Hospitalizations will determine how truly close we are to what is ‘effective heard immunity’, Since we have no easy way of measuring at scale t-cell body immunity.
You can still get the disease, but not badly enough that you need to be hospitalized, especially if you are younger (old people got the vaccine first). But I think it's probably still an OK indicator of herd immunity.
The "younger people are safe" idea is being challenged by these new variants. Additionally, discovering you're in an at-risk group by getting COVID is a pretty terrible outcome.
A more accurate way to phrase this is that young non-overweight people are at far less risk than young obese people. It's not true that young healthy people are at no risk.
Among 780969 adults discharged between April 1, 2020, and June 30, 2020, 63103 (8.1%) had the ICD-10 code for COVID-19, of whom 3222 (5%) were nonpregnant young adults (age 18-34 years) admitted to 419 US hospitals. The mean (SD) age of this population was 28.3 (4.4) years; 1849 (57.6%) were men and 1838 (57.0%) were Black or Hispanic. Overall, 1187 (36.8%) had obesity, 789 (24.5%) morbid obesity, 588 (18.2%) diabetes, and 519 (16.1%) hypertension (Table).
During hospitalization, 684 patients (21%) required intensive care, 331 (10%) required mechanical ventilation, and 88 (2.7%) died. Vasopressors or inotropes were used for 217 patients (7%), central venous catheters for 283 (9%), and arterial catheters for 192 (6%). The median length of stay was 4 days (interquartile range, 2-7 days). Among those who survived hospitalization, 99 (3%) were discharged to a postacute care facility.
Morbid obesity (adjusted odds ratio [OR], 2.30; 95% CI, 1.77-2.98; vs no obesity; P < .001) and hypertension (adjusted OR, 2.36; 95% CI, 1.79-3.12; P < .001) were common and in addition to male sex (adjusted OR, 1.53; 95% CI, 1.20-1.95; P = .001) were associated with greater risk of death or mechanical ventilation. Odds of death or mechanical ventilation did not vary significantly with race and ethnicity. Morbid obesity was present in 140 patients (41%) who died or required ventilation.
> of whom 3222 (5%) were nonpregnant young adults (age 18-34 years) admitted to 419 US hospitals.
So, 3222 / 780969 = 0.4% of the examined population had admission to a hospital with "Covid" on their forms. Of these, 343 died (0.04% of examined population; Table 1).
Obesity, hypertension and diabetes were strongly correlated with death in this population.
That's not "no risk", but it's consistent with the OP's comment: the risk for young people is quite low, and is concentrated amongst the obese (and diseases related to obesity).
You're right, it doesn't. The study posted by the parent is not trying to make claims about absolute risk to young people -- it's focused on the conditional risk, given that a young person is hospitalized in the first place.
"Conditional on being hospitalized for any reason" gives you an exceptionally useless number. There are many conditions that would give you a usable risk number, but not that one.
Just for the obvious extreme example, if I say 0.01% of total hospitalizations are young people with ebola, that doesn't let you conclude anything about whether catching ebola is "quite low risk" for that group.
> "Conditional on being hospitalized for any reason" gives you an exceptionally useless number.
It tells you what to expect if you're a doctor working with hospitalized patients, or if you run a hospital.
This is why they did the study.
> if I say 0.01% of total hospitalizations are young people with ebola, that doesn't let you conclude anything about whether catching ebola is "quite low risk" for that group.
1) that's not what this study calculated. You still don't understand it.
The equivalent study would be "of young people hospitalized with ebola, what percentage of them die?" (and BTW, the answer would be: "a huge percentage of them"...unlike Covid.)
2) They weren't trying to say anything about catching the virus. I understand that you really want to use this paper to make the claim, but it's just not relevant.
They took a population of young people hospitalized for Covid, removed the pregnancies, and looked at what happened to the rest. That's it. It doesn't tell you anything about "catching Covid". It does tell you that if you're young and not obese, not diabetic and don't have heart disease, you are overwhelmingly likely not to die from it.
> 2) They weren't trying to say anything about catching the virus. I understand that you really want to use this paper to make the claim, but it's just not relevant.
I know that, and I wasn't talking about catching, I was talking about the risk of death if you catch it.
> The equivalent study would be "of young people hospitalized with ebola, what percentage of them die?" (and BTW, the answer would be: "a huge percentage of them"...unlike Covid.)
> It does tell you that if you're young and not obese, not diabetic and don't have heart disease, you are overwhelmingly likely not to die from it.
I'm not sure what your definition of "overwhelming" is so I'll put it this way:
Of young people hospitalized, the percentage chance of death is still pretty high. The numbers you quoted were 10 percent! I'm pretty sure you quoted wrong and the real number is 3 percent, but that's still a very real chance of death that you should try very strongly to avoid.
The original quote was "Young healthy people have never been at risk."
Your amended version was "the risk is quite small indeed".
Neither of those fits a 3 percent death rate, even after taking into account the risk factors and focusing on patients without them. That chance of death is something that might be acceptable once or twice in your entire life after great consideration.
The only way to get a "small" risk here is to factor in a sufficient number of people that catch it but never end up in the hospital at all (if there are enough of them). Going purely by the hospital numbers it's not something to brush off at all.
I didn't bother to explain that part because I didn't think you were actually suggesting that 343 out of 3222 is quite low risk! I assumed you were talking about a different number.
You're re-stating what I wrote. There's a very small risk. It is not zero.
If you want to attack someone (again: not me) for saying "there's no risk to young people unless they're obese" -- which is essentially what the OP said -- then that's your prerogative, but I have better places to grind axes.
I think it's important to make it clear that the risk is quite small indeed, and let people make up their own minds. That's different than implying that a "non-zero risk" is somehow meaningful to a young person.
> Also younger people get Long Covid at higher rates.
We do not have a definition for "long covid", let alone enough information to make such a claim.
At best, this is blatant speculation, at worst, it's completely false. The best data for long-term sequelae of Covid indicate that it correlates with disease severity, which itself correlates (strongly) with age.
Agree, the media is really putting this "long covid" fear into younger people to just scare them to not congregate and spread the virus. Long covid can be substituted with long pneumonia, long flu etc. I had long flu back in early 2018, was extremely sick for 3-4 weeks, and went to the Dr. 12 times in 2 months, after almost 3 months was back to normal somewhat, still had cough and fatigue which finally went away after the 3rd month. Very scary times.
What's been disappointing to me throughout this experience is the fact that a large percentage of people don't seem to understand contagion.
The idea that a young person is safe is convenient for young people, but irrelevant. We never seemed to communicate to a segment of the population that we are trying to keep them from spreading it, as well as keeping them from catching it.
I think that this is communicated clearly enough. People will do what they want to do. For example, you can't get clearer than printing pictures of cigarettes-affected lungs with warnings on cigarette packs. Yet certain people keep smoking.
To summarize it’s due to cross-reactive immunity resulting from previous coronavirus (but not CoV-2) infections. Up to 90% of uninfected adults have these antibodies already.
Could this explain why many people have mild cases but some have severe cases? I’d be curious to find out how effective the cross-reactive antibodies are compared to ones produced by a vaccine.
I read that more past exposure to coronaviruses might be the cause why older people suffer from covid more because their immune system is tuned down because of mildness of other coronaviruses it previously encountered so many times.
I'm unsure to the conclusions we can draw as Vancouver is currently at the start of a third wave. I don't believe BC is performing asymptomatic testing so these will be people who have enough symptoms to get tested so it's clearly not enough protection to keep from showing those symptoms.
Wait, you'd think that the four human coronaviruses that supposedly confer partial immunity against COVID-19 are endemic all over the world. If that's the case, why is Brazil doing so badly?
Coronaviruses are strongly affected by climate -- that's why we have "cold season". Maybe the endemic coronaviruses aren't endemic in Brazil's warm and humid climate?
Right. What this seems to be saying is that, for one tiny area of Vancover, BC, 90% of the people tested with a very sensitive antibody test showed that their immune system had encountered some relevant coronavirus and had reacted to it. Is that right?
The trouble is that the article has a clickbait title: "A majority of uninfected adults show pre-existing antibody reactivity against SARS-CoV-2". Which may get translated into "We already have herd immunity" by some television pundit shortly.
