it could a low risk individual who has a great many contacts...
but if that were the soley the case... we would most likely be seeing far more clusters developing all over in areas around say costcos and super markets.
we may not know what makes a super spreader right now... but the data seems to be showing that super spreaders are responsible for 80 percent of the cases.
your analysis based on the SIR model and R0 is not useful for Covid.
Basically your models sucks and you have been full of shit this entire time.
Its is very possible most people with the virus do not infect anyone.
I know multiple people who had it and did not even infect a family member.
I will also tell you your models absolutely suck for the following reason.
If the R0s you have been pushing were accurate for Covid. A virus in which half the people are asymptomatic. And many would be infectious before they new they were sick...
There is no fucking way... this virus would not have erupted and destroyed Sweden and us and everywhere that is not completely shut down...
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The problem, according to Reich & Co., is that SIR is focused heavily on one number above all others, the "R-naught," the theoretical transmission rate, how many people, on average, each infected person can infect. It's been the dominant focus of models of COVID-19 for months now.
Instead, Reich and team emphasize not the average, but the extraordinary cases in society, the people who have many more contacts than most people, and can therefore infect an unusually large amount of people. Super-spreaders have been studied for many years with respect to numerous epidemics. The 2014-2015 outbreak of the Middle East Respiratory Syndrome coronavirus, or "MERS," was traced to one South Korean individual who spread the disease to numerous individuals, two of whom spread the disease to further large groups. Similar patterns of "index" patients were observed with Ebola and with the SARS outbreak in 2002 to 2003.
https://www.zdnet.com/article/googl...uper-spreaders-are-a-big-part-of-the-problem/
Scientists don't know exactly why certain people "shed" virus, meaning, pass it on, more than others. It might have to do with weakened immunity in those individuals, but there are other hypotheses. (Scientist Gary Wong and colleagues at the Chinese Academy of Science provided an excellent explanation of the super-spreader phenomenon
in a paper a few years ago, and their work is cited by Reich & Co.)
Reich,
who is a data scientist at Google, doesn't have the explanation for why super-spreading happens. Rather, he and colleagues take the fact of super-spreading as a given to create predictions of what super-spreading does in a pandemic.
Tell me how just
letting the low risk group run about is going in Brazil.
Let's go over the definition of R) also known as Rnaught again - R0 is the infectious rate of a disease with no mitigation.
R - the infection rate number is the rate of a disease with mitigation at a certain time.
R0 rate of a disease is exactly the same of low risk and high risk individuals. The idea that a "low risk group may have an R0 of close to zero" is nonsense. Rnaught is the same for everyone.
High risk people who are probably staying at home are not superspreaders. Your superspreader is your low risk individual who goes out to crowded gatherings and spreads the disease to a large number of individuals.
The perfect recent example being the COVID positive party guy in South Korea who went to 3 discos and infected at least 160 people with 46,000 traced by contact leading to a lockdown of the local city and for all discos to be closed in the country to prevent this from ever occurring again.
