This implies a shocking high R(effective) for that population. In 2 weeks we'll have super interesting data one way of the other on the CFR.
Of course if we are really lucky and the prison was infected with a naturally attenuated strain we should make use of it .
Your wording is too strong. Data is 50% asymptomatic at time of testing, paper models that that number dropped to 20%.
> from paper
on 19 February and 50.5% (320/634) on 20 February (Table). Soon after identification of the first infections, both symptomatic and asymptomatic cases were transported to designated medical facilities specialised in infectious diseases in Japan. However, these patients were treated as external (imported) cases, and a detailed description of their clinical progression is not publicly available.
We conducted statistical modelling to derive the delay-adjusted asymptomatic proportion of infections, along with the infections’ timeline. The estimated asymptomatic proportion was 17.9% (95% credible interval (CrI): 15.5–20.2%).
The eating together at communal tables, and any other close-quarters communal activities, seem far more relevant to increased R than the air conditioning system and the free airflow.
As such, while the small particles may not exists in sufficient quantities when it is just one infected, or a few infected inmates, but with each infected inmate the concentrations of those small particles will increase. Let's say they're normally 0.5% of the total particle exhalations: 10 inmates get sick through direct contact, and their combined exhalations bring the quantity of smaller, longer lived particles up to an equivalent of 5%. More get sick through contact, bringing it to 20%. At some point, you hit a critical mass where there is a sufficient concentration to infect people, and creates a downward spiral from there.
Prisons are much worse. Chow line with men almost heel to toe. Commissary line. Med line. Recycled air. Big crowds in small spaces.
> Prisons are much worse. Chow line with men almost
> heel to toe. Commissary line. Med line. Recycled
> air. Big crowds in small spaces.
The soap is expensive, they don't have it and masks are not allowed.
Popular restaurants, clubs, sporting events, concerts, movie theaters, stores on Black Friday, etc etc etc.
(Personally, I’ve been on 5 different cruises and they’ve each been among the best vacations of my life. But lol lots of people so they must be just like prisons amirite?)
Perhaps you do. But if you don’t, none of those things are similar to a week-long cruise at all, since you are there for hours and not days.
I don't live asses-to-elbows in line with people for a full week on a cruise ship either. I have a room to myself. What point are you trying to make, exactly?
<18 Under 18 6 0.0%
18 Ages 18-21 1,866 1.1%
22 Ages 22-25 8,366 4.9%
26 Ages 26-30 21,931 12.8%
31 Ages 31-35 28,182 16.4%
36 Ages 36-40 31,206 18.2%
41 Ages 41-45 26,545 15.5%
46 Ages 46-50 19,979 11.6%
51 Ages 51-55 13,749 8.0%
56 Ages 56-60 9,475 5.5%
61 Ages 61-65 5,467 3.2%
>65 Over 65 4,746 2.8%
Local demographics will vary wildly but it looks like the baseline would be 16% 65 and older, 13% in the range of 55-64. Since we're talking about prisons we should probably ignore the population under 18, so the normalized expected population over 65 is closer to 20%.
Anyway, those numbers are certainly much younger than the median age in the USA nationally, which is 39 years with over 65s being 15% of the population.
Now, what are the chances that some government institution acquired tons of crappy test kits, didn't validate them before use, and then proceeded to publish the results which just so happened to be exactly what they wanted them to be?
The data comes from 4 prisons. It is theoretically possible that all 4 of them happened to be in the same window after an initial infection, but it doesn't seem very likely.
I guess the only way to be sure is to do follow up tests every week or so, hopefully that will happen.
I've repeatedly linked to CDC study that estimates r0 in Wuhan before lockdown at between 3.8 and 8.7. Median 5.8.
Take away: Completely avoid being indoors with large groups of people.
The most common fatal case seems to be roughly: 1 week without symptoms, 1 week of mild symptoms, 1 week of severe symptoms, death. That's 3 weeks.
In rare (1/10000) cases, incubation time can reach 14 days, that's where the 14 days quarantine recommendation comes from. But the median is closer to 5 days.
Time to death can be much longer, the virus can cause all sorts of damage to the body, including secondary infections. And if the patient is strong enough to resist the primary infection but not enough to recover, it can take a long time.
What's the cite for that number? I'd be very suspicious of anything claiming a 5-significant-figure result in a disease that has only (heh) 3M known cases.
In fact there's significant supposition that the incubation time and asymptomatic contagious state can last much longer than originally guessed. This would go a long way to explaining the difficulty of detecting early outbreaks (basically nowhere in the world was able to contain before community spread was happening) and the anomalously low rate of new case decline post-peak. But there's no good science on this, and probably won't be in time for it to be useful.
You are totally right about that. I misinterpreted the following paper https://www.ncbi.nlm.nih.gov/pubmed/32150748
The actual number is more like 1/100. The 1/10000 number is the probability for someone who has a 1/100 chance of being infected to develop symptoms after 14 days.
Uhm... too late to fix my original post, sorry.
Also, the number I have seen was ~1% of cases where asymptotic for 14 days. https://hub.jhu.edu/2020/03/09/coronavirus-incubation-period...
Something else is driving those numbers, and it ain't the actual number of new infections. For me the obvious candidate is they hits some testing limit.
Although it's also most certainly true that we're vastly undercounting the cases in most (if not all) areas.
After you're hospitalized, yes you might or might not then have a month long battle for survival.
However, early estimates are going to be biased without the slowest fatalities. Further, that’s also population specific.
But seriously, what is this evidence you speak of?
The Princess cruise was a good indicator of CFR for a specific demographic range when they tested early, often, and had access to quality care. If the CFR of this prison will tell us anything, it will be a counterpoint to such information showing what happens when quality of care is greatly diminished.
