago

Since false positives can be low single digit percentages, anything outside the NYC data is pretty meaningless, and a bunch of meaningless data is still meaningless.

jonahbenton• 6 years ago

Death counts in NYC, combined with a 1% CFR, indicate that the number of infected was ~1.5M 3 weeks ago; probably 2.2M now. That's about 25%.

kurthr2• 6 years ago

Nope, because they're all designed to skew higher. People who are out shopping, people who will go out of their way on a weekend to be tested, healthcare workers... all of them are likely skewed high. One might as well conclude (with as much evidence) that the purpose of the tests is to show higher infection rates. Still, nobody doubts that we're under testing by a factor of 3-5x to catch a majority of cases.

What's disturbing is that if you take the estimated statewide data of 2.7M infected (out of ~20M) at face value and only the current 21k dead you still get 0.7-0.8% fatality rate.

badfrog5• 6 years ago

New York City had the highest positive rate at 21.2%. The potential good news to come to light is that the death rate may be far lower than some estimates, at 0.5%.

How do they get to 0.5%? According to NYC data if you include "probable" cases, 15,400 people, or 0.18% of the population, are already dead. Wouldn't that imply 0.9% fatalities if the whole city was infected?

guscost8• 6 years ago

It would not be ruled as a significant factor leading to death in many of those cases, and for the rest, NYC residents might be more at risk due to higher average viral dose (subways). Also there is a lag in IgG antibody production, the test has imperfect sensitivity, and some portion of exposed people may never develop detectable antibodies. Some of these confounding variables are probably baked into the estimate.

schrodinger• 6 years ago

Maybe that’s including the large number of deaths that are presumed COVID but weren’t officially confirmed by a test?

kevindong• 6 years ago

The data that NYC publishes daily is super interesting since it breaks down cases/deaths by race, gender, age (group), and presence of underlying health conditions [1].

The gist of it is that the majority of deaths from COVID-19 were suffered by people who had some kind of other health issue. As of the most recent data (April 22 at 6pm), 61 deaths were from people with no underlying health issues, 7,474 from people known to have underlying health issues, and 2,755 from people with unknown status [0]. The elderly in poor health are much more likely to die than the young in poor health. But when healthy, the elderly have pretty close to the same fatality rate as the young [2].

[0] https://www1.nyc.gov/assets/doh/downloads/pdf/imm/covid-19-d...

[1]: Bottom of this page: https://www1.nyc.gov/site/doh/covid/covid-19-data.page

[2]: Cross reference this with [0]: https://www1.nyc.gov/assets/doh/downloads/pdf/imm/covid-19-d...

CydeWeys6• 6 years ago

This still is not a random sampling. It only samples from shoppers at grocery stores and big-box retailers. Imagine doing the same study, but of people who ordered groceries online only. Would you expect to see big differences in exposure rate? I think so.

There's a larger, related problem with this: It's way over-sampling people who go outside a lot and make unnecessary trips, and undersampling people who don't. I'm in NYC and I'm only going to one store a week (the grocery store). So I'd have much less chance of being included in this study than someone who hasn't changed their habits and is still shopping much more frequently. And there's a direct correlation between how often you're going shopping and how likely you are to have been exposed to COVID-19.

So yeah, it's very far from a random sampling, and it is specifically over-sampling people who are more at risk. So I'd take it with a grain of salt; it could actually be way off.

They should've activated the jury selection tool for this and gone to people's apartments to draw blood. That way they'd correctly sample the people who aren't leaving home at all, or only do so rarely.

capkutay2• 6 years ago

This still is not a random sampling. It only samples from shoppers at grocery stores and big-box retailers. Imagine doing the same study, but of people who ordered groceries online only. Would you expect to see big differences in exposure rate? I think so.

I'd expect people who still do their own grocery shopping and go to big box retailers to be a better sample of the population than hacker news' audience definition (ordering from instacart/whole foods, working on Zoom/slack all day).

The vast majority of the population does not have the privilege that many people in the tech industry do. Going to a grocery store is a pretty basic activity in most of the population. People who get their groceries delivered online and can maintain their livelihood being on Zoom calls all day are probably statistically insignificant enough to be covered in the sampling error.

mantap2• 6 years ago

It's not black and white. A person who goes to the store more often has a greater chance of being tested, than someone who goes infrequently.

