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A different visualization of deaths, smoothed out by a 7 day rolling average. (from Coronavirus tracked: the latest figures as countries fight to contain the pandemic | Free to read)


upload_2020-5-3_12-59-35.png
 
I heard infection rate in NYC is magically inching backwards! :rolleyes::rolleyes::rolleyes::rolleyes:
There were reports that for the first set of samples people were calling their friends to come and wait in line to get tested. People willing to do that are probably more likely to have been infected. Maybe they made changes to reduce self selection bias?
Maybe it was just a different set of stores in different neighborhoods at a different time of the day? There's always going to be a lot of noise with this type of sampling.
Amazing what humans will do to validate their internal model of the universe. Fabricating new denominators is awfully cute.
:rolleyes:
 
Just wanted to say that this thread is awesome and immensely informative than “FREE AMERICA” tweets. Thank you everyone

At first, I was incredulous how so many can believe in this endless supply of villains working tirelessly behind the scenes to explain away this or that inconvenient truth (about a freaking virus of all things), then I realized we have had leadership that for years has used conspiracy, insinuation, and outright gaslighting to counter everything inconvenient to them. It has trained a tragic number of people to "problem solve" this way, a lousy coping mechanism. It may work in terms of rallying people to this and that cause, or to promote the endless food fight that media companies built empires on, but newsflash: The virus has been the problem, is the problem, and will likely be the problem for many, many months to come.

I salute the relatively few left with the mental stamina to face this crisis daily and try to extract truth from chaos and move the ball forward, whether they be frontline medical, researchers, public health folks, etc. Being neck deep in all the uncertainties around this situation every day is probably too much for most, but these people continue bring discipline of thought to this battle that is more valuable than ever. I also really appreciate the posters here who embody that IMO and have shared a bunch of useful links and content that have helped immensely in trying to understand, thanks.
 
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Getting our kids back to school – a matter of trust
An opinion piece by the Australian Government’s Deputy Chief Medical Officer, Nick Coatsworth.

"As an infectious diseases specialist, I have examined all of the available evidence from within Australia and around the world and, as it stands, it does not support avoiding classroom learning as a means to control COVID-19."

".... the disruption to routine and socialisation, while temporary, tends to have a disproportionate effect on our more vulnerable children..."

Getting our kids back to school – a matter of trust
 
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I heard infection rate in NYC is magically inching backwards! :rolleyes::rolleyes::rolleyes::rolleyes:

Amazing what humans will do to validate their internal model of the universe. Fabricating new denominators is awfully cute.

There were reports that for the first set of samples people were calling their friends to come and wait in line to get tested. People willing to do that are probably more likely to have been infected. Maybe they made changes to reduce self selection bias?
Maybe it was just a different set of stores in different neighborhoods at a different time of the day? There's always going to be a lot of noise with this type of sampling.

:rolleyes:

------

My impression was that for the first time they calculated numbers within NYC weighted by neighborhood size:

NYC overall: 19.9% positive for antibodies.
Bronx: 27.6%
Brooklyn: 19.2%
Manhattan: 17.3%
Queens: 18.4%
Staten Island: 19.2%

(Results are weighted.)

and previously did so only by region within the state, with NYC being a single region. That means they now calculate separate averages for each neighborhood, and combine them weighted by neighborhood population size. In other words, a more detailed and therefore more correct calculation of the city average. (Although I'm not completely certain they didn't do so earlier already.)
 
Lol, I keep looking for indication that "fat" Americans will be affected by covid more than other countries (not a scientific approach, just a hunch everytime I try and find anything at the store without a ton of sugar).

Oh wait, here it is... I think we would have to normalize for per capita data. But we're looking pretty fat right now. "Best healthcare in the world" is all I hear when anyone defends the cost of drugs. Wow, doing so well... Highest score again! USA #1.

upload_2020-5-3_12-41-45.png
 
Today I realized that almost every epidemiologist has made a great error regarding R and herd immunity.

Let’s say R0=2.5. Then it’s a simple thought error to assume that 60% needs to be infected for herd immunity. However here is the error, populations are not uniform. For example R in NYC is gonna be higher than in Alaska. Let’s assume R=4 in NYC and 2 in Alaska, then herd immunity should be at 75% in NYC and 50% in Alaska. Wrong, populations are not uniform. Some people will interact with more people than other. For example young people vs retired people, bus drivers vs truck drivers, kindergarten teachers vs online English teachers etc. If in one city 10% of the people do 50% of the interacting then these people will get infected earlier in average and once they have immunity the city will get their R cut in half.

So the conclusion of this is that R will be higher early in the spread when the high interaction individuals get infected. Then it will naturally fall even with pretty low level of immunity.

Finally a research paper ran with this idea:
Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

Abstract
As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation is depleted causing the rate at which new cases occur to decline. Variation in individual susceptibility or exposure to infection exacerbates this effect. Individuals that are frailer, and therefore more susceptible or more exposed, have higher probabilities of being infected, depleting the susceptible subpopulation of those who are at higher risk of infection, and thus intensifying the deceleration in occurrence of new cases. Eventually, susceptible numbers become low enough to prevent epidemic growth or, in other words, herd immunity is attained. Although estimates vary, it is currently believed that herd immunity to SARS-CoV-2 requires 60-70% of the population to be immune. Here we show that variation in susceptibility or exposure to infection can reduce these estimates. Achieving accurate estimates of heterogeneity for SARS-CoV-2 is therefore of paramount importance in controlling the COVID-19 pandemic.