> The results of the tests for IgG, IgA, and IgM levels are usually evaluated together. Abnormal test results typically indicate that there is something affecting the immune system and suggest the need for further testing. Immunoglobulins testing is not diagnostic but can be a strong indicator of a disease or condition. There are a number of conditions that are associated with increased and decreased immunoglobulins.
Even after the viral load in the upper respiratory tract drops off, there's still lots of virus around. You'll likely test positive -1/+2 weeks around onset of symptoms.
The expectation is that PCR negative is roughly correlated with fighting off the disease in the short term, and basically perfectly correlated in the long term.
Antibody tests only work after several days of infection, but some of them are not very specific to SARS-CoV2 and therefore have a high false positive rate.
So you really need use both tests, but you can't just OR the results together, because then a faulty antibody test will massively skew the results upward.
No, it only works if there is enough virus to be detected. If you are infected, you will have a high enough count to be detected. Each type of PCR test is highly selective. The point of them is that they can differentiate between many types of virus, depending on how its setup.
> Antibody tests only work after several days of infection
Yes. Depending on the type of test, and how its done. it can be up to a month before these tests are accurate.
This is the reason why China started to accept clinical diagnosis like chest scans, causing a sudden big spike in cases.
Yesterday the World Health Organization said: "There is currently no evidence that people who have recovered from COVID-19 and have antibodies are protected from a second infection."
As a fellow south east asian, I am deathly afraid of the under-reporting and testing in other ASEAN countries. Singapore. A 2017 statista study of migrant worker populations in South East Asia (https://www.statista.com/statistics/711513/asean-number-of-m...) shows that Malaysia and Thailand have much larger migrant worker populations than Singapore. Their living conditions are either on par or worse than the ones living in Singapore, yet there are apparently no Covid-19 clusters among migrant populations in other ASEAN countries. This is extremely alarming.
Can those two facts be combined into a theory that asymptomatic carriers are more likely to produce more mild and asymptomatic cases?
Don't know if it makes any sense (probably not), but it would certainly explain how in some closed environments there's a prevalence for mild cases, while in others there's a plenty of very sick people, regardless of the age.
Edited to add: Here's a preprint that is relevant to the "initial dose vs. immune system response" thought: <https://www.medrxiv.org/content/10.1101/2020.03.26.20044487v...
That assumes your immune system wouldn't kick in during the asymptomatic phase or a time close to exiting the latter. But your immune system would actually kick in as soon as it detects the infection, which would plausibly be much earlier. That would effectively buying you time to figure out which antibodies to produce before things become out of control.
"The procedure was most commonly carried out by inserting/rubbing powdered smallpox scabs or fluid from pustules into superficial scratches made in the skin. The patient would develop pustules identical to those caused by naturally occurring smallpox, usually producing a less severe disease than naturally acquired smallpox. "
Perhaps a more mild initial growth stage gives the immune system more time to respond.
Covid in your alveoli is very bad. Covid in your throat not so much.
The virus will grow exponentially, but so will the immune response, so starting conditions are important.
This is a basis for the old pre vaccine "variolation" strategy of getting immunity. Some radical thinkers argue for it as a Covid remedy.
I haven't heard anything in weeks studying anything like this, though, so I don't know where we ended up, if, indeed anybody knows anything at all.
I live in the Netherlands and I think you could say that we actually have it quite under control (relatively speaking of course). We never reached peak ICU capacity and the ICU occupancy has been steadily declining for more than two weeks now. Our schools for children between the ages of 4 and 12 are scheduled to partially open again on the 11th of may.
Only under pressure of the IC doctors on Sunday the 15th of march did the prime minister close all schools and restaurants. (A high school is like a festival every day)
The policy and advice of RIVM has been wrong and misleading from the end of February. For many of us it was already clear they lost control beginning of March.
There was one hero in the North of the Netherlands who went against RIVM and the Minister of health: https://eenvandaag.avrotros.nl/item/het-gelijk-van-microbiol....
This article in the Volkskrant describes how the RIVM was panicking beginning of March, but the prime minister wanted to present "good weather", and they also send their stock of masks to China beginning februari:
Even now they are not testing healthcare people with symptoms in elderly homes and also not providing any sort of masks. Claiming the available masks are not of sufficient quality, they prefer to send healthcare people to work without masks then to get high quality masks even if it is without the preferred certificate.
Last point. Under control is relative. The IC capacity reached a higher number then we ever anticipated, still more IC beds are occupied by corona patients then we had in total beginning of 2020. https://stichting-nice.nl/
For most of the hospitals in the Netherlands most operations and treatments are still postponed. For instance for many cancer patients the date of their treatment is still not sure: https://www.volkskrant.nl/nieuws-achtergrond/chemo-uitgestel...
Throughout Februari and March they had the following policy:
- Clearly stating and assuming that asypmtomatic people cannot or are extremely unlikely to transmit (had letters sent to schools and events I particpated in, was also on their website). True or not, there was no data to backup this up and an assumption like this has big consequences when false.
- When from risk area AND with symptoms as a policy they didn't test. In general the whole focus was to test as minimal as possible. Causing us to be completely caught off guard of the true scope untill March.
- Clearly trying to sell the idea that masks don't work for normal people, while at the same time trying to claim them for themselves
- As a policy not testing healthcare people, not even with symptoms. First random test of healthcare people with symptoms in the south was only done on the 8th of march, they were shocked by result (and for a long time untill march allowing people to work with symptoms ). https://www.rivm.nl/nieuws/steekproef
- As a policy "non-essentials" healthcare people get no protection unless evidence of covid and hardly get tested. 900 of 2100 healthcare/elderly houses now have the virus with 20 to 30 percent death rate.
