Keep in mind that "herd immunity" isn't really immunity, it's the point at which Rt (the average number of people each infected person passes the infection on to) drops below 1.0 and the spread shrinks instead of growing. Rt is dependent on how people behave. When behavior changes, Rt can change as well. Each herd immunity level is thus dependent on health measures, which is why "reaching" herd immunity and then loosening up health measures won't work.
Edit: removed wrong information on R0 that's not really essential to my point
R0 is not a constant inherent to a virus strain. It's a contextual number, determined by population and behavior, population immunity and other factors.
Rt is simply notation of an estimate of R0 at a particular time.
Either way, you're correct that "herd immunity", as used here, means the point at which time the infection rate begins to decline, and this is conditional on population behaviors. If people mix more freely, the estimate changes.
However, the observation that people don't mix uniformly still applies, even if they mix a bit more than they do now. To put it in a CS context, it's like debating the magnitude of the constant, when the algorithm has a fundamentally different asymptotic behavior.
> Each herd immunity level is thus dependent on health measures, which is why "reaching" herd immunity and then loosening up health measures won't work.
I appreciate this paper because I feel like every single article about "herd immunity" completely misses the mark and makes some rather poor assumptions. These assumptions are likely made because they make COVID seem like a bigger deal which sells more papers and gets more clicks.
When an article discussing herd immunity assumes a completely homogeneous population I just shake my head and wonder how in the world this article got published.
Whatever happened to large-scale antibody testing? You'd think that someone would be testing a few thousand random people each week to see how many people have been infected to date. That sort of thing was being done in the US back in April.[1][2] But it seems to have stopped.
If you're going to talk about "herd immunity", you need that info to get anywhere.
The antibody tests seemed to be consistently underestimating other measures of Covid-19 immunity, even conservative ones, so they're not considered as useful as we thought in April or May.
It's possible the tests aren't sensitive enough, or immunity is largely based on T-cells (more expensive to test for) rather than antibodies [0], or antibodies for other coronaviruses confer some level of immunity, or something else we still don't understand.
TLDR: "During the first wave of the COVID-19 pandemic, fewer than 10% of the US adult population formed antibodies against SARS-CoV-2, and fewer than 10% of those with antibodies were diagnosed."
Unfortunately, even antibody testing is unreliable now because of waning antibodies.
(One might object and say that if someone has little to no levels of antibodies they must not be immune anymore, but immunity is complex and not solely determined by antibodies)
These models are fundamentally flawed in that they assume immunity or susceptibility are binary conditions. Based on recent research it appears a significant fraction of the population has at least limited immunity from prior exposure to other coronaviruses. They can still get infected but the immune system clears it more quickly and they tend to suffer fewer symptoms compared to immunologically naive patients.
Every model is wrong, some models are useful. Does this flaw make this model useless? On the flip side is it a useful approximation even if it's not completely accurate?
Well 20% of NYC had COVID and we are currently seeing outbreaks in communities that have relaxed social distancing measures, so it seems obvious that her calculations are incorrect.
I really struggle reading academic studies still...
"Heterogeneity in contact structure and individual variation in infectivity, susceptibility, and resistance are key factors that reduce the disease-induced herd immunity levels to 34.2-47.5% in our models."
I THINK that means, in addition to how infectious COVID is, and how susceptible and resistant people are in general, one of the other things that impact herd immunity is "contact structure" and it tends to be sort of limited. There seems to be plenty of "Heterogeneity in contact structure" studies done on many other things out there, so it looks like this is something that's already understood. If I understand it correctly, it means that most people have limited contacts, and while we all might be "6 degrees" from everyone else, we're not directly contacting all those people, and so that could help with herd immunity. So that maybe reduces the number from 74% to this 34-47% number, which better.
Does that mean "Heterogeneity in contact structure" is different for people based on things like how often we go out, where we go, how we travel and where we live? e.g. a subway/bus trip in Manhattan, NY is different than driving alone in Manhattan, KS.
Yeah, that's what it's referring to. People with more points of contact are both more likely to catch the virus and have a larger impact on herd immunity once they're immune.
