# COVID-19 Update: Data is Awful – Deaths are now the Best Metric

At this point, most of the data aggregators (including Johns Hopkins) have failed to keep track of the myriad of reporting organizations and have settled for less comprehensive data collections. So I have had to go off and decide which metrics are the most meaningful and aggregate them myself.

Because confirmed cases are so dependent on whether a country/state is testing and also because cases range from no symptoms all the way to stays in the ICU and even death, I have decided that confirmed cases are just a curiosity. In the chart above, you can see that NY has just over 2 confirmed cases per 1000 people. However, the number of deaths per 1000 people in NY is 0.02, 100x lower. Since hospitals must be required to report deaths (and since death is a fairly straightforward metric, whereas a confirmed case requires a positive test), I think this is a much better way to evaluate the severity of the outbreaks around the world.

The above chart makes the case (that I have been trying to document) that the ratio of deaths to cases is quite different in different parts of the world. However, there’s one more important measure that can also reflect on the severity, and that is the velocity and acceleration of this normalized death rate. The velocity over a one day period is easy to calculate. It’s just today’s normalized deaths minus yesterdays. The acceleration is the more useful number to understand, however, as it relates to how rapidly the problem is going to get out of control (or under control). This is because all of these outbreaks across the world appear to be increasing non-linearly. To understand what a non-linear process might look like, think about the old saying, “The Rich get Richer.” Because they’re Rich, they get Richer, and because now they’re Richer, they get even more Richer!

So here is a table showing the slope of the non-linear curve for today and the change in this slope over the last two days. Any of these countries or states with a positively changing slope is accelerating. Any with a negatively changing slope is decelerating (what we want!)

The countries that are accelerating the fastest (inst_roc_delta) are poor little Andorra, San Marino, Iceland, Spain, and then the trio of states NY, Vermont, and Louisiana. As you can see, even a small number of deaths in a country or state with a low population, can contribute to a big change in the instantaneous slope.

So… takeaway. Deaths in New York, Vermont, and Louisiana are increasing quickly, but are still well below the rates per 1000 people that we’re seeing in Spain, Italy, France, Iran, and even Switzerland (who is also well below the rates of those other hard-hit countries). The point may well be that things will eventually equalize across the world and these numbers will align. Or it may well be that some regions will remain lucky and will be up to 10x less hit with deaths than neighboring countries. It’s hard to tell right now, so we’ll keep watching.

## One Reply to “COVID-19 Update: Data is Awful – Deaths are now the Best Metric”

1. Alex Ivanov says:

Keep the data coming.