- Failed attempt of centralised buying of masks and other protection wear
- Till the end of Februari claiming they had it under control
There is more things to point out but Ill leave it at this. The above assumptions and actions are a big part of what made the Dutch ministery fail to deal with the crisis properly and on time. Like many of the Western democracies. If they would have acted in Februari a full lockdown probably could have been prevented or shortened, lives would have been saved and many other treatments wouldn't have been cancelled or postponed.
The article i've linked to above talks about the doctor who did the opposite in the North, and was succesful with it, they even tried to force him to follow their policy.
To come back to your article. The short answer we don't have enough data (yet) to make such conclusions.
It seems reasonable that from the 9th of March the infection rate went down. This was the week all of Europe freaked out and many people started working from home, even if it wasnt official policy except for in the South of Holland (this idea was good, but too late). Certains schools already (partially) closed, partly because not enough teachers were showing up.
Whether or not school en restaurant closure lead to a lower infection rate is not clear from the data. The RIVM's analysis indeed suggests that it only had a small impact. The English analysis of the Dutch data in the same article does suggest a bigger impact. It's telling that the RIVM doesn't trust their own analysis enough to turn in into policy, you can watch the briefing of Dissel of last week, they only very slowly open the elementary schools in a few weeks from and don't open restaurants and high schools till the end of may.
> Netherlands National Institute for Public Health and the Environment
> The Netherlands National Institute for Public Health and the Environment, is a Dutch research institute that is an independent agency of the Dutch Ministry of Health, Welfare and Sport. RIVM performs tasks to promote public health and a safe living environment by conducting research and collecting knowledge worldwide.
If anyone wants to read more about this I can't recommend highly enough the book Spillover by David Quammen, which was published in 2012, and covers zoonotic (animal-to-human transmission) viruses, including SARS. Reading the section on SARS made the hairs on the back of my neck stand up. It's uncannily similar to what's happening with Covid-19, and explains a lot of the background involved in these kinds of viruses.
The larger the undetected group is, the lower their relative infectiousness has to be in order to fit the observations. The best fit I believe was 1/25 detected and 11% infectiousness of the undetected group.
Sadly, I have no idea where I read this. But... I know I did! Recently! Maybe NYT?
That is basic infections 101. When you are exposed to any dangerous virus a race starts between the virus and your immune system. If the virus starts out only infecting a handful of cells, your immune system has a head start in developing antibodies before symptomatic infection sets in. (This is also a basic principle behind many vaccines.) But if you are hit will a massive viral load that instantly infects every cell in your lungs, the immune system is fighting uphill from day one. A massive initial viral exposure can also trigger an excessive immune response, for instance dangerously high fever. Such an immune response can be as deadly as the virus. Much covid research is going into not defeating the virus directly but regulating/slowing the immune response to the patient survives their own immune response.
This principal explains why healthcare workers are suffering so. They are exposed to constant massive doses of virus, possibly from multiple patients carrying slight different versions of the virus. So they get sicker than people who are exposed in the general community.
Also, the virus is replicating exponentially only if it can reach many uninfected cells. It takes ~10 hours for an infected cell to start producing virus. Not sure whether non-specific immune system can somehow "contain" virus, would be great to learn about that.
A low initial dose doesn't seem to affect the course of the infection much, though. For a sufficiently low dose either none of the viruses find an ACE2 receptor or your innate immune system wipes up the virus without you noticing (as it does for you with other viruses every day).
There's some evidence that particularly high doses can cause particularly bad prognoses. We have pretty good evidence that this is the case with measles. There's very anecdotal evidence suggesting that maybe this is the case with SARS-CoV-2. But it looks like low doses lead to a chance of no infection, not a chance of an asymptomatic one.
The normal course of the automatic immune system wiping out an invading pathogen without you noticing is that it happens immediately without you noticing and you never get a chance to infect anyone. But if that doesn't happen for COVID-19 or influenza or most things there'll be a time period after infection but before you notice anything where you're infectious. For COVID-19 this period is particularly infectious compared to the flu or SARS-1 or most things. It might be that flu and other coronaviruses tend to people who are infected enough to transmit the virus but never go on to develop symptoms. I don't know in that case.
Until very recently they still said
"The risk of catching COVID-19 from someone with no symptoms at all is very low."
They now say
"Some reports have indicated that people with no symptoms can transmit the virus. It is not yet known how often it happens. WHO is assessing ongoing research on the topic and will continue to share updated findings."
do you carry it forever? does it attack eventually?
what happens if you are an asymptomatic carrier and get a vax?
That's still not 38 years; it's not especially important a point - she infected others over at least 2 extended periods amounting to mor than a couple of decades in total.
It's interesting to me, I thought nih.gov was a scientific publication but at least one part of that document appears to be opinion asserted as fact (~"she never intended to abide by the conditions of her release").
I never stated that she infected others for 38 years. Being an asymptomatic carrier does not require continually infecting others, only that the carrier maintains the infection without showing symptoms.  Additionally, the NIH article isn't complete in listing likely infections, as evidenced by comparing it to the Wikipedia article. Nor does is state that she continued to infect others until her paralysis in 1932.
As for the 38 years, the Wikipedia article notes 1900 as the first known, likely infection of a family she worked for. Then, from the NIH article:
> A post mortem revealed that she shed Salmonella typhi bacteria from her gallstones ...
Her death (and, presumably, post mortem) was in 1938. "Bacterial shedding"  implies infection and, thus, being a carrier in 1938, though asymptomatic. I arrived at 38 years by considering her likely a carrier from 1900 to 1938.
