Analysing COVID-19 outbreak
The strange thing with infectious diseases is that, from first principles, they are the most curable of all diseases. Despite their huge potential to infect large parts of the population in a short time, they are in principle so easy to control. The current ‘corona crisis’ has once again shown us all the enormous impact of an infectious disease that is spreading uncontrollably. This is bad and, in the case of COVID-19, can lead to millions of deaths. However, this does not change a simple medical fact: of all known diseases, infectious diseases are in principle the most controllable. In order to stop the further spread of the disease, a very simple measure is sufficient in principle: you just have to make sure that sick and healthy people do not come into contact - that's all. No vaccination, treatment or medication is necessary (of course, we are here not speaking about the illness of a certain person, but the prevention of further spread to other people). In contrast, there are no known methods to prevent the spread of cancer, cardiovascular diseases or other illnesses in society.
However, the current situation makes us realize how difficult it is to
realize this simple rule in today's networked world.
On Feb 27 I wrote in one Twitter:
Let's do the following thought experiment: imagine a joint effort of all people on this planet going together into quarantine for a limited time. Sounds like a big effort, but after a couple of weeks wouldn't we be rid of Corona and many other diseases? At this time my statement was seen with a great deal of bewilderment by my friends. Today on March 18, just 4 weeks after this tweed, a total lock-down has suddenly become reality all over Europe.
Be it as it may, in the last weeks I have started some investigations (time series analysis and modelling) on COVID-19 dynamics. I have opened a new section coronavirus in this blog, where I will post my results. All numerical code and the developed algorithm will be publicly available on my github repository.