That is not quite what R0 means. R0 is the reproductive rate in a naive population. I believe the variable you are looking for is R(t), which is the effective reproductive rate at any point of time.
Thank you. I've seen the phrase "effective R0" used, for example, here [0], but I can see that you are correct that R(t) is the generally accepted epidemiological term.
this is a mathematical convention, not simply an epidemiological term. the 0th term of any function, like R0, is generally understood as the initial condition constant (at time t=0). R(t) is a function of time and R0 is the value of R at time 0, the initial condition. R0 tells you exactly nothing about the future, it only pins down the starting point (which is important information, but not the be-all-and-end-all of it).
i’ve been mildly amused/dismayed by the constant misplaced focus on R0 over the past 2 years by the media/laypeople, given this essential context.
That’s not correct. While R0 is indeed R at time 0, time is not the important part of that. It’s that at time 0 everyone is presumed susceptible so the growth is going to be as exponential as it’s going to get. R0 is a strong indicator of the limits of how the disease will spread and is very useful for predicting the future, both in terms of the speed of the initial exponential spread, but also the upper bound on spread that the disease is likely to encounter.
no, the epidemiological model in question has two degrees of freedom, and one of those degrees is stipulated by the assumed shape of the curve (exponential, even though that's a poor fit overall, logistic being a better fit). R0 does not constrain the other degree of freedom; it only gives you the initial condition. it requires knowing that other degree of freedom, which you're making implicit assumptions about, that governs what you can say about the rapidness of spread and makes some statements about bounding. this is rudimentary calculus and linear modeling.
