Coronavirus

[KCLarkin]

Twitter thread on why “wild” herd immunity is achieved at much lower % than vaccination

 

 

I found this argument interesting--thanks Cherzeca.

 

Here is why yinonw's thread is a scam:

 

HIT = 1 - 1/Ro

 

But yinonw invented a new thing. I will call it "wild" Herd Immunity. This is the observed level of herd immunity, given current Non-Pharmaceutical Interventions (NPI), seasonality, etc.

 

HITw = 1 -1/Rw

 

Earlier in this thread, I posted that Florida's recent surge was the result of a relatively modest Rw ~ 1.3.

 

So, for Florida:

HITw = 1 - 1/1.3 = 23%

 

So, if Florida maintains "reopening levels" of NPI the epidemic would start to die out once ~23% of the population is infected. (Florida has has added more NPI since, so HITw should be lower).

 

--

But then yinonw pulls his sleight of hand: He claims that Sweden has very modest Covid restrictions, so Rw ~ Ro. Therefore, HITw = HIT. And because HITw in Sweden is similar to other countries, he assumes that HITw = HIT in other countries too. And then he claims this means that masks, lockdowns, school closures, etc have no impact on HITw.

 

This entire chain of assumptions is B.S. But it all starts with the flawed assumption that Sweden has no NPI. This is absolutely false.

https://www.krisinformation.se/en/hazards-and-risks/disasters-and-incidents/2020/official-information-on-the-new-coronavirus/restriktioner-och-forbud

https://www.gstatic.com/covid19/mobility/2020-08-11_SE_Mobility_Report_en.pdf

 

According to Google Mobility trends, traffic to "workplaces" in Stockholm is down 50%!

 

And, it seems like Sweden's schools are closed for the summer holidays since June:

https://publicholidays.se/school-holidays/stockholm/

 

 

 

[LC]

 

-On the 'real' excess mortality from Covid

https://www.ft.com/content/a2901ce8-5eb7-4633-b89c-cbdf5b386938

https://www.ft.com/content/6bd88b7d-3386-4543-b2e9-0d5c6fac846c

Both links offer good quality data concerning international comparisons and the relative marginal differences in timing and extent of "government stringency measures".

Although there are factors that point to under-reporting of deaths. Evidence suggests that, at least so far, on a net basis, excess mortality from Covid has been somewhat under-reported.

 

Upon quick glance this looks interesting and requires some time to review. Thanks for posting.

[KCLarkin]

@cigar. Report dated 6/30. Twitter thread more recent data.

 

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June.

 

But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

[Read the Footnotes]

But then yinonw pulls his sleight of hand: He claims that Sweden has very modest Covid restrictions, so Rw ~ Ro. Therefore, HITw = HIT. And because HITw in Sweden is similar to other countries, he assumes that HITw = HIT in other countries too. And then he claims this means that masks, lockdowns, school closures, etc have no impact on HITw.

 

This entire chain of assumptions is B.S. But it all starts with the flawed assumption that Sweden has no NPI. This is absolutely false.

https://www.krisinformation.se/en/hazards-and-risks/disasters-and-incidents/2020/official-information-on-the-new-coronavirus/restriktioner-och-forbud

https://www.gstatic.com/covid19/mobility/2020-08-11_SE_Mobility_Report_en.pdf

Nice job building on some of my previous arguments, while expressing yourself more clearly and concisely, plus adding to them with other well expressed arguments.

 

I'd like to mention a closely related odd tactic he uses when he says that the only thing NYS and Stockholm have in common is wild herd immunity and that must be driving down the mortality. There are several things wrong with that argument. I'll list two below.

 

First, I can create an exceedingly long list of silly things that NYS and Stockholm have in common, but here are a few that aren't silly:

- I bet a lot more people in both places know someone who got sick and it scared the crap out of them and they changed behavior

- I bet a lot more people in both places know someone who died and that is changing behavior. I have seen estimates that in the USA on average eight people are grieving for each individual death from COVID-19. To be honest I have know idea what exactly that means, but I have a feeling it means that a lot more people are grieving than dying and those people probably don't think it's a hoax even if they did at one point.

