Here are the data that I will use to calibrate the toy world that I am building to get a grip on the COVID-19 pandemic intellectually. I write this in real time. Today is the 6th of June 2020. I use data that I harvest from worldometer.

Today I just have the data in table Fig. 1 available. Twenty-four weeks (0-23), each one ending on Friday. The dates are in column 1. One world and five jurisdictions: China or PRC, USA, France or F, UK and the Netherlands or NL. Two types of information (cumulative): the number of registered coronavirus infections (-i) and the number of registered deaths (-d). These numbers will deviate from what the facts are, but they are the best that I can get.

The data in Fig. 1 show the cumulative dynamics of COVID-19 infections and -fatalities. To get a picture of the wave dynamics one computes the differences between two subsequent weeks. In Fig. 2 these have been recorded for the fatalities (dd, delta-d).

Having six jurisdictions in data invites comparison. This is not easy. My first attempt is in Fig. 3. There we show the fatality curves of Fig. 1’s data. We at least need two different scales for the same data. The graph on top is scaled to show the fatality accumulations until 120,000 max. This scale allows an overview picture wherein each jurisdiction fits but the world, which gets out of bounds in week 16. And things get too compressed around week 12, when the trends in the USA, F, the UK and NL can hardly be distinguished.

Consequently we added another graph of the same data, but now scaled to show the fatality accumulations until 7,000 max. This approach allows to focus on what happens in the first periods of the pandemic *per jurisdiction*. In order to allow comparison with algorithm 0, I added its curve in both, so, that it shows as the most left curve (grey, pen-6). It leaves the top graph in week 16 and the bottom graph in week 10. It is not always easy to realize that these presentations represent the same data. Neither is it self-evident, that the curve for algorithm 0 is scale-free — meaning that it has the same form at different scales. It is further useful to mention that for each of the curves based on observations, the first weeks follow algorithm-0 characteristics, be it in different weeks of the pandemic.

I nevertheless needed an alternative approach. I put it in Fig.4.

Figure 4 shows six columns for six jurisdictions. The rows give visualizations of new deaths, new infections and cumulative coronavirus deaths per week. So if these are at a level of 1000 per day. the minigraphs show a level of 7000 per week. For comparisons in times, week 10 and week 20 are signaled with vertical lines. Interpretations are offered and discussed later.