Is it clickbait? It's a journal article, and as far as I can tell "antibody reactivity" is the correct technical term for what they're describing. Certainly some pundits will misinterpret it, but I don't think we can expect researchers to shape everything they write to avoid PR misunderstandings.
You have to take into consideration a lot when thinking about Brazil.
- the midia and the president are of two different gangs
- data gathering in Brazil is a joke, the true numbers can be double the ones reported for more or less.
Easily double. Probably way more than that. I guess the only way to know is from excess deaths statistics. Even that is confounded by the collapse of the health care system.
What happened to Brazil from being 1/4 of the BRICs countries a couple of decades back. I know Bolsonaro does not have cred in American media but was the system just a house of cards?
The fact that in many states there are people dying for lack of hospital beds is not "perception coming from how the media reports it".
I'm Brazilian born and raised, and even though have been out for about 7 years most of my friends and family are still there.
The fact that pretty much everybody I know over there knows at least a handful of people who have died of COVID-19 and hell knows how many that have had it is not "how the media reports it".
The struggle is real, the situation is pretty dire over there.
Studies keep saying this. People keep pointing to these studies, and demanding policy changes. But I've yet to see a study that makes any claims about:
1. What percentage of these people can catch COVID.
2. How likely they are to infect someone else if they do.
For some reason, communities around the world keep getting second, third, fourth, and fifth waves of infections, and viral variants keep evolving, despite the proliferations of studies like this.
It's like measuring the level of humidity at ground level, and using that to conclude that it's raining. Yes, there's a correlation. No, that's not a reliable way to measure rainfall. A reliable way to measure rainfall is putting a bucket out.
This study is about antibodies stemming from infection with other viruses and explicitly does not come to a conclusion about whether they are meaningfully protective against SARS-CoV2.
I'm well aware of this. That's what makes it useless for making policy decisions, just like my ground-level hygrometer is useless for telling me if its raining... But my bucket isn't.
The fact that communities open up -> communities get another wave of COVID keeps playing out over and over again leads me to believe that neither #1 or #2 are likely to be favourable to us.
Tinfoil hat theory : the SARS-1 outbreak was bigger than documented in east asia and possibly there was an escaped variant with mild symptoms that circulated undetected for some time (testing was not so good 20 years ago). 20 years later places like Tiawan, Veitnam and South Korea have a chunk of their population with an immunity - a little like the immunity to Swine Flu conferred by Spanish Flu.
We seem to keep circling on how it started, but the reality is that something happened in Wuhan.
Viruses don't spring from nowhere, or jump from caves 1000km away to an urban population that just happens to have a lab studying them. I just find the coincidence here too great.
My money is on still on someone associated with the lab became the vector where what they were working on gained function from some other highly spreadable coronavirus. Only takes one protocol breach for a PPE failure, and these labs worldwide seem to have lapses all the time.
They need to find a sample of this mystery virus that was circulating beforehand and see if it had the novel ACE2 receptor binding that the bat virus most like SARS-Cov-2 lacked - maybe then they can put the hypothesis that the lab was involved to rest.
This current we don't really know how it happened is bullshit.
I posited not that sars-1 caused some of that immunity, but that another coronavirus which was spreading around later in 2019. I lost my sense of smell completely around thanksgiving 2019 and don't think that was covid-19 but a similar virus that possibly turned more deadly due to a mutation. My brother was in China earlier in October 19' and I believe he got me sick with it. He himself got sick back to back to back from whatever he had(and he never gets sick). But this is total conjecture.
Maybe conjecture, but they are little pieces of information that seem to be common across many parts of the world at that time.
The summer 2019/20 spike in hospitalised pneumonia cases in the southern hemisphere that were a non-flu virus is another data point out there - someone just needs to put them all together.
The viruses going around 19/20 winter in WA included all kinds of non-flu viruses. The rapid flu test also suffers from the same 50% false negative rate that the rapid COVID test suffers from.
SARS-CoV-2 was almost certainly spreading in Wuhan in October. If your brother was there, and caught a virus, and gave it to you, and you substantially lost your sense of smell, then you should buy a lottery ticket because you were one of a small set of cryptic 2019 infections in the US (or wherever you are).
I would normally kind of shit all over anyone outside of China claiming to have caught the virus in 2019, but you tick off the two boxes which are complete and total loss of smell and contact tracing to someone actually back in China. Presumably you didn't pass it on to anyone or it otherwise died out and never found a superspreader (the majority of chains of infections of SARS-CoV-2 actually die out due to the way it transmits mostly by superspreading and it can take 4+ "seeds" on average before epidemic spread kicks off in an area).
Why didnt we test peoples breaths for being potential superspreaders? If the vaccines make people less infectious, superspreaders should have it first. In a privacy preserving way, they should also be advised to avoid gatherings.
> The findings of this study indicate that that it is possible the virus that causes COVID-19 may have been present in California, Oregon, and Washington as early as Dec. 13-16, 2019, and in Connecticut, Iowa, Massachusetts, Michigan, Rhode Island, and Wisconsin as early as Dec. 30, 2019 - Jan. 17, 2020.
You may want to read that study closer. Most of it is finding cross reactive antibodies, which as the title study here indicates we know isn't indication of prior SARS-CoV-2 infection. Specifically this paragraph:
> In order to better characterize the specimens that were reactive on the pan-Ig ELISA containing whole SARS-CoV-2 spike protein as the capture antigen, and distinguish these from cross-reactivity to common coronaviruses, additional, more specific SARS-CoV-2 testing was performed. The S1 subunit has been reported to be a more specific antigen for SARS-CoV-2 serologic diagnosis than the whole S protein [23]. Furthermore, in recent studies, sera from patients with confirmed human coronavirus infection only contained SARS-CoV-2 S protein–specific IgG antibodies and did not contain IgM or IgA antibodies; neutralizing activity in these sera was found to target only the S2 portion of the spike protein [23, 24]. Therefore, the presence of IgM or IgA antibodies and S1-specific binding activity may distinguish antibodies to SARS-CoV-2 from antibodies to human common coronaviruses [23, 24]. In the present study, 84 of 90 (>93%) reactive sera had neutralizing activity against SARS-CoV-2 virus, 39 (44.3%) had both IgG and IgM SARS-CoV-2 S protein–specific antibodies, 2 (2.2%) sera had surrogate neutralization activities, and 1 of 90 (1.1%) had SARS-CoV-2 S1-specific Ig. Collectively, these data suggest that at least some of the reactive blood donor sera could be due to prior SARS-CoV-2 infection. One serum sample, collected on 10 January 2020 in Connecticut, demonstrated a neutralization titer of 320, a signal-to-threshold ratio of 6.75, and 70% inhibition activity by surrogate neutralization activity, but was Ortho S1 nonreactive. These data indicate that this donation was likely from an individual with a past or active SARS-CoV-2 infection.
They found maybe two good signals for SARS-CoV-2 infection, with only one in Jan 2020 that really passes the test for definitively being SARS-CoV-2 infection. The neutralizing titers were in the total absence of IgG/IgM SARS-CoV-2 S-protein specific antibodies, which can be cross reactivity to antibodies against other coronaviruses. The fact that they were neutralizing against SARS-CoV-2 though in vitro doesn't necessarily confer actual protection as was seen in the study that Derek Lowe cites.
That study is still consistent with not knowing of any SARS-CoV-2 infections in the USA in 2019 and there being nothing possible other than cryptic spread.
Is this study really just telling us that 90% of adults have had a cold in the recent past?
edit: Not implying SAR COV-2 is "a cold". I'm implying it's a coronavirus also like the common cold, hence an antibody study would have to be careful to select for the right one.
It may also be telling us that the antibody tests and our understanding of how antibodies help in protecting against severe Covid may be wildly wrong. Vaccine data indicates overall immune response is protective, and can be successfully prompted, and that is correlated with antibody levels, but there may be more going on here.
Designed for, but except in a very small number of cases not actually validated in the field to perform that way - and the specific antibodies may not be a useful indication of a useful immune response in the way we think it is. We do not have the actual evidence to demonstrate it.
The emergency use authorizations allowed anyone who plausibly had a test to market it, even if it had not been independently validated in any way by anyone. Many folks just bought what they could find, even if it didn’t have an emergency use authorization.
