It does seem trivially obvious - if you are already closely familiar with the log-normal. :) I read the first few lines and thought, 'a long tail of infection t

It does seem trivially obvious - if you are already closely familiar with the log-normal. :) I read the first few lines and thought, 'a long tail of infection times? Infections are based on exponential growth. I bet this is a log-normal!' This is because I like the log-normal and notice it, but it's not something which gets a lot of coverage or is routinely taught in statistical material. A similar thing is the tail effects or order statistics of a normal distribution: if you set a cut off or threshold and look at the distribution of samples beyond it, it can look very surprisingly different from the original distribution. This comes up all the time in discussions of IQ, testing, higher education, racism/sexism/bias in general, health & disease, genetics, optimization etc, and keeps surprising the heck out of people because even though it's a statistical triviality, it's both counterintuitive and not typically taught.