Thanks for sharing.
I found the peek in all-case mortality also very interesting, because that way counting is much more unambiguous: dead is dead.
They showed a clear diversion from the "average" in recent weeks, but... they did not show the stdev for the averages. Finally I found a chart that shows that "outliers" are not uncommon.
There is a very noticeable spike in the worst hit countries: Italy, Spain, France, Belgium, Netherlands and the UK.
The cumulative excess deaths for all Europe in the last two months matches the COVID-19 reported deaths (around 100000).
This article claims that most Covid-19 hotspots have significantly more excess deaths than reported covid deaths. Suggesting that there is a lot of underreporting. NYC being a notable exception. I think several countries count only corona deaths in hospitals, but systematically miss all deaths in care facilities. https://www.spiegel.de/wissenschaft/corona-todesfaelle-wie-v... (charts should be readable despite any language barrier)
(I don't defend either view. As the old joke goes, don't trust any statistics you haven't manipulated yourself :) Statistics and causality have always been difficult, even more so in exceptional time with imperfect short-term data only.)
Another coincidence is that the country that is most suspected of under-reporting, Germany, is also the least represented in EuroMOMO. There is data for only 2 regions.
Italy, Spain and France, the most significant contributors both in COVID-19 related deaths and excess mortality in general, all count deaths in care facilities now. I don't know about the UK though. Deaths at home are probably not counted, but according to the authorities, they are a minority: COVID-19 does not happen suddenly and people normally have time to go to the hospital. Still significant though.
My gut feeling is that there are actually ~50% more deaths than reported. But we'll have to wait for at least a few months to get proper statistics.
New York has been criticized for retroactively adding older cases. The Johns Hopkins data just tacks it on to the end of their time series, creating a weird spike and screwing up what the data represents:
Where's the noticeable spike for Ireland? Where's the spike for Portugal? Where's the spike for Luxembourg? Where's the data for the rest of Germany outside of Hesse and Berlin? Where's the spike for Austria? (And this is not a criticism of them, but they only track Western Europe by the looks of things.)
Don't know where Euromomo is getting its data from but I suggest to you that it's incomplete.
This NYT article (other publications like The Economist have arrived at similar numbers) show that the cumulative excess deaths for France, Netherlands, Switzerland, Spain, and England & Wales sometimes far exceeds reported Covid-19 deaths.
Of the countries you mention only Belgium is actually reporting accurately. (As is Sweden btw, a country you do not mention.) Note that both are smallish countries.
As of 14 hours ago Chris Giles (FT economics editor) tweeted "A cautious estimate of the total number of UK excess deaths linked to coronavirus stands today at 42,700" (He updates this most days.) Worldometer currently has the UK on 20,319 deaths. Quite a difference.
In fact, the numbers show that in Europe actual deaths are between 1.4 [Swiss] and 2.1 [British] times higher than the reported numbers for countries that are under-reporting.
Btw, you say that there are 100,000 deaths? EU 27 has 96,533 deaths as of this moment. EU+UK has 116,852 deaths as of this moment. And Europe in its entirety has 122,568. (Am tracking these figures using a spreadsheet.)
Let's say that the adjustment we have to make is between 1.4 and 2.1 and let's ignore population size and pick 1.75 and then lower that to take into account that some countries are accurately reporting and let's err on the conservative side so let's choose 1.66… repeating as our adjustment rate, agreed? This gives us an estimated excess # of deaths for Europe of 204,280. Twice the figure you've given.
(Europe is generally taken to extend from the Atlantic states of Ireland, Portugal, and Iceland in the West to the Ural and Caucasus Mountains in the east, from Scandinavia in the north to Italy and Greece in the south.)
Admissions at hospitals have collapsed: in the UK they halved. Admissions due to respiratory illnesses however didn't really go up, not surprising when you consider the small absolute numbers. There is now a massive backlog of operations and diagnostics for cancer that health systems will struggle to clear in time.
There's a story with some analysis of that problem here:
In the past the recommendations of epidemiologists have ended up killing a lot more than they saved, with the 2001 foot and mouth epidemic in the UK being a classic example. It's likely it will be true again this time.
It is interesting though that the median undercount is converging to ~10-20x. Perhaps the protocols across regions are similar enough that the confirmed case counts are somewhat comparable.
Unrealistically low death stats coming from Turkey compared to cases easily refute that argument.
Dead is dead, unless the state finds a way to claim that it was not a COVID19 dead.
This is what “dead is dead” mean. One can argue what should count as a COVID19 case, and how exactly we are counting. There is a lot less argument over who is dead and who is not.
It seems I actually missed the mention of "all-cause" while reading the comment.
It's just a matter of demanding tests to declare as a COVID death and do not providing enough tests.
Brazil, for example, has an artificially low count of cases due to the lack of tests and a similarly low number of deaths. However, cases of death by "pneumonia", generic types of SARS and "unexplained respiratory diseases" skyrocketed: https://oglobo.globo.com/sociedade/coronavirus/alem-da-covid...
The 1.66%, otoh, seems reasonably in line or at least compatible with what's been observed in Korea and elsewhere.
Given age is going to skew things a good deal, it seems like a picture is emerging but not that new a picture. An IFR of even 1% is pretty bad, especially given these statistics show how infectious this virus is.
Most of those tests were done on April 4th and 5th which was 3 weeks after Austria started relatively strict lockdown measures, which also impacts that number, as this will result in the test to find an even lower number of positive people.
To be clear: it would be the most dangerous general epidemic disease since the advent of vaccination, and by a significant amount. You need to go back to measles and polio to find general population outbreaks that were more lethal.