...

44 Here we demonstrate that individual variation in susceptibility or exposure (connectivity)
45 accelerates the acquisition of immunity in populations. More susceptible and more connected
46 individuals have a higher propensity to be infected and thus are likely to become immune earlier.
47 Due to this selective immunisation, heterogeneous populations require less infections to cross
48 their herd immunity thresholds than homogeneous (or not sufficiently heterogeneous) models
49 would suggest. We integrate continuous distributions of susceptibility or connectivity in
50 otherwise basic epidemic models for COVID-19 and show that as the coefficient of variation
51 increases from 0 to 4, the herd immunity threshold declines from over 60% to less than 10%.

52 Measures of individual variation are urgently needed to narrow the estimated ranges of herd
53 immunity thresholds and plan accordingly.


What I have realized since I wrote the post above is that early in the spread we have superspreaders who spread it to other superspreaders directly and indirectly. Thus we can see very very rapid increase from 10 cases to 10000 cases. Then 2 months later in the epidemic we can have countries that are still open with just a little social distancing and pretty low levels of anitbodies(5-20%) and still having greatly decreased R. For example Sweden which is still open with people sitting outside in restaurants drinking beer and having a laugh seems to have peaked anyway somehow. Because a lot of the superspreaders have already gotten infected. Also some minor social distancing will greatly reduce the population of superspreaders.
 
Well, yeah it's only useful for serology surveys and hypothetical "immunity passports".
This test is not cheap either, they say $100 is "at cost".
Of course PCR tests can detect infection before symptoms (causing much confusion over reports of huge majorities of asymptomatic cases).
Are there any technologies other than PCR that can detect viruses? Any possibility of a home test?
I was talking about two stage antibody testing
 
As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation is depleted causing the rate at which new cases occur to decline. Variation in individual susceptibility or exposure to infection exacerbates this effect. Individuals that are frailer, and therefore more susceptible or more exposed, have higher probabilities of being infected, depleting the susceptible subpopulation of those who are at higher risk of infection, and thus intensifying the deceleration in occurrence of new cases.
This concept will be quite unpopular in this thread.
 
Finally a research paper ran with this idea:
Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

Abstract
As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation is depleted causing the rate at which new cases occur to decline. Variation in individual susceptibility or exposure to infection exacerbates this effect. Individuals that are frailer, and therefore more susceptible or more exposed, have higher probabilities of being infected, depleting the susceptible subpopulation of those who are at higher risk of infection, and thus intensifying the deceleration in occurrence of new cases. Eventually, susceptible numbers become low enough to prevent epidemic growth or, in other words, herd immunity is attained. Although estimates vary, it is currently believed that herd immunity to SARS-CoV-2 requires 60-70% of the population to be immune. Here we show that variation in susceptibility or exposure to infection can reduce these estimates. Achieving accurate estimates of heterogeneity for SARS-CoV-2 is therefore of paramount importance in controlling the COVID-19 pandemic.

...

44 Here we demonstrate that individual variation in susceptibility or exposure (connectivity)
45 accelerates the acquisition of immunity in populations. More susceptible and more connected
46 individuals have a higher propensity to be infected and thus are likely to become immune earlier.
47 Due to this selective immunisation, heterogeneous populations require less infections to cross
48 their herd immunity thresholds than homogeneous (or not sufficiently heterogeneous) models
49 would suggest. We integrate continuous distributions of susceptibility or connectivity in
50 otherwise basic epidemic models for COVID-19 and show that as the coefficient of variation
51 increases from 0 to 4, the herd immunity threshold declines from over 60% to less than 10%.

52 Measures of individual variation are urgently needed to narrow the estimated ranges of herd
53 immunity thresholds and plan accordingly.


What I have realized since I wrote the post above is that early in the spread we have superspreaders who spread it to other superspreaders directly and indirectly. Thus we can see very very rapid increase from 10 cases to 10000 cases. Then 2 months later in the epidemic we can have countries that are still open with just a little social distancing and pretty low levels of anitbodies(5-20%) and still having greatly decreased R. For example Sweden which is still open with people sitting outside in restaurants drinking beer and having a laugh seems to have peaked anyway somehow. Because a lot of the superspreaders have already gotten infected. Also some minor social distancing will greatly reduce the population of superspreaders.

I could be a "superspreader", cool.
Not the same as these people though...

upload_2020-5-3_13-16-44.png
 
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The problem is also that when they come home or move about, they infect others who are innocent of such behavior.

It's true. So vancouver should apply the swedish model. I. E. Only isolate the old.

I used to be very cautious towards the long term lung problems and the large amount of cases where ppl get chronic reinfections. Bit so far it seemsnlike vancouver don't have this problem. Even our homeless downtrodden population shows no such problem. So whatever condition that causes the virus to manifest its strength doesn't happen here.
 
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...if you are obese, have diabetes, cancer, high blood pressure, or are old, you are in pretty high danger of hospitalization and possible death. Otherwise, it’s not too bad.

Agreed. But the tragic problem is 42% of adults and 18% of children in the US are obese.
Obesity is a Common, Serious, and Costly Disease
Childhood Obesity Facts | Overweight & Obesity | CDC

And nearly 70% of American adults age 40–79 are on prescription drugs, most of which may increase vulnerability because they increase ACE2 receptors in the lungs that provide entry to the virus.
Products - Data Briefs - Number 347 - August 2019
ACE inhibitors and angiotensin receptor blockers may increase the risk of severe COVID-19, paper suggests