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Thanks for the link.

I'd say the big limitation is that the study relied on self-reporting to find out whether players have covid. Soccer players in the study had covid at a rate lower than the general population. And significantly lower at that. About 35% lower on a population of 90,000.

Either soccer is protective, or self reporting does a very poor job of identifying covid cases.
I guess Christiano doesn't self test or self report. lol
 
Thanks.

Is there a way to distinguish to what extent being a superspreader also means you are more likely to catch the disease? I’m wondering what fraction of superspreaders are already infected.

The catch is, Bob might be a superspreader because he is a very socially connected person, or it might be because he sprays as he talks. One makes him likely to be an early patient, and the other does not.
Didn't read @Lionel's link yet. I'll get to it and, yes, this is one of the significant complications.

I attempted a numerical approximation based on the results I showed above. I'll post it later today when I organize it better.
 
Continuing from my previous post, I have attempted to determine when the effective R = 1 for this population (herd immunity). Let me know if you find something questionable.

The primary assumption made along with the two previously calculated R-values is that “R” describes not only an individual’s propensity to spread the virus, but also describes their propensity to get the virus. On some level, that makes sense. To spread the virus to many people one needs to interact with many people. It’s not a stretch to believe that the same activity that allows one to infect many others also makes one more likely to get the virus. This assumption takes that idea to the extreme, but, it is illustrative.

Assume:
1. Population R0 = 3
2. 10% of the population has an R = 24
3. 90% of the population has an R = 2/3

Method: I use weights to allocate 1% of the population at a time to each group. The weights depend on the ratio of individuals with R = 24 to those with R = 2/3. This ratio will change as those in the group with R = 24 will get the virus at a higher rate. Thus the weights are constantly changing.

Initially, 100% of the population is susceptible:
10% weight: 0.1*24 = 2.4
90% weight: 0.9*2/3 = 0.6
The proportion associated with the 10% = 2.4/(2.4 + 0.6) = 0.8
- For the first 1% of the population infected, 0.8% are the “24’s” and 0.2% are the “2/3’s”
- So, the “24’s” drop from 10% to 9.2% and the 2/3’s” drop to 89.8%
- Re becomes (0.092*24 + 0.898*2/3) = 2.84
- Note that for the homogeneous population where R = 3 for everyone, after 1% are infected, Re = 0.99*3.0 = 2.97

Now, 99% of the population is susceptible
10% weight: 0.092*24 = 2.208
90% weight: 0.898*2/3 = 0.059866…
The proportion associated with the 10% = 2.208/(2.208 + 0.059866..) = 0.787


I summarize this process in the table below which was done on a spreadsheet

1602828451698.png

As a final adjustment, I averaged the proportion associated with 10% so that it doesn’t always take the value at the beginning of the “1% allocation” process and re-calculated.

1602828595220.png
 

Lionel Hutz

SILVER
Thanks.

Is there a way to distinguish to what extent being a superspreader also means you are more likely to catch the disease? I’m wondering what fraction of superspreaders are already infected.
Not really. Three things that drive superspreading -- virus, individual, setting. What makes a particular virus spread in this manner or a particular individual a superspreader is largely unknown. There is no data to my knowledge that shows superspreaders are more prone to being infected.

I have a feeling that there are significantly more superspreaders than there are superspreading events. Someone who is highly infectious will only become a superspreader if their behavior puts them in a situation -- like going to a club/bar/cruise -- where their presence can trigger one of these events.
 
CO announced its vaccine distribution plan when the time comes.


Colorado on Friday released its distribution plan for an approved coronavirus vaccine when it becomes publicly available as the state faced a deadline to submit it to the federal Centers for Disease Control and Prevention.

The distribution plan prioritizes three groups of people for the order in which people in those groups will be eligible to get vaccines. The first group of recipients is broken down into three levels of prioritized people and the second has two levels.

In the first phase, the priority recipients will be assisted living facility workers, home health care workers and outpatient pharmacists. Next are police officers, firefighters, public health workers and corrections staff members. The third level of vaccine recipients are nursing home and assisted living patients.

During the second phase, vaccines will be given to homeless people living in shelters; adult group home residents; workers such as ski industry and agricultural employees who share living spaces; students living in dormitories; essential workers such as grocery store workers, teachers and child care workers; and employees of businesses like the meatpacking sector where workers are in close proximity to each other. In the second part of this phase, people who are older than 65 or have certain health risks will get vaccines.

When all of those people have been given an opportunity to get the vaccine, the final phase starts with vaccine distribution to adults ages 18 to 64.
 

Grace T.

PREMIER
CO announced its vaccine distribution plan when the time comes.


Colorado on Friday released its distribution plan for an approved coronavirus vaccine when it becomes publicly available as the state faced a deadline to submit it to the federal Centers for Disease Control and Prevention.

The distribution plan prioritizes three groups of people for the order in which people in those groups will be eligible to get vaccines. The first group of recipients is broken down into three levels of prioritized people and the second has two levels.

In the first phase, the priority recipients will be assisted living facility workers, home health care workers and outpatient pharmacists. Next are police officers, firefighters, public health workers and corrections staff members. The third level of vaccine recipients are nursing home and assisted living patients.

