When looking for ways to artificially reenact the COVID crisis for understanding it, it may well be that I will need the approach with networks and complex adaptive systems, but it is not very helpful to begin with that. See also how I got stuck setting up likely systems with network architectures. It turned out that I simply knew too little about the simpler observations and the connections that could be explained with them. Well, such led me to take the time to brush up my very outdated programming knowledge. I focused on Python. With that I under my belt I produced overviews of the first COVID year (in several parts). Here I show a collection of graphs from 21 European countries.
I do not analyze them further here. I will use them later to elaborate on rules of conduct and heuristics for toy worlds. Anyone reading this can use them to assess his or her ideas about the societal mechanisms that generate and drive COVID. The information is (or should be) equivalent to, e.g., the COVID dashboard provided by the WHO. Only, such dashboards do not combine graphs and present them apart. This, I find, does not make analysis easier.
Each graph in the figure below has a header with the three-letter code of the jurisdiction in question. In that line, the number of deaths up to the first of the week of 2021 is also given, followed by the same number, but now (for comparison) per million inhabitants.
The lines in the graphs indicate the numbers of new deaths (black) and new infections (red) per day. The infections have been scaled to 1/100 of the actual number to be support placing both lines in one graph. That also helps to be able to judge those numbers on their value a little. If the black line is clearly above the red, this means either that the risk of death from infection is above the one percent, or that the registration rate is low. The x axis is a timeline. The y axis gives the numbers (or hundreds) of people.
I selected the countries by intuition, as belonging to the EU or as being closely associated with it geopolitically. That resulted in 29 countries: Albania, Austria, Belgium, Bulgaria, Bosnia and Herzegovina, Switzerland, Cyprus, Czech Republic, Germany, Denmark, Spain, Estonia, France, Great Britain, Greece, Ireland, Italy, Lithuania, Latvia, Malta, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia and Sweden.