Tests this year on blood from people who had SARS in 2003, indicated that 17 years later they still had T-cell responses . On the other hand, coronaviruses which are experienced as "colds" apparently have a lot less retention of immune system recognition. Optimistic scenario is that the immune system is "smart" enough to recognize which infections are a big deal which must be remembered forever, and which are not. Pessimistic scenario is we got lucky with SARS, and may not with Covid-19.
Immunity isn't a binary condition which lasts for a certain length of time and then stops. It exists on a spectrum. The best evidence we have indicates that most recovered patients will retain a significant level of immunity for at least several years.
So, according to this paper 34.2-47.5% of US citizens need immunity before the pandemic can be declared over? So best case scenario we can achieve herd immunity with roughly 100M infections/recovered. USA is currently at ~8M infections/recovered, so that means we are roughly 8% of the way to herd immunity (best case).
At the current rate of +50K infections per day, that's 20 days per 1M infections, so we need 20 days * 92 = 5 years before we achieve herd immunity (best case, assuming no vaccines)? That doesn't seem right.
Well, we could get to 2MM faster if we opened everything up for the less-vulnerable populations (i.e. everyone under 50 without obesity or heart conditions) for whom the survival rate is above 99.99%. You might then be looking at 500k a day rather than 50k.
CONFIRMED cases. The total number of cases is probably 5-10x that.
I live in the Deep South, and honestly I suspect that our curves have fallen simply due to a "limited" herd immunity effect (i.e. the groups of people most likely to catch COVID have already done so in large enough numbers). I certainly haven't observed any significant change in behaviors since the July peak, yet the numbers are falling like a rock regardless.
This also assumes that acquired immunity from an infection is complete and permanent. Immunity to other coronaviruses decays over a year or two -- meaning that before the five years are up in your scenario, there would be a significant cohort of prior victims open to reinfection.
No, we are undercounting the number of people who have it (asymptomatic or not) by a huge factor. at one point it was by a factor of 10, but I doubt that is still the case.
This is why I watch florida like an eagle, because if it stops going up there we know we got a very good estimate to know when the top is.
~2.5-3% (730k/21.5m) of Florida has had it and it's slowed dramatically (use to be like 16k/day now down to 3). It feels reasonable that herd immunity starts slowing down the virus pretty fast somewhere around 25-30%. It seems reasonable it may come to a complete halt by 47%.
This is fag packet math, so I'll spare any exact figures.
But if the second wave data for the UK is anything to go by, confirmed cases vs actual cases was at _least_ 5x for the first wave.
There obivously are other factors, but with increased testing that multiplier only climbs, bringing herd immunity numbers actually within reasonable grasp.
I strongly suspect there have been similar effects in the US.
> At the current rate of +50K infections per day, that's 20 days per 1M infections, so we need 20 days * 92 = 5 years before we achieve herd immunity (best case, assuming no vaccines)? That doesn't seem right.
I can't remember exactly where I heard it, but I believe robust herd immunity in human populations has never been achieved for a virus like this without the widespread use of a vaccine. Which makes sense, because there's evolutionary pressure on viruses to adapt, and so many diseases remained endemic and common until vaccines where introduced for them.
Edit: in response to the dead reply: the Spanish Flu didn't disappear. It killed tens of millions (out of a much smaller world population) and persisted for decades as a seasonal flu. IIRC, it didn't get eclipsed by other strains until the 50s.
I wonder if this also means that only 35% of us need a vaccination to declare it over. I had previously read 60-70% were needed and that 35% of Americans get a flu shot. That depressed me.
EDIT: seriously, downvoting this comment? Can't imagine why and would like to know.
The implication here is that having "tested positive" is equivalent to having an "infection". An infection, by definition, is an alteration of the biological state of the entity with observable side-effects (symptoms). It is patently false to assert that "testing positive" for this virus is 100% indicative of an "infection".
Further, "100M infections/recovered" implies that this infection can lead to "recovered" implying that the other alternative to recovere is a terminal/chronic condition. I guess this makes sense if we agree that many millions of "infected" immediately "recover" after testing positive, given that a substantial subset of those who "test positive" are "asymptomatic", reasonably understood as not-ill, not-sick, not-infected. Thus insta "recovery".