- Most importantly, standard of care has radically improved and that is driving down mortality independently of in the rate of infection.

 

Second, herd immunity isn't a measure of the potential for deaths but of the potential for infections to spread, therefore we want to track new infections not mortality. So why is he using mortality as his primary metric when there are so many issues Mortality is a lagging indicator with a rather long lag period relative to the length to date of this Pandemic even now. Plus there is the problem that we would expect that mortality will decrease due to improvements in standard of care which has happened. You can even go back to my posts from March where I encouraged everyone to take this seriously for the first couple of months because anyone who got sick in the first couple of months would likely get pretty terrible care compared to what would be available later, and unfortunately that was true to an embarrassing extent.

 

You could argue he uses mortality because he says wild herd immunity is to some extent about how ill people become once infected, but people who don't get very sick can still be infectious and infectiousness is what determines herd immunity so this all just seems silly at this point, and I think we would be better served by discussing higher quality sources of information.

[StubbleJumper]

@cigar. Report dated 6/30. Twitter thread more recent data.

 

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June.

 

But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

 

 

There is no problem with the Ontario analysis due to recency or lack of recency.  Essentially, what the data show is that about 0.4% of Toronto residents were officially diagnosed as being infected with covid up to June 30, but about 1.5% of people in Toronto who submitted a blood sample to the health system showed the presence of antibodies.  On the face of it, the ratio between people carrying antibodies and those officially diagnosed is a bit low compared to other seroprevalence studies (ie, ~3.75:1), but on the other hand people who are young and healthy do not generally submit blood samples to health care system, so it is quite possible that the blood samples were biased to those who had existing co-morbidities and who were quite rightly taking their own social-distancing measures to avoid the virus.

 

 

SJ

 

[Cigarbutt]

@cigar. Report dated 6/30. Twitter thread more recent data.

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June.

But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

There is no problem with the Ontario analysis due to recency or lack of recency.  Essentially, what the data show is that about 0.4% of Toronto residents were officially diagnosed as being infected with covid up to June 30, but about 1.5% of people in Toronto who submitted a blood sample to the health system showed the presence of antibodies.  On the face of it, the ratio between people carrying antibodies and those officially diagnosed is a bit low compared to other seroprevalence studies (ie, ~3.75:1), but on the other hand people who are young and healthy do not generally submit blood samples to health care system, so it is quite possible that the blood samples were biased to those who had existing co-morbidities and who were quite rightly taking their own social-distancing measures to avoid the virus.

SJ

Yes, since June 30th, in Ontario, standard measures such as daily new cases per million population have remained very low (even lower than British Columbia) and the positivity rate has stayed below 1% and has been declining. There is no evidence that community spread has continued to any significant degree, enough to materially alter the conclusions that could be obtained from using antibody levels during the study period, as an input.

To be clear, the methodology used by the Ontario public health is not perfect but is quite robust: "Specimens tested to generate seroprevalence estimates were originally submitted to PHO Laboratory for clinical testing for antibodies to a variety of infectious diseases (but not COVID-19)". They had to make some adjustments for various reasons but their method is quite dependable.

[clutch]

No matter how well the government responds, if the people act stupidly, this virus will spread like a wildfire.

 

"South Korea church coronavirus cluster causes alarm"

 

https://www.bbc.com/news/world-asia-53803011

[StubbleJumper]

@cigar. Report dated 6/30. Twitter thread more recent data.

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June.

But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

There is no problem with the Ontario analysis due to recency or lack of recency.  Essentially, what the data show is that about 0.4% of Toronto residents were officially diagnosed as being infected with covid up to June 30, but about 1.5% of people in Toronto who submitted a blood sample to the health system showed the presence of antibodies.  On the face of it, the ratio between people carrying antibodies and those officially diagnosed is a bit low compared to other seroprevalence studies (ie, ~3.75:1), but on the other hand people who are young and healthy do not generally submit blood samples to health care system, so it is quite possible that the blood samples were biased to those who had existing co-morbidities and who were quite rightly taking their own social-distancing measures to avoid the virus.