Not every death is the same - a 80 year old with weak immune system could have lived 5 years longer without corona, but a healthy 20 year-old dying from cytokine storm caused by influenza has lost potentially 60 years of healthy life - the loss is much worse.
Seeing those numbers makes me more supportive of the isolation measures.
In a triage situation, where you have to decide between different people dying, such choices are unavoidable or necessary. But I want highlight that you are talking about this stuff to say that it's OK to plan for the death of "a 80 year old with weak immune system could have lived 5 years longer" versus no death at all. And that's not OK.
One choice is providing some opportunity for further life beyond what's expected. That's generally considered something society likes but isn't obligated to provide. Society doesn't obligate it's member to spend money developing some miracle-extend that gives someone five more years.
The other choice is taking life that would normally be expected. That is something that society very much frowns on. If you could protect someone and you don't do it 'cause it would cost you money, you may wind-up in jail for murder.
Very quantitatively oriented people seem to have a hard time grasping why there's a difference here. But I think it's very rational in an evolutionary game-theoretic compact kind of way. Everyone is a member of society and values everyone else's life highly, more highly than immediate material things though maybe not more highly than other people's lives. This gives member of society basic security - you are thinking my insulin might worth just stealing and selling on the open market, me murdering you first might be my best strategy. You can see where things break down? The "social contract" is kind of the way around this.
And not doing anything (pretend it's just the flu) will result in 50M dead world wide. Everyone worried about a new depression should realize one is going to happen no matter what we do now. The only thing we can do is act in a humane fashion.
Where do you get your 50M worldwide figure? When a new flu appears, Neil Ferguson claims his 3K lies of undocumented C code forecast 200M will die. These numbers are all speculation and worse predictors than throwing darts at a board behind your back.
If you look worldwide, there are 7.8B people. If herd immunity takes 60% of the population becoming infected, that's 4.6B infections. With an IFR of 1%, that's 46.8M deaths. 460M hospitalizations (where possible).
Even say the IFR is overstated as some like. Say it's a magnitude less, comparable to the flu at .1% Now you are down to 4.7M deaths, but still the 460M hospitalizations. Still one of the most serious crises in the last 100 years.
OK, so how many "influenza death equivalents" are we looking at? What's your metric for how bad this is? I mean, I think that's a little ghoulish, obviously, but if people really want to make this argument I'd really like to see the kinds of well-founded numbers that the experts are producing. Medical ethics is hardly a new field, after all. You'd think someone would have pulled some analysis off the shelf.
Instead, the people pushing "these people would have died anyway" seem to be almost exclusively political actors (or their proxies on social media sites like this one) with a goal of either defending the inaction of the current administration or pushing a policy goal that necessarily sets the virus loose on the public.
But if you really want to make a numerate case for not trying to save the old and sick, I'd genuinely and carefully read it.
So you would need to estimate the number of years lost vs the economic damage. This is impossible to get right on both sides but at least it gives you a framework.
Basically everyone who dies from this has a preexisting condition, but basically everyone in the US will develop at least one of the big three (hypertension, diabetes, or obesity) at some point.
Kinda sucks if you have any of those conditions right now though.
You chose to eat X and not exercise for years/decades. A middle class American has enough education and purchasing power to know and behave accordingly.
Does it suck? Yes, but i find it incredibly unfair and hypocritical towards the rest of the world by ruining their lives based on the extremely old and or fat/unhealthy population.
And your comment comes across as extremely crass and insensitive.
The elderly and immunocompromised obviously die more to almost every illness. But the effect is really pronounced with covid. And most other viral infections tend to kill children at higher rates too, and covid very notably does not. It's definitely an interesting aspect of the disease, though it's produce a kind of horrifying calculus among a lot of the right wing in the US.
What do you mean? There were vaccines in 1918.
"In order to test the detection sensitivity and specificity of the COVID-19 IgG-IgM combined antibody test, blood samples were collected from COVID-19 patients from multiple hospitals and Chinese CDC laboratories. The tests were done separately at each site. A total of 525 cases were tested: 397 (positive) clinically confirmed (including PCR test) SARS-CoV-2-infected patients and 128 non- SARS-CoV-2-infected patients (128 negative). The testing results of vein blood without viral inactivation were summarized in the Table 1. Of the 397 blood samples from SARS-CoV-2-infected patients, 352 tested positive, resulting in a sensitivity of 88.66%. Twelve of the blood samples from the 128 non-SARS-CoV-2 infection patients tested positive, generating a specificity of 90.63%."
That gives us 62% false positive ratio according to (where a study finds the prevalence to be 6% of subjects using the test):
In some cases we have research being carried out with such low positive results that they can entirely be accounted for by the low specificity. So for example if you took samples from 100 people, based on 90% specificity, even if everyone had never had corona, 10 could be found positive.
Credit to this post:
However it should be noted the article in question for this submission does not mention the type of test used.
Edit: I'm looking at the reddit post but I have a lot of reservations with the "prevalence 0.06", unless we'll use the test to test absolutely everybody and not only people who are suspect. Has that calculator been validated as well?
If the test was 12 false positives in 128 negatives, how come they can claim the false positive rate is 60%?
"Our data from this week and last tell a very similar story. In both weeks, 6% of participants tested positive for COVID-19 antibodies, which equates to 165,000 Miami-Dade County residents"
That is what the commentator is referring to in the linked post.
So if you plug their own figures into the calculator:
and a Prevalence of .06 based on the study, you get the 62% false positive rate.
As the prevalence increases, as with the NYC study which found the positive rate to be 21% (prevalence), the false positive rate decreases, down to 28% of the NYC study.