My overall point here is that the permitted vocabulary of speaking and reasoning about this phenomena is inexplicably illiterate. Whether this permitted simplistic vocabulary of discourse is by design or a symptomatic of the state of humanity, the inevitable consequence is a degradation of analysis and sub-optimal solutions.
[+] [-] jupp0r|5 years ago|reply
Edit: removed wrong information on R0 that's not really essential to my point
[+] [-] oopsiforgot7|5 years ago|reply
[+] [-] jacquesm|5 years ago|reply
I think you just devalued your argument.
https://wwwnc.cdc.gov/eid/article/25/1/17-1901_article
[+] [-] timr|5 years ago|reply
Rt is simply notation of an estimate of R0 at a particular time.
Either way, you're correct that "herd immunity", as used here, means the point at which time the infection rate begins to decline, and this is conditional on population behaviors. If people mix more freely, the estimate changes.
However, the observation that people don't mix uniformly still applies, even if they mix a bit more than they do now. To put it in a CS context, it's like debating the magnitude of the constant, when the algorithm has a fundamentally different asymptotic behavior.
[+] [-] ignoramous|5 years ago|reply
Yep. Here's a very approachable and well written paper on the topic: https://academic.oup.com/cid/article/52/7/911/299077
And my comment on it from 6 months ago: https://news.ycombinator.com/item?id=22818413
[+] [-] just-juan-post|5 years ago|reply
This seems like something you made up. Can you cite your source?
How exactly does your rule apply to non-humans? What "health measures" do packs of wild horses take when disease comes to the herd?
[+] [-] zests|5 years ago|reply
When an article discussing herd immunity assumes a completely homogeneous population I just shake my head and wonder how in the world this article got published.
[+] [-] Animats|5 years ago|reply
If you're going to talk about "herd immunity", you need that info to get anywhere.
[1] https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v...
[2] https://abc7ny.com/coronavirus-testing-antibody-new-york-ny/...
[+] [-] dmurray|5 years ago|reply
It's possible the tests aren't sensitive enough, or immunity is largely based on T-cells (more expensive to test for) rather than antibodies [0], or antibodies for other coronaviruses confer some level of immunity, or something else we still don't understand.
[0] https://www.eurekalert.org/pub_releases/2020-08/cp-mcc081720...
[+] [-] saalweachter|5 years ago|reply
TLDR: "During the first wave of the COVID-19 pandemic, fewer than 10% of the US adult population formed antibodies against SARS-CoV-2, and fewer than 10% of those with antibodies were diagnosed."
[+] [-] argonaut|5 years ago|reply
(One might object and say that if someone has little to no levels of antibodies they must not be immune anymore, but immunity is complex and not solely determined by antibodies)
[+] [-] unknown|5 years ago|reply
[deleted]
[+] [-] nradov|5 years ago|reply
https://www.jci.org/articles/view/143380
https://pubmed.ncbi.nlm.nih.gov/32978311/
[+] [-] gpm|5 years ago|reply
[+] [-] vannevar|5 years ago|reply
"Heterogeneity in contact structure and individual variation in infectivity, susceptibility, and resistance are key factors..." (emphasis added)
[+] [-] timr|5 years ago|reply
https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v...
https://www.medrxiv.org/content/10.1101/2020.07.23.20160762v...
https://www.medrxiv.org/content/10.1101/2020.09.26.20202267v...
[+] [-] xadhominemx|5 years ago|reply
[+] [-] blakesterz|5 years ago|reply
"Heterogeneity in contact structure and individual variation in infectivity, susceptibility, and resistance are key factors that reduce the disease-induced herd immunity levels to 34.2-47.5% in our models."
I THINK that means, in addition to how infectious COVID is, and how susceptible and resistant people are in general, one of the other things that impact herd immunity is "contact structure" and it tends to be sort of limited. There seems to be plenty of "Heterogeneity in contact structure" studies done on many other things out there, so it looks like this is something that's already understood. If I understand it correctly, it means that most people have limited contacts, and while we all might be "6 degrees" from everyone else, we're not directly contacting all those people, and so that could help with herd immunity. So that maybe reduces the number from 74% to this 34-47% number, which better.
