While the intent here is to give a lesson on exponential and logistic growth as general phenomena, with epidemics as a timely case study, there are a few notes worth adding when it comes to epidemics themselves. Probably the most important, mentioned only as a small on-screen note, is that these models should account for the amount of time someone with the virus remains infectious. Those who recover (or die) are no longer able to spread it, and so don't factor into the growth equation. The faster the growth, the less this matters, since at each point on the curve most people with the virus will have only contracted it recently, but especially in the long run or with slower growth, any realistic model has to consider this. The other factor, which I was hesitant to even get into here, is the extent to which reported cases reflect real cases. Generalizing away from epidemics, though, the key upshot is to be aware of phenomena where the rate of growth is proportional to the size of the thing growing. Compound interest, technological progress, population growth, and many other things fit this pattern, and it's shocking how bad our intuitions can be at recognizing what it means.

"Two Knuckles Deep in My Mathhole: Slowly Reaching Calculus”

An excellent, diagram-guided overview of Fitt's Law, which declares that the closer and larger something is, the easier it is to access. The relationship is curved: small changes to small items can have a large impact.

Extensive, exhaustive, informative.