Combined with porous borders, e-commerce and the internet, lack of consequences for someone in China to ship junk here? We got buried in (at best) untested junk, and often outright scams.
This has resulted in a rather predictable disaster when it comes to data and awareness - very few of the tests are being cross referenced to other data sources or tested against an independently verified data source, and even fewer (if any) are being evaluated by a independent party. The vast majority of tests in April have since been removed from authorization because they don’t work, don’t work well enough, etc. You can read a very nice paper from the FDA here summarizing it. [https://www.nejm.org/doi/full/10.1056/NEJMp2033687]
As far as I am aware, there is still no clear picture on which tests have actually been validated, by whom, and to what extent against what data set. Will they pick up variants, and if so which ones? With what accuracy? What are common field errors (collection problems, etc) that can lead to problems? What about manufacturing variance and supply chain issues?
You've raised the bar a long ways from except in a very small number of cases not actually validated in the field to perform that way to a comprehensive analysis of all tests that have even maybe been available.
Of course, the 'very small number of cases' makes it impossible to argue without doing a comprehensive study, but it's clear enough that the widely used commercial tests were developed with the idea that they should minimize false positives and tested against pre-Covid serum.
Thank you for digging that up! When I searched, I got a bunch of ads and junk from well before that study was run.
Do you have any data on which tests are widely used? (As in by number of tests done?)
I’m hoping it’s shifted the way you’re saying, but as of November there were more BS ones than legit ones, and it was hard to find a real validated test. None of the folks I knew getting antibody tests were able to find any of the validated ones.
That validated tests are good is great if they are being used, or used widely. Because in November the ones being used widely were still junk, which was my point.
If you have, per your study, 3 tests that are validated - are they used in the field for these studies? If so, objection withdrawn for current studies using them.
If they are studies based on the older, unvalidated, and often junk tests - then that point still stands.
I checked one test, using a non biased sampling method, and it contradicted the whole structure of your argument. Why would you expect anyone to continue the conversation on your terms?
Yeah I saw a recent study that showed in monkeys the T cell response didn't really matter or do much for COVID-19. They looked at monkeys which had an illness that depleted their T cells and compared to healthy monkeys to see how an infection of COVID-19 went and saw surprisingly the T-cell depleted monkeys weren't much worse off. This is somewhat of a surprise since it was assumed T cells would be an effective way to neutralize COVID-19. Ultimately it just shows there are many more mysteries to this virus than solid answers. Preprint here: https://www.biorxiv.org/content/10.1101/2021.04.02.438262v1
> "Ultimately it just shows there are many more mysteries to this virus than solid answers."
it's not the virus but rather our bodies that are so mysterious. the virus is relatively simple in comparison (which is different from saying we know everything about it, since we obviously don't).
Nod, and we have a lot of practical ethical issues getting in the way (rightfully so) of figuring it out too. It is really hard to figure out realistic risks around exposures without doing field trials for instance. We could of had a much earlier vaccine rollout if we’d done double blind, intentional exposure studies (give someone the vaccine or saline, unknown to anyone, then stick them in the same room as a bunch of Covid patients with no protection) with early versions - which we could have done in March. We had 250+ candidates at the time, and about 3% were proven out, when I looked in Jan/Feb.
To get somewhat useful data, you’d probably need to do that for at least a couple thousand folks (10k each arm would be my guess), so you’re looking at what, 5 million total in the study, 2.5 million exposed? Based on the best data we had at the time (assumed 3.5% fatality rate I believe?), that would have been 87k fatalities out of that group. [https://www.who.int/bulletin/volumes/99/1/20-265892/en/ ], Currently seems like estimates are around 1-2% which would drop it to only 25-50k [https://www.nature.com/articles/s41392-021-00527-1].
For many very, very good reasons that isn’t how we roll right now though, and we do have good technology for solving this either. Star Trek style ‘simulate’ mode is a looong way away in this space.
Looking forward to it hopefully getting better soon though - a lot of money going into getting this figured out.
yah, i think my underlying point is that it's certainly worth using this opportunity to further our understanding of the body and its immune system vs. getting infatuated with the virus itself, because the former is likely much more transferable knowledge than the latter.
in general, we have trouble modulating our attention and resource allocation around unique events like this, and it behooves us to zoom out and put it in the proper context.
"Wildly wrong" may be stretching it a bit, but you're not entirely off base. There's more to the vaccines than simply getting antibodies to show up in the blood stream.
Along with inducing antibodies for immediate defense, mRNA vaccines against COVID-19 also stimulate the lymph nodes to generate immune cells that provide protection over the long term, a new study confirms. The early wave of antibodies are generated by B cells called plasmablasts. In healthy volunteers, blood tests showed that two doses of the Pfizer/BioNTech vaccine induced "a strong plasmablast response," said coauthor Ali Ellebedy of Washington University School of Medicine in St. Louis. The immune cells that will produce antibodies upon exposure to the virus in years to come - called memory B cells - are generated by germinal center B cells found only in lymph nodes near vaccine injection sites, his team explained in a paper currently undergoing peer review for possible publication in a Nature journal. In repeated biopsies of volunteers' lymph nodes, "we saw a robust germinal center response," Ellebedy said. The responses lasted at least seven weeks, "with no sign of cooling down anytime soon," he added. "While we do not have long-term samples yet, it is safe to assume given the magnitude and persistence of the germinal center reaction that those individuals will develop a durable immune response" to mRNA vaccines. Moderna Inc's vaccine also uses mRNA technology.
yes, the "common cold" can be carried by rhinoviruses, coronaviruses, influenza viruses (maybe a mild case of 'flu' mistaken as a cold), and adenoviruses.
I've never really understood the link between "being cold" and catching the "cold". I assume it's because your immune system is somehow slower when you're cold, but the correlation seems pretty strong based on what I have observed. Other people and I very rarely catch a cold without being cold, and after being cold it's common to catch a cold. Are there *viruses floating (?) around constantly, and your body is severely less effective at fighting them off when cold? Is it just confirmation/survivorship bias?
From what I can find online, there's a correlation, but it's pretty light on details about how strong it is.
I'm pretty sure (unverified claim) that the "cold" description got linked with the illness in pre-germ-theory-of-disease days, where being outside in the cold for too long would imply one "caches a cold" when they feel ill the next day.
> Sense of "indisposition involving catarrhal inflammation of the mucous membranes of the nose or throat" is from 1530s, so called because the symptoms resemble those of exposure to cold; compare cold (n.) in earlier senses "indisposition or disease caused by excessive exposure to cold" (early 14c.), "chills of intermittent fever" (late 14c.).
Put less technical: shivering, runny nose, etc, are symptoms of both the common cold and being cold.
In the sense that people with rhinovirus symptoms usually say "I have a cold", yes.
It seems it's best to think of "cold" and "flu" as totally informal terms with a wide range of possible meanings. I've had Actual Real Influenza twice and both times it knocked me on my ass for a week, lost weight, etc. yet I hear people saying "I have the flu" when they have mild symptoms and only miss a single day of work. Hard to take such a wide range medically seriously.
> I hear people saying "I have the flu" when they have mild symptoms and only miss a single day of work.
They could have had influezna with mild symptoms. Two different people can have the same influenza virus enter their body and experience different effects. Anywhere from no symptoms at all to death.
It means their body responds to the virus, we aren't necessarily clear on why. Supposedly, this could be because they came in contact with SAR COV-2 OR some other virus which enabled the response.
In this case, 77% of participants were in the medical profession and were evaluated between May and June 2020. I suspect they came in contact with SAR COV-2 and didn't even realize it (body fought it off).
What this study is really suggesting is that your body either (a) has an immune response from previous contact (likely due to similarity with regular corona viruses) or (b) lots of people show no symptoms (we know this) and that they obtain an immune response from it.
In either case, the SAR COV-2 is likely far-less dangerous in the sense that more people have it and there are less deaths per infection OR many of us have a natural immune response (more than previously suspected).
Well, we do know how dangerous this virus is. This new data doesn’t tell us anything new because mortality rate is mortality rate and that’s that. What this data might do is help point to what further research to conduct to try to figure out why some people have such strong reactions to COVID while others have few or no symptoms at all.