Does that mean "Heterogeneity in contact structure" is different for people based on things like how often we go out, where we go, how we travel and where we live? e.g. a subway/bus trip in Manhattan, NY is different than driving alone in Manhattan, KS.
[+] [-] SpicyLemonZest|5 years ago|reply
[+] [-] streptomycin|5 years ago|reply
[+] [-] rossdavidh|5 years ago|reply
[+] [-] nradov|5 years ago|reply
https://www.jimmunol.org/content/early/2020/09/03/jimmunol.2...
[+] [-] umvi|5 years ago|reply
At the current rate of +50K infections per day, that's 20 days per 1M infections, so we need 20 days * 92 = 5 years before we achieve herd immunity (best case, assuming no vaccines)? That doesn't seem right.
[+] [-] hammock|5 years ago|reply
[+] [-] zwischenzug|5 years ago|reply
[+] [-] StevePerkins|5 years ago|reply
CONFIRMED cases. The total number of cases is probably 5-10x that.
I live in the Deep South, and honestly I suspect that our curves have fallen simply due to a "limited" herd immunity effect (i.e. the groups of people most likely to catch COVID have already done so in large enough numbers). I certainly haven't observed any significant change in behaviors since the July peak, yet the numbers are falling like a rock regardless.
[+] [-] mchusma|5 years ago|reply
https://covid19-projections.com/ (Excellent source during these times. Sad to see them deciding to stop moving forward but it's good for now).
[+] [-] rst|5 years ago|reply
See, e.g., https://www.nature.com/articles/s41591-020-1083-1
[+] [-] autokad|5 years ago|reply
This is why I watch florida like an eagle, because if it stops going up there we know we got a very good estimate to know when the top is.
~2.5-3% (730k/21.5m) of Florida has had it and it's slowed dramatically (use to be like 16k/day now down to 3). It feels reasonable that herd immunity starts slowing down the virus pretty fast somewhere around 25-30%. It seems reasonable it may come to a complete halt by 47%.
[+] [-] unknown|5 years ago|reply
[deleted]
[+] [-] gpm|5 years ago|reply
[+] [-] jackpeterfletch|5 years ago|reply
But if the second wave data for the UK is anything to go by, confirmed cases vs actual cases was at _least_ 5x for the first wave.
There obivously are other factors, but with increased testing that multiplier only climbs, bringing herd immunity numbers actually within reasonable grasp.
I strongly suspect there have been similar effects in the US.
[+] [-] ardy42|5 years ago|reply
I can't remember exactly where I heard it, but I believe robust herd immunity in human populations has never been achieved for a virus like this without the widespread use of a vaccine. Which makes sense, because there's evolutionary pressure on viruses to adapt, and so many diseases remained endemic and common until vaccines where introduced for them.
Edit: in response to the dead reply: the Spanish Flu didn't disappear. It killed tens of millions (out of a much smaller world population) and persisted for decades as a seasonal flu. IIRC, it didn't get eclipsed by other strains until the 50s.
[+] [-] e40|5 years ago|reply
EDIT: seriously, downvoting this comment? Can't imagine why and would like to know.
[+] [-] eternalban|5 years ago|reply
This is a false binary state space.
The implication here is that having "tested positive" is equivalent to having an "infection". An infection, by definition, is an alteration of the biological state of the entity with observable side-effects (symptoms). It is patently false to assert that "testing positive" for this virus is 100% indicative of an "infection".
Further, "100M infections/recovered" implies that this infection can lead to "recovered" implying that the other alternative to recovere is a terminal/chronic condition. I guess this makes sense if we agree that many millions of "infected" immediately "recover" after testing positive, given that a substantial subset of those who "test positive" are "asymptomatic", reasonably understood as not-ill, not-sick, not-infected. Thus insta "recovery".
My overall point here is that the permitted vocabulary of speaking and reasoning about this phenomena is inexplicably illiterate. Whether this permitted simplistic vocabulary of discourse is by design or a symptomatic of the state of humanity, the inevitable consequence is a degradation of analysis and sub-optimal solutions.
[+] [-] wodenokoto|5 years ago|reply
Is it:
- everybody will eventually, but much later, get covid and become immune?
- Keep the infected number low until a vaccine is developed?
- Something else?