SJ

Yes, since June 30th, in Ontario, standard measures such as daily new cases per million population have remained very low (even lower than British Columbia) and the positivity rate has stayed below 1% and has been declining. There is no evidence that community spread has continued to any significant degree, enough to materially alter the conclusions that could be obtained from using antibody levels during the study period, as an input.

To be clear, the methodology used by the Ontario public health is not perfect but is quite robust: "Specimens tested to generate seroprevalence estimates were originally submitted to PHO Laboratory for clinical testing for antibodies to a variety of infectious diseases (but not COVID-19)". They had to make some adjustments for various reasons but their method is quite dependable.

 

No, things have been quite impressive in Ontario, but that is largely due to the Draconian measures that were put in place by governments during the lockdown (some aspects were more severe than in Quebec, some less). 

 

Now, you are a medical practitioner, so you can tell us.  How many perfectly healthy people are asked to provide blood samples?  How many diabetics are asked to provide blood samples?  How many people with coronary difficulties are asked to provide blood samples? It is a physician-selected group of people who *already* have interactions with the health care system, which generally would exclude the healthy population under age 50 and would particularly exclude the healthy population under age 40.  Ontario does not need to apologize for using existing samples of blood, but let us not pretend that it was in any way random (remember the non-random sample of Manhattan denizens who were tested when they went out for groceries?).  These were probably sicker than average people.

 

So is this better or worse than using blood donors?  The blood donors are probably healthier than average people.  But, let us not pretend that they are random either.  In any case, the recency or non-recency of the sample is not particularly problematic.  The seroprevalence work in Ontario is directionally consistent with that done for other populations, but I remain hesitant to accept the magnitude.

 

 

SJ

[Cigarbutt]

@cigar. Report dated 6/30. Twitter thread more recent data.

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June.

But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

There is no problem with the Ontario analysis due to recency or lack of recency.  Essentially, what the data show is that about 0.4% of Toronto residents were officially diagnosed as being infected with covid up to June 30, but about 1.5% of people in Toronto who submitted a blood sample to the health system showed the presence of antibodies.  On the face of it, the ratio between people carrying antibodies and those officially diagnosed is a bit low compared to other seroprevalence studies (ie, ~3.75:1), but on the other hand people who are young and healthy do not generally submit blood samples to health care system, so it is quite possible that the blood samples were biased to those who had existing co-morbidities and who were quite rightly taking their own social-distancing measures to avoid the virus.

SJ

Yes, since June 30th, in Ontario, standard measures such as daily new cases per million population have remained very low (even lower than British Columbia) and the positivity rate has stayed below 1% and has been declining. There is no evidence that community spread has continued to any significant degree, enough to materially alter the conclusions that could be obtained from using antibody levels during the study period, as an input.

To be clear, the methodology used by the Ontario public health is not perfect but is quite robust: "Specimens tested to generate seroprevalence estimates were originally submitted to PHO Laboratory for clinical testing for antibodies to a variety of infectious diseases (but not COVID-19)". They had to make some adjustments for various reasons but their method is quite dependable.

No, things have been quite impressive in Ontario, but that is largely due to the Draconian measures that were put in place by governments during the lockdown (some aspects were more severe than in Quebec, some less). 

Now, you are a medical practitioner, so you can tell us.  How many perfectly healthy people are asked to provide blood samples?  How many diabetics are asked to provide blood samples?  How many people with coronary difficulties are asked to provide blood samples? It is a physician-selected group of people who *already* have interactions with the health care system, which generally would exclude the healthy population under age 50 and would particularly exclude the healthy population under age 40.  Ontario does not need to apologize for using existing samples of blood, but let us not pretend that it was in any way random (remember the non-random sample of Manhattan denizens who were tested when they went out for groceries?).  These were probably sicker than average people.

So is this better or worse than using blood donors?  The blood donors are probably healthier than average people.  But, let us not pretend that they are random either.  In any case, the recency or non-recency of the sample is not particularly problematic.  The seroprevalence work in Ontario is directionally consistent with that done for other populations, but I remain hesitant to accept the magnitude.

