Once again, the use of 'average' in the phrase 'average reproduction number' presumes that the numerical value of 'average reproduction number' has some relevance to something or other in the real world. If such a numerical value can vary from 0.9-100, that fact would belie any commonsense notion of 'average' -- meaning 'ordinary' or 'typical'. But wait, it gets much worse! This numerical value R0_whatever-you-want-to-call-it is used as the *base* for an exponential function ! I.e., we're looking at an exceedingly fat-tailed distribution of numbers (R0)^some-exponent, so any hope of 'fitting' data to such a mess is out of the question. But models that can't fit data, can't predict anything. Models that cannot predict anything are no longer science, but quackery aka witchcraft. Is it any wonder that none of these 'models' can predict even an order of magnitude of infection, much less even 1 significant (decimal!) digit? The next article I read that quotes some PhD 'expert' which refers to this R0 nonsense will cause me to vomit. Perhaps those on this list will agree that proofs should end with 'QED', not 'PhD'. At 08:30 AM 5/22/2020, Michael Kleber wrote:
Just for clarity of terminology:
The epidemiological definition of R0 is the average reproduction number *in a completely susceptible population*.