For practical purposes, do you want to count these symptom-free infections in that calculation? Knowing this, would you want to do anything differently in how we handle this pandemic? I don’t see how this changes much at all about our present situation.
I am not against knowledge in any way. More research will only help. What I am saying is that in the people who get sick, the mortality rate is 1-3%. This data does not tell us whether that generalizes to everyone or not because merely having these antibodies does not guarantee that you actually won’t get deathly ill. It could be interpreted that you have full immunity or it could be interpreted that you have a weak immunity to COVID. More research is necessary.
However the “pretend mortality rate” you refer to is not a thing. It is 1-3% in people who test positive, which correlates pretty strongly with people who have the disease. Think about it this way: the yearly flu in 2018-2019 had a mortality rate of 1.3-48.7% according to the CDC. The denominator in that was 61,000 or so cases. If you found out that 100,000 additional people were exposed to the flu but had no symptoms and by any definition had no flu illness would that change your outlook on whether the flu vaccine or hand washing is worth it?
Or another example: there is surgery which has a mortality rate of 15% due to post surgery infection. Not everybody needs the surgery, only 100 people per year do. Does that mean the rate of mortality here is fake because the denominator should be 7.5 billion? Or should we only count the people who get the disease that necessitates the surgery?
> If you found out that 100,000 additional people were exposed to the flu but had no symptoms and by any definition had no flu illness would that change your outlook on whether the flu vaccine or hand washing is worth it?
Yes, of course my outlook would change. Not on the binary scale--i wouldn't suddenly think it's not worth it to wash hands-- but I would want to know when deciding on measures.
The mortality rate is a specific figure, it's not whatever figure makes your reaction most appropriate.
If some people get the virus and have no symptoms, that's an incredibly important piece of the puzzle when deciding how to proceed.
Using your exaggerated examples, what if 99% of the population didn't suffer any adverse effects? Wouldn't you reevaluate the current response in light of that?
> If some people get the virus and have no symptoms, that's an incredibly important piece of the puzzle when deciding how to proceed.
This study does not tell you that these people had COVID. That's the point: we don't know what this means. All we know, is that we need to study this further.
> The mortality rate is a specific figure, it's not whatever figure makes your reaction most appropriate.
From Wikipedia: "Mortality rate, or death rate, is a measure of the number of deaths (in general, or due to a specific cause) in a particular population, scaled to the size of that population, per unit of time." What is the "particular population" here is in question. I argue that "people who had the SARS-CoV-2 disease" are the relevant population. That is, people who had symptoms or tested positive after an exposure. This study does not change this because it shows no source of the antibodies: if I inject my COVID-19 antibodies into your arm, it does not mean that you had the disease and therefore should not be counted in the mortality rate, does it? How those antibodies got there is a question yet to be answered but the possible answers range from "those people got a mild case and didn't notice" to "those people developed low level antibodies due to incidental contact with COVID-19" without getting the the illness. Their immune system is not trained well enough to fight off a higher viral load."
> Using your exaggerated examples, what if 99% of the population didn't suffer any adverse effects? Wouldn't you reevaluate the current response in light of that?
Yes and no. First, this study does not tell me anything regarding suffering adverse effects. But if a future study did, I think the 3 million people that have died so far would have wanted us to take more precautions, not less, just because we, the living, won the antibody lottery. At the end of the day this is a highly infectious + somewhat deadly disease that adds up to one deadly pandemic. If your point is that only another few million will die if we let it run rampant vs all of humanity, I don't disagree with you but urge you to examine what it means to let millions of people die in this case.
> For practical purposes, do you want to count these symptom-free infections in that calculation?
well it possibly changes the calculus of how many people could potentially be a carrier of the virus. if that many people had the disease enough to have some antibodies even with all the extreme measures put into place it is possible this virus is even more contagious than we thought it could be. i don't know and i feel like we won't know because the study of transmission is woefully hard to do. going into this we didn't even know specifically how the flu was transmitted other than hand waving ways(maybe on the surface, maybe aerosols, maybe particles). our research has improved but it's still not great.
Agreed. This tells us that we need to do 100 more studies and not much else. It doesn’t conclude that the people with these antibodies are actually any better off and not getting sick or not transmitting the disease. As you point out they might be worse off. Everyone here is getting very excited about this study because I suspect people think this means that everyone already had COVID so there is less reason to worry. This study says nothing of the sort.
Mortality rate is the ratio of deaths to individuals in a specific population.
So there's the mortality rate for the overall population (what GP is referencing) vs mortality rate among people who've had COVID (what I believe you're referencing). Both are valid and useful in different circumstances: "How likely am I to die if I get COVID" changes as we discover a glut of asymptomatic cases, but "What % of the population will die of this disease?" stays the same
> "What % of the population will die of this disease?" stays the same
That doesn’t sound right — you can’t know the population death rate definitely without knowing the infection rate;
If no one gets the disease in your sample population of 100, your death rate says 0. If 1 person is infected and 1 dies, your population death rate says 1%. If 80 are infected, and 10 dies, your population death says 10%.
The “correct” number should be stable, but the population death rate should be changing as the disease spreads, approaching the correct number (but this is also true of liklihood of dying to COVID)
Your population death rate would only be static if your sample population is 100% infected, which is the same as “How likely am I to die if I get COVID”
You are getting a bit carried away. You aren’t wrong, the number of people who already got sick and either recovered or died affects future infection rates. So do other things. But I’ll use the example I used in another comment here: if you have 7.5 billion people in the world, and a rare disease that requires surgery where 100 people per year get sick, and all 100 undergo the surgery, and 15 of them die due to post surgery infections, is the mortality rate of the surgery 15/100 or 15/7.5 billion? If the latter, why?
As another example: lots of people have the tuberculosis infection which lies dormant in their lungs. TB infection is distinct from TB disease which is where you get symptoms. The former is only dangerous in that it can develop into the latter. The latter can kill you. How should you look at these numbers? Is it worthwhile to drop the number of people with TB disease and just divide deaths by TB infections or is it more informative to derive mortality as deaths / TB diseases while also using TB infections and the conversion rate from those to TB disease to calculate risk and transmissibility? I argue the latter is much more relevant to decision making.
Keep in mind that the death rate still has to exist in a given time frame so only can only be extrapolated backwards and has to be recalculated annually.
Strikes me as similar to those who predict x% returns on their s&p index funds based on past stock market performance.
I don’t think you can directly compare disease to the stock market. The stock market is a level 2 chaos system: predictions about it are direct inputs into the system affecting outcomes. Disease is generally much closer to level 1: it is random but unaffected by predictions. COVID is possibly mildly affected by predictions in that people might make travel plans based on predictions but I don’t think the majority of people are acting in ways that seriously change their transmission risk based on predictions.
Mortality rate may be unknown. But we know it's killed at least a half million in the US alone, 3 million worldwide. There are also deaths not associated with Covid 19 but caused by it (they didn't get a test before or after death). That's still the highest rate of death we've seen since the last pandemic (spanish flu) caused in a single season by a virus. So yes it is dangerous.
We can estimate the total number of infections through seroprevalence studies. The latest research shows a global infection fatality rate of about 0.15%, although there has been a wide variance between countries.
We know the mortality rate to a degree. Mortality rate is number of deaths over the number of instances. If you have limits on the accuracy of the denominator you have limits on the accuracy of mortality rate.
Sero studies like this one suggest to how many infections of the virus we have been missing.
The current answer to me seems to be that we do not know one way or the other. The hope is that it will but we are just now starting to get some data on how effective vaccines are at preventing transmission (Pfizer seems effective, others have no conclusive data AFAIK), we don’t know what herd immunity actually is (Fauci estimates between 70 and 95% vaccinated; 70% is possible without vaccinating children, 95% is not. In the US you have enough anti-vaxxers to prevent herd immunity from ever happening even at 70%), we don’t know how long the vaccine is good for (current estimate is at least 6 months but no clue if it is more), and we don’t know what other mutations will show up. The peachy scenario is that we vaccinate everyone super quickly while keeping social distancing and masks to not have any new variants develop and herd immunity can be achieved with very low percentages. The other scenario is that we take our time, dozens of vaccine resistant variants pop up in the meantime and it never goes away because a virus can mutate and spread more quickly than we can play whack a mole.