SJ

From old and recent knowledge, i gather that the methods of these serosurveillance investigations done at the population level will depend on what you want to achieve and compromises have to be made between the 'investment' required and the precision and generalization of findings. You need to decide if the study will be cross-sectional (performed once) or longitudinal (follow-up). You also need to decide how to sample the population. The Ontario method used above and blood donors (convenience sampling) are not truly random but are relatively simple to design, to do and to analyze compared to fancy random selection of different population stratas. Blood donors tend to participate well but tend to be different from the general population (often healthier and other factors). The Ontario study design is interesting because it likely represents fairly well the general population. Random sampling is more complicated, more expensive and takes longer to perform so there is a price to pay for precision that may not be critical for population level measures that may be helpful during the acute decision making process. Also, people that get randomly sampled have to consent to the lab test etc and this is a source of efficiency and statistical problems. There is a more complex project going on:

https://abcstudy.ca/about/

The seroconversion data at large has been a bit of a cold shower if the hope was to rapidly get to herd immunity (whichever form or definition that you adhere to)

i would like to hear from cherzeca, yourself or others about how a such a low seroprevalence in Ontario (or Toronto) could be reconciled with herd immunity under any circumstances going forward.

Hope this helps in your thought process.

[StubbleJumper]

@cigar. Report dated 6/30. Twitter thread more recent data.

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June.

But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

There is no problem with the Ontario analysis due to recency or lack of recency.  Essentially, what the data show is that about 0.4% of Toronto residents were officially diagnosed as being infected with covid up to June 30, but about 1.5% of people in Toronto who submitted a blood sample to the health system showed the presence of antibodies.  On the face of it, the ratio between people carrying antibodies and those officially diagnosed is a bit low compared to other seroprevalence studies (ie, ~3.75:1), but on the other hand people who are young and healthy do not generally submit blood samples to health care system, so it is quite possible that the blood samples were biased to those who had existing co-morbidities and who were quite rightly taking their own social-distancing measures to avoid the virus.

SJ

Yes, since June 30th, in Ontario, standard measures such as daily new cases per million population have remained very low (even lower than British Columbia) and the positivity rate has stayed below 1% and has been declining. There is no evidence that community spread has continued to any significant degree, enough to materially alter the conclusions that could be obtained from using antibody levels during the study period, as an input.

To be clear, the methodology used by the Ontario public health is not perfect but is quite robust: "Specimens tested to generate seroprevalence estimates were originally submitted to PHO Laboratory for clinical testing for antibodies to a variety of infectious diseases (but not COVID-19)". They had to make some adjustments for various reasons but their method is quite dependable.

No, things have been quite impressive in Ontario, but that is largely due to the Draconian measures that were put in place by governments during the lockdown (some aspects were more severe than in Quebec, some less). 

Now, you are a medical practitioner, so you can tell us.  How many perfectly healthy people are asked to provide blood samples?  How many diabetics are asked to provide blood samples?  How many people with coronary difficulties are asked to provide blood samples? It is a physician-selected group of people who *already* have interactions with the health care system, which generally would exclude the healthy population under age 50 and would particularly exclude the healthy population under age 40.  Ontario does not need to apologize for using existing samples of blood, but let us not pretend that it was in any way random (remember the non-random sample of Manhattan denizens who were tested when they went out for groceries?).  These were probably sicker than average people.

So is this better or worse than using blood donors?  The blood donors are probably healthier than average people.  But, let us not pretend that they are random either.  In any case, the recency or non-recency of the sample is not particularly problematic.  The seroprevalence work in Ontario is directionally consistent with that done for other populations, but I remain hesitant to accept the magnitude.

