you are so full of shit.. just yesterday you admited R0 is estimated and can not be determined accurately until the epidemic is over. What you are citing is a bunch of attempts to estimate R0 using a failed model and frequently using very bad data from China. Its not real. What is real is the virus is not following the growth model in places which are coming out of lockdown... and Sweden which was not in lockdown. nothing you believe makes any sense in light of real world data yet you still bullshit your ass off. you beliefs are countered by the data yet you refuse to change them. Why are Sweden's deaths trending down. Why hasn't almost everyone in stockholm gotten Covid? your models are garbage.
When Governor Gretchen Whitmer finishes destroying Michigan's economy with huge job losses then, after she imposes huge taxes on her constituents, I cannot wait for the Antifa and BLM thugs to come out and riot, destroy and burn Michigan down. These extreme liberal Democrat governors think they are way too smart and will damage President Donald Trump's re-election. All they are damaging is their state's economies from which, they will have a hard time recovering from if at all. So, keep at it Democrat chumps, you are doing a hell of a job.
EVERY SINGLE DETAILED STUDY FOR COVID-19 CURRENTLY HAS Rnaught ABOVE 2. Of course the final figure will not be arrived at until the first wave of the pandemic is passed. As note before the CFR and R0 for nearly every novel disease goes UP rather than down when final studies are completed. How can this be so difficult for you to understand? Let's begin with a question - Do you understand that there is only one Rnaught figure that applies to ALL of humanity. There is not one Rnaught figure for low risk people and a different Rnaught figure for high risk people. Until you state that you clearly understand this and accept it as undisputed fact then it is not even worth having a discussion with you.
I already taught you.. .by definition it does not apply to all humanity. It applies to homogenous susceptible groups. The people in San Diego are not necessarily like the people in wuhan. And we don't even know that everyone is equally suspceptible. it is possible who had other similar viruses in the past... don't catch Covid. you constant confuse theory for reality and that is why you are constantly wrong as new data comes in. because your detailed studies have used horrible data from with populations which are nothing alike. And initially this virus was spread in clusters and preyed upon the weak. Your model is based on 100 year old thinking. The proper way to view this is that 80 percent of the infections come from very few individuals and the rest of us on average don't spread it at all. this virus is not following anything close to an exponential growth model impled by an R0 of two or more. Graphs in places which were not shutdown (in the first world) look the same as places were where. South Dakota and Sweden death rates are way down and look like everwhere else. your model fails in the real world. this type of model is much more likely to explain things... https://www.zdnet.com/article/googl...uper-spreaders-are-a-big-part-of-the-problem/ Reich and colleagues move beyond the typical infectious disease models that are commonly used for COVID-19. Those models are based on the so-called "susceptible, infectious, recovered" model of disease spread. The SIR model is a "mechanistic" model, based on a very general understanding of the mechanism by which all infectious diseases spread. It was first introduced in 1927 by scientists William Ogilvy Kermack and Anderson Gray McKendrick. 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.
proof you are an idiot who does not take in the science or data contrary to the dnc world view. by definition GWB is wrong. by observation GWB is wrong by the new models of super spreaders and clusters GWB is super wrong. as I said... We don't even know that everyone in each population can catch Covid. so starting from scratch... no vaccine no previous Covid. Spread rate in a population in Wuhan could be very very different that the spread in north county san diego. -- a far more useful model... will be developed when we can estimate a populations propensity to have superspreaders. If your population has zero superspreaders your R0 is likely going to be significantly different than a population with a large number of potential super spreaders.
the average within the population vs the average within the other population... how does that work? how does that work if one population has more superspreaders?
If you don't even understand the scientific definition of Rnaught then there is really no purpose in continuing the discussion with you.
Things continue to go great in Georgia. Where as in some places people are still locked down in their basement. "Mom is it safe to come out of the basement?" "Not yet Joe."