Question: Could a COVID-19 vaccine (or any vaccine for that matter) have contagious immunity? In other words, is it possible (at present or in future vaccines) for the safe variation of the virus (or whatever the delivery agent) to be passed from person to person?
I understand that without symptoms like coughing or sneezing, the vector for spreading would be relatively limited, but I have to imagine it's still possible (even commonplace) for healthy individuals to effectively spread bacteria/viruses (even harmless ones).
If it is possible, what are the chances of that happening unintentionally? Would it be ethical to engineer a vaccine to intentionally do that?
I'm not trying to imply that's what's happening now - but I am curious.
Sterilizing immunity is the term you're looking for, and as far as I know the vaccines are still being studied to determine if it happens. It's very difficult to determine right now because you need to very carefully control a studied person AND all of their contacts and people they interact with--you test all of those people daily and then can tell if people in the vaccine or placebo group have close contacts coming down with sickness more or less often (hinting at the presence or not of sterilizing immunity). The big trials for EUA of the major vaccines declined to do this kind of study because it takes longer and costs a LOT more to do that much testing across 60k people + all their contacts.
It will also be more challenging going forward to do these kinds of studies because of the ethics. It will be hard to ethically justify keeping an arm of a trial unvaccinated as a placebo in the face of a very serious and very deadly virus which we have known good vaccines. There are some interesting things like crossover trials that apparently more of the current in research vaccines are trying.
In principal, viral vector vaccines are technically transmissible, though I do not think we have demonstrated actual transmission anywhere. The J&J vaccine is a viral vector vaccine.
The mRNA COVID vaccines are not; with those, the vaccine material is mRNA that your body codes into a protein recognizable to the immune system. The mRNA is both unstable (so it doesn't last long inside the body) and not capable of contagious transmission
> Could a COVID-19 vaccine (or any vaccine for that matter) have contagious immunity? In other words, is it possible (at present or in future vaccines) for the safe variation of the virus (or whatever the delivery agent) to be passed from person to person?
If a vaccine used a virus that was both live and contagious but somehow safe, its not impossible; of course, there’d also be a risk of it mutating to become unsafe.
The actual vaccines for protection against COVID-19 that I know of don’t use a delivery mechanism where that is possible; that’s certainly not something, e.g., a mRNA vaccine could do.
The title seems to suggest that the reason many people haven't been infected yet is because they are immune, and that we are therefore approaching herd immunity. I'd caution against drawing that conclusion until case numbers and R0 start declining. In some places where vaccination campaigns have been aggressive, like Israel, we are starting to see what looks like herd immunity. What this study appears to show is that some of the antibodies against coronaviruses that people already have from the common cold may also fight against SARS-CoV-2. But that may have been the case from day 0 of this pandemic.
I am not sure how to reconcile this with the fact that there has been a global pandemic for the past year or so. Perhaps I am missing something obvious. Can anybody explain?
They didn't study whether the reactive antibodies were protective, just whether they were there.
The thing the study establishes is that most adults have antibodies that will react to some parts of the pandemic virus. And then that's it. They didn't establish whether it was protective or not or anything like that.
I would assume that most people have some sensitivity because they've been exposed to coronaviruses before. However this is not enough to quickly raise an immune response when the new variant shows up.
It doesn't need to be a global/political conspiracy for people to be more sensitive to a large amount of people dying after almost 20 years of significantly lower death rates.
Edit: Also, looking at overall deaths per million is not anything like comparing actual mortality rates of those infected. The baseline mortality in 1918 was already way higher and the pandemic amplified that, despite actually being less deadly than COVID-19 at an individual level. So I'd argue that the response to this pandemic was more than merited and was appropriate to the nature of the virus itself. It was not just another "asian flu."
It would seem unlikely that the population would notice a 6% increase against the base annual death rate. We previously tolerated hospital overcrowding and death spikes from influenza waves.
Most other countries around the world are showing a 4-6% increase. There seems to be a correlation to severity of lockdown and increased number of deaths, presumably due to factors like interruptions to regular medical treatments, and individual health deteriorating during lockdown.
An alternate scenario could also be the most at risk populations (elderly, obese, etc.) lockdown, while the young, healthy, low risk populations gain quick herd immunity
For this to work, (a) the young would actually have to be very low risk and (b) they could NEVER contact those in the sheltering groups. Which would be a problem with families with older children or multi-generational households. And schools would have difficulty remaining open due to teachers and staff being isolated in some degree. And the variants that develop in this regime might have been hard on the young - in Canada, much of the current ICU crowd is young, lower-risk individuals.
> In total, 276 healthy adults were recruited for this cohort between May 17th and June 19th 2020. (...) The majority (n = 196; 71%) were health care workers
This number seems low. I think the title is poorly worded, to me it concludes more of that healthcare workers in Canada developed antibodies before being diagnosed with COVID-19
If you did have covid, then the theory is that you'll have a more severe reaction to the first shot because your body's already seen the virus and is primed to fight.
It would be nice if HN would be a place that is free of Corona related debate.
Especially, since most people here are not qualified to draw the correct conclusions from studies such as this.
The people in this community are more qualified than most people in my social circles for debating this topic, and tend to be less motivated toward bias. People here tend to be better at referencing source material, facts, and statistics that support their thoughts.
Although I don't usually seek out this topic in this community, I find these discussions here helpful from time to time.
Locking down scientific information from the greater scientific community and the general population is a terrible and anti-scientific idea which we have seen implemented by many theocracies and authoritarian states throughout human history
> But here’s the key part: “cross-react” does not mean “neutralize” and it does not mean “provide protection from”. These antibodies may or may not have been neutralizing against the other coronaviruses, but they don’t seem to have any such effect on the current one. And in keeping with that, having such cross-reactive antibodies seems to provide no protection against catching SARS-Cov2 or against being hospitalized with it if you do. There’s no difference in the infection/hospitalization rates of the people who had cross-reactive coronavirus serum antibodies ready to go versus those who didn’t. They’re basically useless.
> Now, you can still make an argument that the T cell component of immunity might provide some protection after a previous coronavirus infection. The current study didn’t address this directly, but after these results, it’s at least less likely that that’s happening. The authors make a note of this, and also note that pre-existing mucosal antibodies might exert a protective effect (which this study didn’t examine, either). But prior circulating human coronavirus antibodies, even ones that can bind to the current one – those it looks like we can rule out. Which is too bad.
The title study here is nothing new, we know there's cross reactive antibodies to other coronaviruses, they're not neutralizing, the hospitalization/death rates are the same so they don't confer any protection.
Nobody had any pre-existing immunity to this virus before it erupted last year (and no, the virus or variants of it were not traveling the globe months or years earlier).
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[ 2.9 ms ] story [ 236 ms ] threadYoung healthy people have never been at risk.
A more accurate way to phrase this is that young non-overweight people are at far less risk than young obese people. It's not true that young healthy people are at no risk.
From https://jamanetwork.com/journals/jamainternalmedicine/fullar...:
Among 780969 adults discharged between April 1, 2020, and June 30, 2020, 63103 (8.1%) had the ICD-10 code for COVID-19, of whom 3222 (5%) were nonpregnant young adults (age 18-34 years) admitted to 419 US hospitals. The mean (SD) age of this population was 28.3 (4.4) years; 1849 (57.6%) were men and 1838 (57.0%) were Black or Hispanic. Overall, 1187 (36.8%) had obesity, 789 (24.5%) morbid obesity, 588 (18.2%) diabetes, and 519 (16.1%) hypertension (Table).
During hospitalization, 684 patients (21%) required intensive care, 331 (10%) required mechanical ventilation, and 88 (2.7%) died. Vasopressors or inotropes were used for 217 patients (7%), central venous catheters for 283 (9%), and arterial catheters for 192 (6%). The median length of stay was 4 days (interquartile range, 2-7 days). Among those who survived hospitalization, 99 (3%) were discharged to a postacute care facility.