SJ

From old and recent knowledge, i gather that the methods of these serosurveillance investigations done at the population level will depend on what you want to achieve and compromises have to be made between the 'investment' required and the precision and generalization of findings. You need to decide if the study will be cross-sectional (performed once) or longitudinal (follow-up). You also need to decide how to sample the population. The Ontario method used above and blood donors (convenience sampling) are not truly random but are relatively simple to design, to do and to analyze compared to fancy random selection of different population stratas. Blood donors tend to participate well but tend to be different from the general population (often healthier and other factors). The Ontario study design is interesting because it likely represents fairly well the general population. Random sampling is more complicated, more expensive and takes longer to perform so there is a price to pay for precision that may not be critical for population level measures that may be helpful during the acute decision making process. Also, people that get randomly sampled have to consent to the lab test etc and this is a source of efficiency and statistical problems. There is a more complex project going on:

https://abcstudy.ca/about/

The seroconversion data at large has been a bit of a cold shower if the hope was to rapidly get to herd immunity (whichever form or definition that you adhere to)

i would like to hear from cherzeca, yourself or others about how a such a low seroprevalence in Ontario (or Toronto) could be reconciled with herd immunity under any circumstances going forward.

Hope this helps in your thought process.

 

 

Well, if you truly believe the Toronto seroprevalence work, it cannot be reconciled with impending herd immunity in any realistic manner.  If you are in the camp that there are only 1.5% of Torontonians who have antibodies, then it's a hell of a long haul to have this virus peter out *irrespective* of whether you think that a 15%-20% presence of antibodies will do the job, or whether you are in the traditional camp that holds the view that ~60% of the population with antibodies would be required.  In the end, you need to question whether the methodology of Ontario's seroprevalence work results in a fair representation of the actual path of covid in the province, or whether the many other studies scattered amongst a wide variety of other jurisdictions are more representative of reality. 

 

If you believe the results, what it does suggest is that Ontario, despite having already had a catastrophic outbreak in its retirement homes might still be very susceptible to a second wave of covid (see what is currently happening in Spain, France, Belgium and the Netherlands).  On that, I can offer the opinion that there will be much less willingness for a vigourous lockdown in a potential second wave than there was in the first.  Like what is happening in Europe right now, there will likely be a much greater tolerance to the presence and spread of covid than what there was in April.  It calls into question the wisdom and sustainability of a great many of the measures that governments imposed in March/April.

 

Even in the "best" of cases where you would optimistically hold the view that there is a 15:1 ratio between people who hold immunity and officially diagnosed cases, Toronto would currently only be at 7.5% of the population with antibodies, right?  If you think 15%-20% is required, there still remains much misery to occur, and if you are in the camp that 60% is required there might be years of misery in Toronto's future.

 

 

SJ

[Cigarbutt]

...

Well, if you truly believe the Toronto seroprevalence work, it cannot be reconciled with impending herd immunity in any realistic manner.  If you are in the camp that there are only 1.5% of Torontonians who have antibodies, then it's a hell of a long haul to have this virus peter out *irrespective* of whether you think that a 15%-20% presence of antibodies will do the job, or whether you are in the traditional camp that holds the view that ~60% of the population with antibodies would be required.  In the end, you need to question whether the methodology of Ontario's seroprevalence work results in a fair representation of the actual path of covid in the province, or whether the many other studies scattered amongst a wide variety of other jurisdictions are more representative of reality. 

 

If you believe the results, what it does suggest is that Ontario, despite having already had a catastrophic outbreak in its retirement homes might still be very susceptible to a second wave of covid (see what is currently happening in Spain, France, Belgium and the Netherlands).  On that, I can offer the opinion that there will be much less willingness for a vigourous lockdown in a potential second wave than there was in the first.  Like what is happening in Europe right now, there will likely be a much greater tolerance to the presence and spread of covid than what there was in April.  It calls into question the wisdom and sustainability of a great many of the measures that governments imposed in March/April.

 

Even in the "best" of cases where you would optimistically hold the view that there is a 15:1 ratio between people who hold immunity and officially diagnosed cases, Toronto would currently only be at 7.5% of the population with antibodies, right?  If you think 15%-20% is required, there still remains much misery to occur, and if you are in the camp that 60% is required there might be years of misery in Toronto's future.