During the second phase, vaccines will be given to homeless people living in shelters; adult group home residents; workers such as ski industry and agricultural employees who share living spaces; students living in dormitories; essential workers such as grocery store workers, teachers and child care workers; and employees of businesses like the meatpacking sector where workers are in close proximity to each other. In the second part of this phase, people who are older than 65 or have certain health risks will get vaccines.

When all of those people have been given an opportunity to get the vaccine, the final phase starts with vaccine distribution to adults ages 18 to 64.
Any word on what the guidelines are for mandatory requirements. I'm asssuming since in phase 1 it concerns living facility workers, the goal there is to protect the residents (not the workers) so presumably it will be mandatory. Same in phase 2 for officers and firefighters. By mandatory I'd define as take it or not allowed to work.

The third level might be rejiggered depending on what the vaccine tests show with older Americans, but maybe they have more up to date information showing early concerns aren't warranted and the vaccine has been very effective in older Americans.
 
I think what is trying to be calculated here is known as the "individual reproductive number" which is know as "v" which tries to capture the variation in R at the individual level by incorporating the dispersion parameter "k" for a given disease (k tries to capture if a disease spread is constant like the flu or spreads is bursts because of superspreaders like we see with Covid or SARS)

If you really want to dig into this -- here is a good layman explanation in The Atlantic on "k" (LINK) and the Nature paper from 2005 that describes how "v" is calculated (LINK).
Interesting paper. Thanks for sharing. I interpret the results to imply that if COVID 19 spread more like the flu, which generally has less variation in individual R, it would have been less likely to "die out" with a few infections in the population as it appears to have in Northern Italy. On the other hand, COVID 19 is also more likely to have an explosion of cases than the flu. Am I interpreting the results correctly?
 
Not really. Three things that drive superspreading -- virus, individual, setting. What makes a particular virus spread in this manner or a particular individual a superspreader is largely unknown. There is no data to my knowledge that shows superspreaders are more prone to being infected.

I have a feeling that there are significantly more superspreaders than there are superspreading events. Someone who is highly infectious will only become a superspreader if their behavior puts them in a situation -- like going to a club/bar/cruise -- where their presence can trigger one of these events.
I haven't found anything that addressed whether superspreaders are more likely to be infected either, but it would seem counter-intuitive if they weren't. If, as you suggest, they become a superspreader by being infected and going to a club/bar/cruise, etc., those that they come into contact with will also have the habit of frequenting those establishments.

This abstract looked at it in another way. It suggests that infections caused by superspreaders may be more severe and thus more likely to produce new superspreaders. It focuses not only on whether someone gets the disease but also on the severity of the case.

 

Lionel Hutz

SILVER
Interesting paper. Thanks for sharing. I interpret the results to imply that if COVID 19 spread more like the flu, which generally has less variation in individual R, it would have been less likely to "die out" with a few infections in the population as it appears to have in Northern Italy. On the other hand, COVID 19 is also more likely to have an explosion of cases than the flu. Am I interpreting the results correctly?
That is basically correct. To these points -- it has been suggested that the low "k" of coronaviruses may explain why we have seen two major coronavirus outbreaks in the past two decades but not smaller outbreaks -- it is hard for these viruses to get established but explode once they find the right environment.
 
Been awhile since I chimed in. Out here in Maryland, we were hit hard early. Since June, we have been open for the most part and are now up to 75% capacity in restaurants. Face masks are mandated indoors only. That is the current status. Now we are one of the lowest states reporting new cases by percentage for over a month. Soccer practices and tournaments have been going since August which has been great!

My question is why are we not seeing this in many other states? Why so many restrictions? You would think Maryland would be a great example to follow? (I should note that I know one answer to this problem but I am not allowed to voice it)
 
Been awhile since I chimed in. Out here in Maryland, we were hit hard early. Since June, we have been open for the most part and are now up to 75% capacity in restaurants. Face masks are mandated indoors only. That is the current status. Now we are one of the lowest states reporting new cases by percentage for over a month. Soccer practices and tournaments have been going since August which has been great!

My question is why are we not seeing this in many other states? Why so many restrictions? You would think Maryland would be a great example to follow? (I should note that I know one answer to this problem but I am not allowed to voice it)
MD, TX, CO, AZ, ...

C'mon, @MARsSPEED, you can't compare us to other states. Haven't you heard that we are "ahead of the curve" out here in Cali?

 

dad4

PREMIER
Been awhile since I chimed in. Out here in Maryland, we were hit hard early. Since June, we have been open for the most part and are now up to 75% capacity in restaurants. Face masks are mandated indoors only. That is the current status. Now we are one of the lowest states reporting new cases by percentage for over a month. Soccer practices and tournaments have been going since August which has been great!

My question is why are we not seeing this in many other states? Why so many restrictions? You would think Maryland would be a great example to follow? (I should note that I know one answer to this problem but I am not allowed to voice it)
It's interesting because MD has a case count almost equal to CA, per capita. And your daily cases per capita are only slightly higher than ours.

What are the restrictions in MD these days? ( schools, bars, movies, restaurants, sports, family gatherings, and so on...)

And do people follow the restrictions on private gatherings?
 
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