Morbid obesity (adjusted odds ratio [OR], 2.30; 95% CI, 1.77-2.98; vs no obesity; P < .001) and hypertension (adjusted OR, 2.36; 95% CI, 1.79-3.12; P < .001) were common and in addition to male sex (adjusted OR, 1.53; 95% CI, 1.20-1.95; P = .001) were associated with greater risk of death or mechanical ventilation. Odds of death or mechanical ventilation did not vary significantly with race and ethnicity. Morbid obesity was present in 140 patients (41%) who died or required ventilation.
So, 3222 / 780969 = 0.4% of the examined population had admission to a hospital with "Covid" on their forms. Of these, 343 died (0.04% of examined population; Table 1).
Obesity, hypertension and diabetes were strongly correlated with death in this population.
That's not "no risk", but it's consistent with the OP's comment: the risk for young people is quite low, and is concentrated amongst the obese (and diseases related to obesity).
Just for the obvious extreme example, if I say 0.01% of total hospitalizations are young people with ebola, that doesn't let you conclude anything about whether catching ebola is "quite low risk" for that group.
It tells you what to expect if you're a doctor working with hospitalized patients, or if you run a hospital.
This is why they did the study.
> if I say 0.01% of total hospitalizations are young people with ebola, that doesn't let you conclude anything about whether catching ebola is "quite low risk" for that group.
1) that's not what this study calculated. You still don't understand it.
The equivalent study would be "of young people hospitalized with ebola, what percentage of them die?" (and BTW, the answer would be: "a huge percentage of them"...unlike Covid.)
2) They weren't trying to say anything about catching the virus. I understand that you really want to use this paper to make the claim, but it's just not relevant.
They took a population of young people hospitalized for Covid, removed the pregnancies, and looked at what happened to the rest. That's it. It doesn't tell you anything about "catching Covid". It does tell you that if you're young and not obese, not diabetic and don't have heart disease, you are overwhelmingly likely not to die from it.
I know that.
> 2) They weren't trying to say anything about catching the virus. I understand that you really want to use this paper to make the claim, but it's just not relevant.
I know that, and I wasn't talking about catching, I was talking about the risk of death if you catch it.
> The equivalent study would be "of young people hospitalized with ebola, what percentage of them die?" (and BTW, the answer would be: "a huge percentage of them"...unlike Covid.)
> It does tell you that if you're young and not obese, not diabetic and don't have heart disease, you are overwhelmingly likely not to die from it.
I'm not sure what your definition of "overwhelming" is so I'll put it this way:
Of young people hospitalized, the percentage chance of death is still pretty high. The numbers you quoted were 10 percent! I'm pretty sure you quoted wrong and the real number is 3 percent, but that's still a very real chance of death that you should try very strongly to avoid.
The original quote was "Young healthy people have never been at risk."
Your amended version was "the risk is quite small indeed".
Neither of those fits a 3 percent death rate, even after taking into account the risk factors and focusing on patients without them. That chance of death is something that might be acceptable once or twice in your entire life after great consideration.
The only way to get a "small" risk here is to factor in a sufficient number of people that catch it but never end up in the hospital at all (if there are enough of them). Going purely by the hospital numbers it's not something to brush off at all.
I didn't bother to explain that part because I didn't think you were actually suggesting that 343 out of 3222 is quite low risk! I assumed you were talking about a different number.
But a nontrivial percentage of young people hospitalized for COVID are not obese, and some otherwise healthy young people have died.
So the claim is false. "Much less risk" is not "no risk."
If you want to attack someone (again: not me) for saying "there's no risk to young people unless they're obese" -- which is essentially what the OP said -- then that's your prerogative, but I have better places to grind axes.
I think it's important to make it clear that the risk is quite small indeed, and let people make up their own minds. That's different than implying that a "non-zero risk" is somehow meaningful to a young person.
We do not have a definition for "long covid", let alone enough information to make such a claim.
At best, this is blatant speculation, at worst, it's completely false. The best data for long-term sequelae of Covid indicate that it correlates with disease severity, which itself correlates (strongly) with age.
That said, the news media has been shameless about misinterpreting data consistently in order to promote fear. It's a real problem.
The idea that a young person is safe is convenient for young people, but irrelevant. We never seemed to communicate to a segment of the population that we are trying to keep them from spreading it, as well as keeping them from catching it.
Could this explain why many people have mild cases but some have severe cases? I’d be curious to find out how effective the cross-reactive antibodies are compared to ones produced by a vaccine.
https://www.iflscience.com/health-and-medicine/prior-exposur...
And the poorer/denser the country, even more congregation in the fewer climate controlled spaces there are.
It is unclear whether this antibody reactivity may confer clinical benefits, for instance, modulating the severity of a SARS-CoV-2 infection.
I think quantifying any protective effect is gonna be pretty difficult.
The trouble is that the article has a clickbait title: "A majority of uninfected adults show pre-existing antibody reactivity against SARS-CoV-2". Which may get translated into "We already have herd immunity" by some television pundit shortly.
What data is there that indicates this is the case?
I'm Brazilian born and raised, and even though have been out for about 7 years most of my friends and family are still there.
The fact that pretty much everybody I know over there knows at least a handful of people who have died of COVID-19 and hell knows how many that have had it is not "how the media reports it".
The struggle is real, the situation is pretty dire over there.
1. What percentage of these people can catch COVID.
2. How likely they are to infect someone else if they do.
For some reason, communities around the world keep getting second, third, fourth, and fifth waves of infections, and viral variants keep evolving, despite the proliferations of studies like this.
It's like measuring the level of humidity at ground level, and using that to conclude that it's raining. Yes, there's a correlation. No, that's not a reliable way to measure rainfall. A reliable way to measure rainfall is putting a bucket out.
The fact that communities open up -> communities get another wave of COVID keeps playing out over and over again leads me to believe that neither #1 or #2 are likely to be favourable to us.
And super intriguing!
Viruses don't spring from nowhere, or jump from caves 1000km away to an urban population that just happens to have a lab studying them. I just find the coincidence here too great.
My money is on still on someone associated with the lab became the vector where what they were working on gained function from some other highly spreadable coronavirus. Only takes one protocol breach for a PPE failure, and these labs worldwide seem to have lapses all the time.
They need to find a sample of this mystery virus that was circulating beforehand and see if it had the novel ACE2 receptor binding that the bat virus most like SARS-Cov-2 lacked - maybe then they can put the hypothesis that the lab was involved to rest.
This current we don't really know how it happened is bullshit.
The summer 2019/20 spike in hospitalised pneumonia cases in the southern hemisphere that were a non-flu virus is another data point out there - someone just needs to put them all together.
https://threadreaderapp.com/thread/1249414291297464321.html
https://www.nejm.org/doi/full/10.1056/NEJMc2008646
The viruses going around 19/20 winter in WA included all kinds of non-flu viruses. The rapid flu test also suffers from the same 50% false negative rate that the rapid COVID test suffers from.
I would normally kind of shit all over anyone outside of China claiming to have caught the virus in 2019, but you tick off the two boxes which are complete and total loss of smell and contact tracing to someone actually back in China. Presumably you didn't pass it on to anyone or it otherwise died out and never found a superspreader (the majority of chains of infections of SARS-CoV-2 actually die out due to the way it transmits mostly by superspreading and it can take 4+ "seeds" on average before epidemic spread kicks off in an area).
> The findings of this study indicate that that it is possible the virus that causes COVID-19 may have been present in California, Oregon, and Washington as early as Dec. 13-16, 2019, and in Connecticut, Iowa, Massachusetts, Michigan, Rhode Island, and Wisconsin as early as Dec. 30, 2019 - Jan. 17, 2020.