There's also the issue that people are trying to avoid other human beings right now, including the human beings administering tests. People who are social distancing more effectively are less likely to agree to a test.

mirimir• 6 years ago

Sure, but it's still data for the groups that they sampled. It would be better to have data for truly random samples.

But even then, you'd want demographic data for each subject. And then you could compare appropriate subsets of the results with this study.

With such data, you could explore risk factors, effectiveness of quarantines, and so on.

not_a_moth• 6 years ago

Except your hypothetical "never leave house" population is probably <5% of the population - every single person I know is still going out to public places at some time during the week.

Mikeb853• 6 years ago

I literally made the same comment a few days ago but here goes: every thread about a study such as this one is has criticisms concerning the scientific accuracy even though all these studies point to the same conclusion and not one of them provide evidence to the contrary.

This isn't exact science, we're in the middle of a pandemic. But all these antibody studies are pointing towards the same conclusion.

smacktoward• 6 years ago

Do they all use the same testing mechanism? If they do, a flaw in that mechanism could result in them all being incorrect or misleading in the same way(s).

DeonPenny12• 6 years ago

I can't believe people are still screaming false results at this point every single random sampling has been the same or point to more infections. At this point based on everyone's method of random sampling that should merit the badge of random sampling, but people argue it on every post.

tigershark2• 6 years ago

The biggest problem looking at these tests is that they are completely on the opposite side compared to the mortality estimated using South Korea numbers. We know for a fact that South Koreans tracked pretty much every single person with covid given that their new cases are increasing by a single digit per day. We know that as of today they have 10708 cases and 240 deaths, with still 1967 active cases. This give us a lower bound for the mortality at 2.2%. I think this is the best way to estimate mortality and I think that a lot of studies are giving numbers for the infected that are just out of touch with reality. I remember an Oxford study that was saying that half the UK was infected at the beginning of April. Those numbers were simply insane. I still don’t have a perfect explanation why the mortality numbers from the antibody tests seem so low, but I think that the accuracy of these tests or the way they select the people to be tested may be involved. Do you see any flaw in using South Korea numbers to calculate the mortality?

FiberBundle2• 6 years ago

South Korea apparently has conducted 11500 tests/ 1m population. It's ridiculous to claim that they detected every covid case and to suggest that their cfr is a lower bound for the ifr.

seemslegit• 6 years ago

0.5% IFR is still very high, I wonder what the antibody detection threshold is - i.e. is it possible that a lot more people have been exposed but don't have detectable antibody levels ? Would it qualify as infection in the sense that they are not susceptible for covid19 in the near term ?

IkmoIkmo• 6 years ago

They're trying to measure infection rates by analysing people who are more likely to go outside, and more likely to be infected. There's no adjustment for this confounder at all that I can see. Quick example:

Suppose there's a 10% chance of getting infected every time someone goes outside. Suppose there's a million people of which half are type-A people who go outside once this month, and half are type-B people who go outside 10 times a month.

The type-A person will have a 10% infection rate. The type-B person will have a 65% chance to be infected after a month. The average infection rate is around 42%. Yet if you randomly select someone outside, odds are 10 to 1 that it'll be a type-B person, and you'll get a far higher average of 60%, which isn't indicative of the average person, only of the average person who goes outside.

Second, the article then compares the infection rate to the mortality rate. But the mortality rate does not include excess deaths. These are quite a bit higher for NYC, about 30% or so it seems than the official figures. But even this may be undercounting (or potentially, overcounting) the impact of the corona disease itself. Other deaths might be much lower (e.g. traffic, murder) or higher (e.g. untreated cancer).

Then there's the lag-effect. There's 150 thousand confirmed infected, 15 thousand dead. But the vast majority of confirmed cases are still active, not recovered. They're confirmed because tens of thousands were hospitalised. Of the incubated people, 80% do not come out alive. There's lots of people fighting for their lives right now. Once those cases resolve, many will not have made it. And that's just hospitalised people. Then there's lots of cases who just got infected, and will be developing symptoms in 1-2 weeks.