 

SJ

i do 'believe' that the 'real' % is higher but likely not much higher, because of the methodological limitations. An input that strengthens this belief is the recent data published in the UK. The method of study was much stronger but, as you likely know also, the social method involved, at least for some time and to a relative degree, involved to "take it more on the chin", and it may be reasonable to raise the possibility that the different approach is correlated and perhaps more to the more elevated morbid statistics. So, they reveal a slightly less than 6% prevalence overall (3 to 13%, according to the regions, by the end of June).

https://www.imperial.nhs.uk/about-us/news/largest-home-antibody-testing-publishes-results

Your points about sustainability and 'fatigue' are well taken.

What i know is that my area seems to be better prepared (actions already taken and others ready to be deployed) in the event of a second wave towards chronic care and retirement homes.

[Gregmal]

https://nypost.com/2020/08/17/shocking-images-show-packed-wuhan-pool-party-in-former-coronavirus-ground-zero/

 

 

CLEARLY! concerned about the virus....

[Dalal.Holdings]

“Shocking” news from Lombardy too!

 

https://www.velonews.com/news/road/il-lombardia-2020-remco-versus-the-rest/

 

It’s almost like if you manage the pandemic competently, you could return back to close to normal life even if you were among the hardest hit areas instead of holding out for mythical “herd immunity” or a rushed vaccine all the way in August 2020. Sorry, America!

[StubbleJumper]

“Shocking” news from Lombardy too!

 

https://www.velonews.com/news/road/il-lombardia-2020-remco-versus-the-rest/

 

It’s almost like if you manage the pandemic competently, you could return back to close to normal life even if you were among the hardest hit areas instead of holding out for mythical “herd immunity” or a rushed vaccine all the way in August 2020. Sorry, America!

 

 

Have you considered the possibility that the reason why things are going okay in Lombardy these days is because they actually made significant progress towards herd immunity during their atrocious outbreak in the spring?  Lombardy is a region where the official numbers state that there have been 97k diagnosed cases and 17k deaths recorded for a region of 10m people.  With a ~17% calculated CFR, clearly the official statistics are drastically under-counting the true number of cases in that region.  So, run the calculation backwards, beginning with the number of deaths to infer a plausible number of infections in the region.  If you are in the camp that believes that the IFR is likely around 0.5% or 0.6%, then the 17k deaths implies about 3 million infections.  A region of 10m people with ~3m infections could be quite far advanced along the path to herd immunity.

 

So, are the current daily numbers in Lombardy indicative of good management in the present, or poor management in the past?

 

 

SJ

[tng]

Comparing present U.S., European, and Asian numbers have a lot of flaws. The U.S. got the virus later than Europe, who got it later than Asia. And in the beginning, nobody was counting COVID cases/deaths because they didn't know COVID was a thing and they didn't have testing ability/capacity. Who knows how much it spread before they started counting. If the COVID deaths curve goes way up (meaning it is extremely widespread within the population) and then flatlines, the region probably has herd immunity. You can't remove the virus from the population when it is that extremely widespread. Too much noise in the data and people focus too much on where the theoretical threshold for herd immunity is. You know it when you see it, and that is when the deaths go away.

[Liberty]

https://arstechnica.com/science/2020/08/covid-spit-test-is-faster-cheaper-avoids-shortages-and-now-greenlit-by-fda/

 

The US Food and Drug Administration this weekend authorized a saliva-based diagnostic test for COVID-19 that costs less than $5, is faster than current laboratory tests, and may dodge supply shortages plaguing the country—without losing much in accuracy, according to early data.

 

The test, called SalivaDirect, was developed by researchers at Yale University, who have no plans to commercialize the test and have made the test’s protocol completely open and available.

[Dalal.Holdings]

For some reason USA continues to be exception to everywhere else and folks want to believe it’s “not fair” to compare to just about every other country...it never spread much from northern Italy (Lombardy) to southern Italy nor did it spread much outside of Wuhan to rest of China. Almost like when certain countries had certain regions hit, they strapped down and got through it without significant spread to other regions and now life is returning to some semblance of normal. Compare to USA...

 

Almost like calling it a hoax, dragging your feet, not caring because “mostly blue states are hit anyway”, and politicizing mask wearing was a terrible, irrational way to approach the pandemic and needlessly dragged it on, allowed it to take hold in other areas, and led to many more deaths in the USA...