> In order to better characterize the specimens that were reactive on the pan-Ig ELISA containing whole SARS-CoV-2 spike protein as the capture antigen, and distinguish these from cross-reactivity to common coronaviruses, additional, more specific SARS-CoV-2 testing was performed. The S1 subunit has been reported to be a more specific antigen for SARS-CoV-2 serologic diagnosis than the whole S protein [23]. Furthermore, in recent studies, sera from patients with confirmed human coronavirus infection only contained SARS-CoV-2 S protein–specific IgG antibodies and did not contain IgM or IgA antibodies; neutralizing activity in these sera was found to target only the S2 portion of the spike protein [23, 24]. Therefore, the presence of IgM or IgA antibodies and S1-specific binding activity may distinguish antibodies to SARS-CoV-2 from antibodies to human common coronaviruses [23, 24]. In the present study, 84 of 90 (>93%) reactive sera had neutralizing activity against SARS-CoV-2 virus, 39 (44.3%) had both IgG and IgM SARS-CoV-2 S protein–specific antibodies, 2 (2.2%) sera had surrogate neutralization activities, and 1 of 90 (1.1%) had SARS-CoV-2 S1-specific Ig. Collectively, these data suggest that at least some of the reactive blood donor sera could be due to prior SARS-CoV-2 infection. One serum sample, collected on 10 January 2020 in Connecticut, demonstrated a neutralization titer of 320, a signal-to-threshold ratio of 6.75, and 70% inhibition activity by surrogate neutralization activity, but was Ortho S1 nonreactive. These data indicate that this donation was likely from an individual with a past or active SARS-CoV-2 infection.
They found maybe two good signals for SARS-CoV-2 infection, with only one in Jan 2020 that really passes the test for definitively being SARS-CoV-2 infection. The neutralizing titers were in the total absence of IgG/IgM SARS-CoV-2 S-protein specific antibodies, which can be cross reactivity to antibodies against other coronaviruses. The fact that they were neutralizing against SARS-CoV-2 though in vitro doesn't necessarily confer actual protection as was seen in the study that Derek Lowe cites.
That study is still consistent with not knowing of any SARS-CoV-2 infections in the USA in 2019 and there being nothing possible other than cryptic spread.
edit: Not implying SAR COV-2 is "a cold". I'm implying it's a coronavirus also like the common cold, hence an antibody study would have to be careful to select for the right one.
The antibody tests are designed with high specificity for particular antibodies, this study went out of their way to look for any reactivity.
The emergency use authorizations allowed anyone who plausibly had a test to market it, even if it had not been independently validated in any way by anyone. Many folks just bought what they could find, even if it didn’t have an emergency use authorization.
Combined with porous borders, e-commerce and the internet, lack of consequences for someone in China to ship junk here? We got buried in (at best) untested junk, and often outright scams.
This has resulted in a rather predictable disaster when it comes to data and awareness - very few of the tests are being cross referenced to other data sources or tested against an independently verified data source, and even fewer (if any) are being evaluated by a independent party. The vast majority of tests in April have since been removed from authorization because they don’t work, don’t work well enough, etc. You can read a very nice paper from the FDA here summarizing it. [https://www.nejm.org/doi/full/10.1056/NEJMp2033687]
As far as I am aware, there is still no clear picture on which tests have actually been validated, by whom, and to what extent against what data set. Will they pick up variants, and if so which ones? With what accuracy? What are common field errors (collection problems, etc) that can lead to problems? What about manufacturing variance and supply chain issues?
You've raised the bar a long ways from except in a very small number of cases not actually validated in the field to perform that way to a comprehensive analysis of all tests that have even maybe been available.
Of course, the 'very small number of cases' makes it impossible to argue without doing a comprehensive study, but it's clear enough that the widely used commercial tests were developed with the idea that they should minimize false positives and tested against pre-Covid serum.
Do you have any data on which tests are widely used? (As in by number of tests done?)
I’m hoping it’s shifted the way you’re saying, but as of November there were more BS ones than legit ones, and it was hard to find a real validated test. None of the folks I knew getting antibody tests were able to find any of the validated ones.
That validated tests are good is great if they are being used, or used widely. Because in November the ones being used widely were still junk, which was my point.
If you have, per your study, 3 tests that are validated - are they used in the field for these studies? If so, objection withdrawn for current studies using them.
If they are studies based on the older, unvalidated, and often junk tests - then that point still stands.
it's not the virus but rather our bodies that are so mysterious. the virus is relatively simple in comparison (which is different from saying we know everything about it, since we obviously don't).
To get somewhat useful data, you’d probably need to do that for at least a couple thousand folks (10k each arm would be my guess), so you’re looking at what, 5 million total in the study, 2.5 million exposed? Based on the best data we had at the time (assumed 3.5% fatality rate I believe?), that would have been 87k fatalities out of that group. [https://www.who.int/bulletin/volumes/99/1/20-265892/en/ ], Currently seems like estimates are around 1-2% which would drop it to only 25-50k [https://www.nature.com/articles/s41392-021-00527-1].
For many very, very good reasons that isn’t how we roll right now though, and we do have good technology for solving this either. Star Trek style ‘simulate’ mode is a looong way away in this space.
Looking forward to it hopefully getting better soon though - a lot of money going into getting this figured out.
in general, we have trouble modulating our attention and resource allocation around unique events like this, and it behooves us to zoom out and put it in the proper context.
From https://www.reuters.com/article/us-health-coronavirus-scienc...:
Along with inducing antibodies for immediate defense, mRNA vaccines against COVID-19 also stimulate the lymph nodes to generate immune cells that provide protection over the long term, a new study confirms. The early wave of antibodies are generated by B cells called plasmablasts. In healthy volunteers, blood tests showed that two doses of the Pfizer/BioNTech vaccine induced "a strong plasmablast response," said coauthor Ali Ellebedy of Washington University School of Medicine in St. Louis. The immune cells that will produce antibodies upon exposure to the virus in years to come - called memory B cells - are generated by germinal center B cells found only in lymph nodes near vaccine injection sites, his team explained in a paper currently undergoing peer review for possible publication in a Nature journal. In repeated biopsies of volunteers' lymph nodes, "we saw a robust germinal center response," Ellebedy said. The responses lasted at least seven weeks, "with no sign of cooling down anytime soon," he added. "While we do not have long-term samples yet, it is safe to assume given the magnitude and persistence of the germinal center reaction that those individuals will develop a durable immune response" to mRNA vaccines. Moderna Inc's vaccine also uses mRNA technology.
this list is not comprehensive.
From what I can find online, there's a correlation, but it's pretty light on details about how strong it is.
> Sense of "indisposition involving catarrhal inflammation of the mucous membranes of the nose or throat" is from 1530s, so called because the symptoms resemble those of exposure to cold; compare cold (n.) in earlier senses "indisposition or disease caused by excessive exposure to cold" (early 14c.), "chills of intermittent fever" (late 14c.).
Put less technical: shivering, runny nose, etc, are symptoms of both the common cold and being cold.
It seems it's best to think of "cold" and "flu" as totally informal terms with a wide range of possible meanings. I've had Actual Real Influenza twice and both times it knocked me on my ass for a week, lost weight, etc. yet I hear people saying "I have the flu" when they have mild symptoms and only miss a single day of work. Hard to take such a wide range medically seriously.
They could have had influezna with mild symptoms. Two different people can have the same influenza virus enter their body and experience different effects. Anywhere from no symptoms at all to death.
In this case, 77% of participants were in the medical profession and were evaluated between May and June 2020. I suspect they came in contact with SAR COV-2 and didn't even realize it (body fought it off).
What this study is really suggesting is that your body either (a) has an immune response from previous contact (likely due to similarity with regular corona viruses) or (b) lots of people show no symptoms (we know this) and that they obtain an immune response from it.
In either case, the SAR COV-2 is likely far-less dangerous in the sense that more people have it and there are less deaths per infection OR many of us have a natural immune response (more than previously suspected).
It is unclear whether this antibody reactivity may confer clinical benefits, for instance, modulating the severity of a SARS-CoV-2 infection.
Not really. Mortality rate is number of deaths / number of infections.
We roughly know the total number of deaths. We have no idea what the total number of infections has been.
We should continue to make decisions based on the pretend mortality rate and ignore the true one?
Of course we "want to know it."
However the “pretend mortality rate” you refer to is not a thing. It is 1-3% in people who test positive, which correlates pretty strongly with people who have the disease. Think about it this way: the yearly flu in 2018-2019 had a mortality rate of 1.3-48.7% according to the CDC. The denominator in that was 61,000 or so cases. If you found out that 100,000 additional people were exposed to the flu but had no symptoms and by any definition had no flu illness would that change your outlook on whether the flu vaccine or hand washing is worth it?