The Antibody test is a serology test which measures the amount of antibodies or proteins present in the blood when the body is responding to a specific infection. This test hasn’t been reviewed by the FDA. Negative results don’t rule out SARS-CoV-2 infection, particularly in those who have been in contact with the virus. Follow-up testing with a molecular diagnostic lab should be considered to rule out infection in these individuals. Results from antibody testing shouldn’t be used as the sole basis to diagnose or exclude SARS-CoV-2 infection. Positive results may be due to past or present infection with non-SARS-CoV-2 coronavirus strains, such as coronavirus HKU1, NL63, OC43, or 229E.
I don't know what tests the other studies used.
It may be helpful to you.
Thank you for tracking these metrics.
Specifically, the Premier Biotech/Hangzhou Biotest Biotech test was validated by a Chinese provincial CDC and found 4 false positives out of 150. 
It was also validated by the COVID-19 Testing project and found 3 false positives out of 108. 
The Biomedomics test used in the Miami Dade study was also validated by the COVID-19 Testing Project and found 14 false positives out of 107. 
Hence I would recommend taking the results of the California and Florida studies with a huge grain of salt as the prevalence rates they found were within the false positive rates of the tests used.
Reporting on 96% without symptoms is misleading without mentioning this: It gives the impression that the # of coronavirus infections could be up to 24x higher than the known positives cases. But symptoms can take 2-14 days to develop, meaning it is entirely too soon to tell if these are all asymptomatic cases, or merely pre-symptomatic.
There was a nursing home in Massachusetts which had 51 out of 98 residents testing positive but asymptomatic in early April. While this sounded encouraging in the sense no one was critically ill because of coronavirus, a few weeks later 19 had died and about 30 more had tested positive.
Let’s wait a month until there is a clearer picture about the impact of the virus on a particular population of people.
"Asymptomatic" is kind of a sliding scale. Are you sick? No. Do you have a stuffy nose? Kinda.
When you add in all the other things that count as comorbidities here, you're probably looking at like 75%.
i'm so tired of literally every other HN comment being like this. there is truly nothing more low effort / "i am very smart" than the HN-classic "do you have a source for that? where's the peer-reviewed study?". it adds absolutely nothing to the discussion, and yet i see all sorts of materially less obnoxious things be downvoted to oblivion.
 "citation needed"
They're all slightly different, but yes they're looking for antibodies against specific parts of SARS-CoV-2, like the N protein . I think the N protein ones are most common. I just did a BLASTp against SARS-CoV's N protein and there's maybe ~90% homology? So I would hope they're using a site that's different between the two. Or, there's an assumption that most people have not been previously exposed to SARS-CoV or others with similar N proteins.
> Also aren't antibodies effectively developed in a sort of random process?
Yeah, but there's only so many prominent features to a virus that you can make antibodies against.
Perhaps humans tend to have enough random antibody generation that they are likely to start mass producing most of the protein shapes that are able to bind to the virus? And as another commenter pointed out, there are not that many options to bind to.
I wish we had leaders that had the chutzpah to say things like, "look the science is inconclusive, so we won't arrest you, but please do the right thing and wear masks". But we don't. And also we have people spouting completely non-evidence based assertions like "if you don't force people to wear masks, then they won't". Which of course fuels assholes to flaunt not wearing masks, because now it's not about doing the right thing, it's about freedom.
If instead we had done random sampling we could have been very accurately projecting the number of active cases pretty easily, but apparently we’ve mostly decided not to do that until now with the antibody studies.
Furthermore, people in environments with a lot of virus (i.e., cruise ships, hospitals, or just northern italian towns where the virus has run amok, tend to get sick and die at much higher rate than those antibody tests would suggest.
There may be a mechanism for multiple infection which makes multiple exposure more dangerous even if you have antibodies.
Do you have a source for that?
I think that will be the primary message that people will get from that study.
Simple question: Why?
For most coronaviruses, antibodies reflect only a temporary immunity, that is usual gone in 6-24 months, due to the nature of these viruses.
All an antibody survey shows is that antibodies can be created, not that they are effective long term. Showing a longer term immunity takes statistical analysis, usually after that temporary window has ended.
In fact, antibody surveys may not even show an effective temporary immunity, if the wrong kinds of antibodies are being screened for.
Knowing this, why was the antibody surveys supposed to be some golden bullet? The advice from the medical community was "this is being actively studied, wait and see."
The surveys provide the medical community with important data, but they don't really provide us with policy making data, and they certainly don't predict the future for the general population when exposed to the virus.
A good place to keep an eye on for the short term would be Sweden. Despite the lack of lockdown their disease penetrance is still on par with the UK.
10 fold over what? A problem since the beginning is that many people are confusing CFR and IFR. Worse is when people compare the IFR of COVID-19 to the CFR of the flu. Regardless, the IFR for COVID-19 has been thought to be .5-1% since the beginning. If we assume the NY antibody study is mostly correct (even with the sampling errors), I believe it puts the IFR in the .5-1% range . If that IFR holds it still means 1.6-3.3M deaths in the US assuming the healthcare does not get overwhelmed.
deaths/(cases x 10 fold) x 100 == IFR
21908/(288313 x 10) x 100 == ~.75%
Data pulled from https://www.worldometers.info/coronavirus/country/us/ on 4/26/2020 @ 8am EST.
You cannot assume that 100% of people will be infected. Looking at case studies like USS Roosevelt (840 of 5000) and Diamond Princess (712 of 3,711) as the worst case prevalence because they are much higher-R environments.
So basically your IFR based fatality numbers could be divided by roughly 5.
There is some news out that is putting the IFR closer to .3% on the low end. That is great news if it holds up. The problem is that the numbers out of NY, if flawed would bring the IFR lower than reality, and they are ~.75% IFR.