[KCLarkin]

If the COVID deaths curve goes way up (meaning it is extremely widespread within the population) and then flatlines, the region probably has herd immunity. You can't remove the virus from the population when it is that extremely widespread. Too much noise in the data and people focus too much on where the theoretical threshold for herd immunity is. You know it when you see it, and that is when the deaths go away.

 

This is B.S. If this were true, there would not be the second wave phenomenon seen in past pandemics.

[Liberty]

If the COVID deaths curve goes way up (meaning it is extremely widespread within the population) and then flatlines, the region probably has herd immunity. You can't remove the virus from the population when it is that extremely widespread. Too much noise in the data and people focus too much on where the theoretical threshold for herd immunity is. You know it when you see it, and that is when the deaths go away.

 

This is B.S. If this were true, there would not be the second wave phenomenon seen in past pandemics.

 

Can confirm, it is total B.S. made up by people who have no idea what they're talking about or what it would take for "herd immunity".

[clutch]

If the COVID deaths curve goes way up (meaning it is extremely widespread within the population) and then flatlines, the region probably has herd immunity. You can't remove the virus from the population when it is that extremely widespread. Too much noise in the data and people focus too much on where the theoretical threshold for herd immunity is. You know it when you see it, and that is when the deaths go away.

 

This is B.S. If this were true, there would not be the second wave phenomenon seen in past pandemics.

 

His/her description is true if there were no lock downs (as predicted by the SIR model). We get 2nd waves because of interventions.

[KCLarkin]

His/her description is true if there were no lock downs (as predicted by the SIR model). We get 2nd waves because of interventions.

 

It would be roughly true if there were no public health interventions and no voluntary behaviour changes and no seasonality.

[Read the Footnotes]

His/her description is true if there were no lock downs (as predicted by the SIR model). We get 2nd waves because of interventions.

 

It would be roughly true if there were no public health interventions and no voluntary behaviour changes and no seasonality.

 

It would be roughly true if there were no public health interventions and no voluntary behaviour changes and no seasonality and no massive improvements in standard of care and if there were not multiple self reinforcing exponential components with associated tipping points regarding severity of disease.

 

I would not surprise me if we could be seeing a 95% reduction in fatality rates purely due to improvements in care. That alone would be enough to explain the difference, but such a wide gap is likely localized and not widespread. The thing you have to keep in mind is that early on in places like NYC, US healthcare was not only were not doing the right things, they actively doing the wrong things! There likely won't be much discussion of this fact due to many reasons, but litigation risk is clearly one of the top reasons.

[Spekulatius]

https://nypost.com/2020/08/17/shocking-images-show-packed-wuhan-pool-party-in-former-coronavirus-ground-zero/

 

 

CLEARLY! concerned about the virus....

 

You realize that this is likely party sanctioned and a big middle finger to the US? They claim no community transmission since May and have every one tested in Wuhan. One should at this with caution, but the claims are likely directional correct, otherwise this party wouldn’t happen.

 

In the mean time we can’t even open up our universities and schools.

[DocSnowball]

If the COVID deaths curve goes way up (meaning it is extremely widespread within the population) and then flatlines, the region probably has herd immunity. You can't remove the virus from the population when it is that extremely widespread. Too much noise in the data and people focus too much on where the theoretical threshold for herd immunity is. You know it when you see it, and that is when the deaths go away.

 

This is B.S. If this were true, there would not be the second wave phenomenon seen in past pandemics.

 

Very interesting counterpoint. However, influenza immunity lasts a few months typically and in past flu pandemics a lot of second waves were described. Coronavirus immunity has been longer lasting (1 year plus) example for SARS where there was no second wave. Still hard for me to believe at 5-20% of antibody titer positivities we would have herd immunity. IMHO it's partial population immunity but a major impact is from physical distancing and mask wearing. It's good enough to decrease cases so that there is a bed in the hospital if you need it, but not good enough where (near) normal social interaction could resume without inviting another outbreak.

[UK]

https://www.bloomberg.com/news/articles/2020-08-18/sweden-s-face-mask-debate-heats-up-amid-covid-resurgence-warning