Or another example: there is surgery which has a mortality rate of 15% due to post surgery infection. Not everybody needs the surgery, only 100 people per year do. Does that mean the rate of mortality here is fake because the denominator should be 7.5 billion? Or should we only count the people who get the disease that necessitates the surgery?
Yes, of course my outlook would change. Not on the binary scale--i wouldn't suddenly think it's not worth it to wash hands-- but I would want to know when deciding on measures.
The mortality rate is a specific figure, it's not whatever figure makes your reaction most appropriate.
If some people get the virus and have no symptoms, that's an incredibly important piece of the puzzle when deciding how to proceed.
Using your exaggerated examples, what if 99% of the population didn't suffer any adverse effects? Wouldn't you reevaluate the current response in light of that?
This study does not tell you that these people had COVID. That's the point: we don't know what this means. All we know, is that we need to study this further.
> The mortality rate is a specific figure, it's not whatever figure makes your reaction most appropriate.
From Wikipedia: "Mortality rate, or death rate, is a measure of the number of deaths (in general, or due to a specific cause) in a particular population, scaled to the size of that population, per unit of time." What is the "particular population" here is in question. I argue that "people who had the SARS-CoV-2 disease" are the relevant population. That is, people who had symptoms or tested positive after an exposure. This study does not change this because it shows no source of the antibodies: if I inject my COVID-19 antibodies into your arm, it does not mean that you had the disease and therefore should not be counted in the mortality rate, does it? How those antibodies got there is a question yet to be answered but the possible answers range from "those people got a mild case and didn't notice" to "those people developed low level antibodies due to incidental contact with COVID-19" without getting the the illness. Their immune system is not trained well enough to fight off a higher viral load."
> Using your exaggerated examples, what if 99% of the population didn't suffer any adverse effects? Wouldn't you reevaluate the current response in light of that?
Yes and no. First, this study does not tell me anything regarding suffering adverse effects. But if a future study did, I think the 3 million people that have died so far would have wanted us to take more precautions, not less, just because we, the living, won the antibody lottery. At the end of the day this is a highly infectious + somewhat deadly disease that adds up to one deadly pandemic. If your point is that only another few million will die if we let it run rampant vs all of humanity, I don't disagree with you but urge you to examine what it means to let millions of people die in this case.
well it possibly changes the calculus of how many people could potentially be a carrier of the virus. if that many people had the disease enough to have some antibodies even with all the extreme measures put into place it is possible this virus is even more contagious than we thought it could be. i don't know and i feel like we won't know because the study of transmission is woefully hard to do. going into this we didn't even know specifically how the flu was transmitted other than hand waving ways(maybe on the surface, maybe aerosols, maybe particles). our research has improved but it's still not great.
So there's the mortality rate for the overall population (what GP is referencing) vs mortality rate among people who've had COVID (what I believe you're referencing). Both are valid and useful in different circumstances: "How likely am I to die if I get COVID" changes as we discover a glut of asymptomatic cases, but "What % of the population will die of this disease?" stays the same
Ref: https://www.merriam-webster.com/dictionary/mortality%20rate
https://www.merriam-webster.com/dictionary/case%20fatality%2...
That doesn’t sound right — you can’t know the population death rate definitely without knowing the infection rate;
If no one gets the disease in your sample population of 100, your death rate says 0. If 1 person is infected and 1 dies, your population death rate says 1%. If 80 are infected, and 10 dies, your population death says 10%.
The “correct” number should be stable, but the population death rate should be changing as the disease spreads, approaching the correct number (but this is also true of liklihood of dying to COVID)
Your population death rate would only be static if your sample population is 100% infected, which is the same as “How likely am I to die if I get COVID”
As another example: lots of people have the tuberculosis infection which lies dormant in their lungs. TB infection is distinct from TB disease which is where you get symptoms. The former is only dangerous in that it can develop into the latter. The latter can kill you. How should you look at these numbers? Is it worthwhile to drop the number of people with TB disease and just divide deaths by TB infections or is it more informative to derive mortality as deaths / TB diseases while also using TB infections and the conversion rate from those to TB disease to calculate risk and transmissibility? I argue the latter is much more relevant to decision making.
Strikes me as similar to those who predict x% returns on their s&p index funds based on past stock market performance.
The future is always unknown.
https://onlinelibrary.wiley.com/doi/10.1111/eci.13554
We know deaths / symptomatic infections really well due to the large numbers involved.
I understand that without symptoms like coughing or sneezing, the vector for spreading would be relatively limited, but I have to imagine it's still possible (even commonplace) for healthy individuals to effectively spread bacteria/viruses (even harmless ones).
If it is possible, what are the chances of that happening unintentionally? Would it be ethical to engineer a vaccine to intentionally do that?
I'm not trying to imply that's what's happening now - but I am curious.
Artificially creating such a thing has been discussed, but I don't think anyone's ready to go there for ethical reasons. What if they screw it up?
Also, you still need _some_ symptoms to get people to sneeze the "vaccine" to their neighbors. It's a very fine line to tread.
It will also be more challenging going forward to do these kinds of studies because of the ethics. It will be hard to ethically justify keeping an arm of a trial unvaccinated as a placebo in the face of a very serious and very deadly virus which we have known good vaccines. There are some interesting things like crossover trials that apparently more of the current in research vaccines are trying.
The mRNA COVID vaccines are not; with those, the vaccine material is mRNA that your body codes into a protein recognizable to the immune system. The mRNA is both unstable (so it doesn't last long inside the body) and not capable of contagious transmission
There is open research, such as https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777272/, as to whether making intentionally transmissible vaccines is feasible (or even a good idea)
If a vaccine used a virus that was both live and contagious but somehow safe, its not impossible; of course, there’d also be a risk of it mutating to become unsafe.
The actual vaccines for protection against COVID-19 that I know of don’t use a delivery mechanism where that is possible; that’s certainly not something, e.g., a mRNA vaccine could do.
If you are exposed to 1000 versus 100,000, does one lead to an infection while the other indices some exposure response?
The thing the study establishes is that most adults have antibodies that will react to some parts of the pandemic virus. And then that's it. They didn't establish whether it was protective or not or anything like that.
https://swprs.org/wp-content/uploads/2020/10/sweden-monthly-...
This is just the first one that has hit at a time when it was politically and technically possible to shut down whole societies in fear of them.
Edit: Also, looking at overall deaths per million is not anything like comparing actual mortality rates of those infected. The baseline mortality in 1918 was already way higher and the pandemic amplified that, despite actually being less deadly than COVID-19 at an individual level. So I'd argue that the response to this pandemic was more than merited and was appropriate to the nature of the virus itself. It was not just another "asian flu."
https://www.statista.com/statistics/525353/sweden-number-of-...
It would seem unlikely that the population would notice a 6% increase against the base annual death rate. We previously tolerated hospital overcrowding and death spikes from influenza waves.
Most other countries around the world are showing a 4-6% increase. There seems to be a correlation to severity of lockdown and increased number of deaths, presumably due to factors like interruptions to regular medical treatments, and individual health deteriorating during lockdown.
Aka everybody gets it very fast and in a short time period, hospitals are easily overwhelmed and lead to even more deaths.
More interestingly, there was a dip in 2019, so 2020 was expected to be a bit high even before the pandemic.
This number seems low. I think the title is poorly worded, to me it concludes more of that healthcare workers in Canada developed antibodies before being diagnosed with COVID-19
Show us the proof I'm waiting...
Although I don't usually seek out this topic in this community, I find these discussions here helpful from time to time.
> Now, you can still make an argument that the T cell component of immunity might provide some protection after a previous coronavirus infection. The current study didn’t address this directly, but after these results, it’s at least less likely that that’s happening. The authors make a note of this, and also note that pre-existing mucosal antibodies might exert a protective effect (which this study didn’t examine, either). But prior circulating human coronavirus antibodies, even ones that can bind to the current one – those it looks like we can rule out. Which is too bad.
From: https://blogs.sciencemag.org/pipeline/archives/2021/02/10/do...
The title study here is nothing new, we know there's cross reactive antibodies to other coronaviruses, they're not neutralizing, the hospitalization/death rates are the same so they don't confer any protection.
Nobody had any pre-existing immunity to this virus before it erupted last year (and no, the virus or variants of it were not traveling the globe months or years earlier).