The next time someone asks when you think things might get back to normal, you might reply, like Flyvbjer, "I don't think we will see a regression to the mean because pandemics, like earthquakes and bankruptcies, don't follow the rules of Gaussian distribution." That'll stop the conversation right there.

We live under the assumption that most things in life follow a pattern of standard distribution. This is the basis for the idea of regression to the mean which is deeply ingrained in most of us. For that reason and others, we imagine things going *back to normal*. But not all events occur with standard distribution.

Size-distributions of pandemics, floods, wildfires, earthquakes, wars, and terrorist attacks, e.g., have no population mean, or the mean is ill defined due to infinite variance. In other words, mean and/or variance do not exist. Regression to the mean is a meaningless concept for such distributions, whereas what one might call "regression to the tail" is meaningful and consequential.

In disaster recovery, there can never be a return to the way things were [1]. Return to normal or *regression to the mean*, is *meaningless*. There are a few options; abandon ship (or house, or town, or country, or planet… is that an option??), build back better, or rebuild in some other way. If not better then what? If not back to normal, then what?