In the previous posts I made something of a deal about the number called the growth factor. I’d like to explain why it’s such a deal. Consider the following graph:

It looks like “Mr. Toad’s Wild Ride” and is generated from the data I’ve collected from the Johns Hopkins COVID-19 website. I hope to show here that VERY small changes in it’s value can lead to major changes in the outcomes. First, let’s look at the actual numbers:

Additionally, growth factors 2 or greater lead to extremely high infection counts (the entire world would be infected in under 33 days) that are not reflected in reality so eliminate those data points.

so, I’m going to use the last seven days growth factors to predict the next seven days number of infections. For comparison let’s check the projections using the raw growth rates, the rates without the outliers plus rates greater than 2, and finally the filtered seven day averaged.

I will be using the running average in future predictions. Let’s see how things look on Friday . . . film at 11:00.