The way exponentials work is that lag is way more important. In the first weeks NY doubled every 2 days. That means if you have 10 thousand today infected today, in 10 days that's 320 thousand. That's when people start to get symptoms, and 10 days later people start dying from the symptoms. That means your infection count can go into the hundreds of thousands or even millions before seeing any death. But you can't conclude mortality figures from that, at all.

In short, the 21% and the 0.5% conclusions are extremely premature and should not be reported like this. It's good to report the measurements, in context, but you can't draw the conclusions about the population or disease from it.

DenisM• 6 years ago

This might be a bit blunt but I am not jesting - an article about disease testing that does not contain the words "false positive" and "false negative" in some form is literally not worth reading.

Even decent antibodies tests can have 10% false positive rates (bodysphere), and lots of those tests have dodgy provenance and 20% false positive is not out of the question.

Here's a better article, thou still not great (paywall): https://www.nytimes.com/2020/04/23/nyregion/coronavirus-anti...

The closest they come to discussing the errors is to acknowledge there might be some: State officials said the test had been calibrated to err on the side of producing false negatives — to miss some who may have antibodies — rather than false positives, which would suggest a person had coronavirus antibodies when they did not. Not very informative, I know.

A word of caution from the NYC health officials: https://www1.nyc.gov/assets/doh/downloads/pdf/han/alert/2020...

m3kw92• 6 years ago

For the people that thinks death rate is low is good news, it’s not when you know how contagious it is, you then need to look at numbers, not percentage to get a practical look at severity.

zyxzevn• 6 years ago

Good news. Herd-immunity is growing.

Also, this means that the death-rate is far lower than reported. And this is nice too. Maybe we can save people by starting the society again.

In other news, we see that hydroxychloroquine is actually working according to doctors. But there was a very bad study that claimed that it caused 2x as many deaths. It should have said instead that it was mainly used on patients that were close to death. Here is a good analysis of that study. https://www.youtube.com/watch?v=dLSYRqcg0wo&feature=youtu.be... Bad studies like this wide published one show that science is not immune to political agendas.

baconforce• 6 years ago

This video states that a randomized controlled study needs to be conducted, otherwise nobody can claim that hydroxychloroquine works or does not work.

mantap2• 6 years ago

The presence of antibodies is not sufficient for herd immunity. For herd immunity you need those antibodies to stick around.

hkai• 6 years ago

Aha! So perhaps we shouldn't have shut down the economy and financially ruined millions of people, not to mention the hundreds of millions of people on the brink of starvation in developing countries.

Perhaps we just like sharing images of coffins and feeling virtuous.

SerLava• 6 years ago

Even if the study is true, this doesn't follow.

You only get to limit your response if you have the capability to do actual testing... which we didn't and still largely don't.

known• 6 years ago

But they can infect others

tangent-man2• 6 years ago

To assume the infection fatality ratio(IFR)is 0.5% from this is retarded. We know that when covid-19 began to spread in South Korea at first it spread among a younger population who were ignoring or at least not following government advise so closely and taking chances the IFR was looking like about 0.7% to start with (In SK). We know this as SK kept excellent data / records to begin with. We also know that the Diamond Princess with a more generally aged population has a IFR of 13% +. We know this is a disease that adversely effects the elderly and infirm (in the developed world) If you are over 80 getting covid you might as well play Russian roulette with a Magnum .45 .These groups of people know there at risk, so if they have any sanity they are staying the hell at home. So people who are going into the Grocery store in NY city aren't representative of this population. This is why we are staying at home mostly to protect the old and infirm. That's not to say you want Covid-19 yourself either because there's about a 5% chance you will end up in the ICU (and an as yet undisclosed chance of death) even if your a member of the Hungarian Olympic Shot-Putting team. This does kill young tough people, it does happen but this is mostly killing the elderly and infirm. Why are people so fecking retarded? I can't take this anymore!! Stay the Sm3g at home! It's stopping the hospitals being overloaded.. It's buying us time to figure out new treatments / how to treat this better.

apexalpha• 6 years ago

Read an article that over half of Europe's Covid deaths might be from nursing homes...

tangent-man2• 6 years ago

Sounds plausible. Do you have a link to that article? I'm not trying to bate you, I'd genuinely like to read it.

Preliminary test results suggest 21% of NYC residents have Covid antibodies

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