Which is why when these studies happen, the public is told to wait for it to be assessed, rather than pretending all of us are remotely qualified to judge the content and draw conclusions from it about what actual risks the general population might be facing.
When the studies in question have a high rate of false positives, that is absolutely not the case. It may simply be a statistical anomaly, from taking the incorrect confidence interval.
Currently, from the studies taken, it looks like we have high rates of both false negatives, and false positives. Which means that the testing does not give you an accurate picture of whether a population group has previous infections or not.
With that said, the extrapolated numbers for NY do fall in line with the original IFR of .5-1% The downside is that if that is the IFR then the US is looking at 1.6-3.3M deaths assuming hospital systems can keep up as the infection spreads.
Edit. It's also important to talk about infection counts (what antibody tests are looking for) and case counts (people who show symptoms and end up seeking medical care). In the past when people were saying it's just the flu they were comparing COVID-19 IFR to the flus CFR.
But the 21% study is seriously flawed because it didn't do a random sampling of the population. We need that at a minimum to know with any certainty what the actual exposure rate is. The figures that are coming back from studies using random samples in other places have been much lower.
This would be a much better list to sample randomly from than "go to a grocery store and test everyone who walks in".
I should point out on /r/nyc, some local redditors saw the testing going on all week in the same location and posted about it, informing others. I suspect this led people who wanted a free test to actively seek them out, especially because it's so hard to get tested otherwise. I'm pretty sure I had it over a month ago and I still haven't gotten tested, so if I'd seen those posts in time I'd have headed over there to get tested myself. Point is, the sample is even further biased because word spread around and some number of people getting tested there were actively seeking it out for reasons.
What huge legal issues? This is all the government. Of course it has lists of all of its citizens, and can and does use said lists.
There are some tests trying to sample everyone in a geographic area (SF Mission census block) but the data isn't out yet because they're conducting tests as we speak.
* It will also show an undercount of at least an order of magnitude.
* Commenters will still pop up to explain why the results can't be trusted and which further studies are absolutely required before we believe them.
Also elsewhere in this thread it's mentioned that the Florida and Santa Clara results could be entirely explained by high type II error in the test. The Florida test appeared to have a false positive rate of ~15% when independently validated, which is basically the infection rate they found. In other words, this is a specific form of base rate fallacy where the test accuracy is really low.
It seems pretty likely that the data will come out showing at least 10%, so it's literally impossible for it to undercount by an order of magnitude.
How do you think a random sample of inhabitants would be off by a whole order of magnitude, anyway? Can you explain the mechanism whereby that might happen? The only thing that comes to mind would be using a worthless test with a 90+% false negative rate.
So far as of Saturday at 6:49pm EST 16,919 have officially died in NYC.
I think the anti-body test in this case is fairly close and the death rate is probably 1% more or less depending on the demographic distribution. Obviously there are a number of people in NYC who will die over the next month even if all new infections where halted right now.
The serology tests are just wrong when only a small number of people in the sample were infected, which is what we’ve seen from the stuff in CA so far.
Another data point, ~12k healthy foreign workers in Singapore have tested positive. The city-state has only 12 deaths total (all elderly, not the foreign workers). In Singapore the foreign workers may have already been asymptomatic for weeks.
Based on NYC data, LA city data, Stanford's Santa Clara data, Singapore, Danish blood donor data, a picture is emerging that the virus is not particularly dangerous to healthy people.
- Over half of state prisoners and up to 90% of jail detainees suffer from drug dependence.
- Hepatitis C is nine to 10 times more prevalent in correctional facilities than in communities.
- Chronic health conditions, such as asthma and hypertension, and mental health disorders also affect prisoner populations at rates that far exceed their prevalence in the general population.
- About 40% of all inmates are estimated to have at least one chronic health condition. With a few exceptions, nearly all chronic health conditions are more prevalent among inmates than in the general population. 
With that said, the average age is much younger than the general population . Age is by far the biggest factor in outcomes, followed by co-morbidities.
2. Over 5000 (roughly 40%) have been hospitalized https://www.scmp.com/week-asia/health-environment/article/30...
Data from antibody tests can so far be summarized as garbage:
I guess the TL;DR of all of this is, this picture you're talking about is a fallacy premised on bad data
But as of 25-04-2020 at least 4 inmates have died to Corona virus according to https://eu.marionstar.com/story/news/local/2020/04/24/corona.... There are 2,564 inmates (https://drc.ohio.gov/mci).
If coronavirus goes around again, that could raise the death rate
It would be pretty novel for the human immune system to clear out the disease on it's own, then a few days later forget how to do that, and become re-infected. SARS-COV-1 saw immunity conferred for 2-3 years.  I suspect something similar is likely here, probably for a shorter duration due to the more limited severity, but long enough to get us to a vaccine.
Generally for as long as you show antibody response you won't be re-infected because that's what antibodies do. The link I provided to the study I referenced was specifically for the purpose of, and I quote: "to assess SARS patients’ risk for future reinfection."
"To be clear, most experts do think an initial infection from the coronavirus, called SARS-CoV-2, will grant people immunity to the virus for some amount of time. That is generally the case with acute infections from other viruses, including other coronaviruses." 
If you think this time is different the burden of proof is on you to provide studies and not provide unsupported, unsubstantiated conjecture.
In science, it's incumbent on those making the claim to provide studies and proof. That means you...
And to say that this is unsupported, unsubstantiated is ridiculous, and you know it. It's straight from the WHO's mouth.
Nothing I said contradicts the WHO.
> Don't you think that if this was a foregone conclusion, we'd be able to demonstrate that?
I'm sorry, do we need to re-prove how the immune system works? Why re-demonstrate the utterly obvious?
> Isn't it odd, that with people having been infected and recovered months ago, that no one is saying how long the antibodies persist?
No, because it hasn't been long enough. I'm confident that research is under way.
But an immune response from an actual virus should last for at least a few years. There are situations where you can get reinfected later in life if you're not exposed or given booster shots (likes Shingles).
Is there evidences that our adaptive immune system only generates short lived antibodies, and for what families of viruses?
It's like saying "I find it very strange no scientists came out on record this week with a study showing water remains wet -- does it?! How can we tell if we don't check again."
Lack of proof of an affirmative is not proof of a negative, and especially not when plenty of other evidence points in the direction of the affirmative (again, not conclusively).
I agree. In fact, its highly unlikely, as with coronaviridae we've seen that the milder the disease the less likely you are to obtain long-term immunity. Even SARS, a much, much more serious disease, gives you 2-3 years as per my reference.
However, that's not what GP was arguing. GP argued broadly that "people who test for antibodies [may not be] immune to future infections." That's extremely unlikely. The question is how many people, and for how long, and then how do we utilize that information. Broadly speaking a positive test for antibodies means you're pretty likely immune at the time the test is taken. Of course the question is how that antibody response changes over time.
I was pretty clear about that: "Generally for as long as you show antibody response you won't be re-infected because that's what antibodies do."
The WHO is saying don't issue one-off certificates of immunity for life on the basis of testing positive for antibodies at one point in time before we know more. I agree.
I suspect a round of infection is likely to tide us over to a broad vaccination program, but we need a study.
""There is currently no evidence that people who have recovered from COVID-19 and have antibodies are protected from a second infection.""
They were prompted to issue this because some people were touting this idea of immunity being granted perpetually and allowing people to safely return to work.
"Broadly speaking, a positive test for antibodies means you're pretty likely immune at the time the test is taken."
That's in complete contradiction to what the WHO is saying. Read carefully: There is no evidence.
You're using circular arguments to provide bad information. Something you've consistently been doing.
"...but we need a study."
Why? You've said it's unlikely to be different than other viruses. Of course we need a study, because we don't know.
There is currently no evidence of X does not mean X is not true. It just means there's no evidence of X being directly true yet. Nothing I said contradicts the WHO.
What I said was that we can reasonably infer from similar coronaviruses (including both more and less severe ones that are up to 90% genetically identical) that immunity is conferred. Also from other viruses. We shouldn't base our global health policy decisions on that until we have conclusive evidence but there's no reason for you to continue with the messaging when all evidence points to immunity being conferred for some duration of time.
Specifically what I said was that we do not have enough evidence to issue prophylaxis certificates, but that chances are good immunity is conferred based on studies of very similar diseases. I also stand by the fact it would be hugely surprising (totally novel) that any of those testing positive right now are actually re-infections due to the limited timescale involved.
Seeing smoke doesn't mean there's fire, but it means there's a pretty good chance of fire. Yeesh.
You have not brought any evidence to the table. If there is a study that says SARS-COV-2, unlike the majority of (all?) viruses and all coronaviruses that results in immune response sufficient to clear the disease that then immediately dissipates, I'll certainly accept the premise.
Until then, a preponderance of evidence points (or suggests without proving conclusively) otherwise.
> That's crystal clear, but it doesn't align with your opinion that this is just like the flu in seriousness.
That is not my opinion. My opinion is that it's milder than the flu for young people (it is) , and much worse than the flu for older folks (it is) -- no citation needed, I assume. To suggest otherwise would be to ignore the evidence you claim to hold sacrosanct.
powerful argument there, not.
With SARS1 there was continuing damage post 6 months.
SARS-COV-1 had an IFR (not CFR) of 14-15%. Broken out, it's less than 1% for people younger than 25, 6% for those aged 25 to 44, 15% for those aged 45 to 64, and more than 50% for people 65 or older, officials said. 
On the other hand SARS-COV-2 has an IFR of somewhere in the lower quartile of the range 0.1% to 1%, trending to around 0.3%.
Not to mention, I argued that lung function would recover, to which you said "strong argument, not [the much worse disease saw lung function recover in 6 months]" which implies you were actually supporting my argument not refuting it.
The coronaviridae family is huge, and fatality varies from ~0% in the 15% of common colds they cause to 0.1-1% for COVID to 15% for SARS-COV-1 to 50% for MERS. I can't stress this enough. SARS-COV-1 and MERS are not SARS-COV-2, they are much worse diseases.
For a patient, a high false negative rate is usually worse. For an insurer, a high false positive rate is usually worse. The perspective matters.
At an individual level, false negative seems more dangerous. But at a macro level, a high false positive rate could lead to taking dramatically policy decisions
I agree with the caveat that false negative rate is much more relevant for society when a disease is very contagious. Take measles, with an R0 in the teens. A high false negative rate can cause explosive growth in the numbers of people catching the disease, which I think is what makes it relevant to the COVID-19 scenario
Implementation examples: South Dakota and Sweden.
It seems clear that the infection rate has been severely under counted, meaning mortality rates are artificially high. Even better (from the standpoint of restarting) that "flu-like" mortality rate is concentrated in people over 60 years old.
What that all means together is the economy can easily restart, with the most vulnerable (old and sick) taking extra precautions.
This entire thing has been a fascinating exercise in how poorly central planning can work given bad information. The cure has been vastly more damaging than the disease.
Besides, the article you pointed down in a reply is about a different kind of test.
I do disagree that a false negative rate is not important in the context of a disease where asymptotic cases may still be contagious, however.