Pandemics and scapegoats

Emperor Marcus Aurelius

Human beings have an irresistible tendency to blame others for our misfortunes and our mistakes. In fact, this is a symptom of low maturity, very clear in children, who when they are caught red-handed doing something they shouldn’t, they always try to justify themselves by blaming someone else. But the trend is so widespread that it applies not just to children, but to most human beings.

In the particular case of pandemics, this is seen quite clearly. Epidemic diseases were almost unknown before the invention of cities, which took place some 10,000 years ago. But for a pandemic to be possible (an epidemic affecting a considerable part of the world), the world had to wait until there were great empires, with many internal and external commercial relations.

Mathematics of the pandemic

The May issue of the Spanish magazine on popular science Investigación y Ciencia, associated to Scientific American, contains an article authored by Bartolo Luque, Fernando Ballesteros and Octavio Miramontes, in which they apply to the current pandemic a mathematical model that dates back over a century. This model describes the first phase of the pandemic, the exponential rise of the first part of the logistics curve that I referred to in a previous post in this blog, and makes it possible to compare the evolution of the disease in various countries, depending on the virus containment measures that have been taken in each of them. It could also serve to explain why Spain has become the country with the most cases in Europe and with the most deaths per 100,000 inhabitants in the world.

The evolution of the pandemic in Spain

Logistic curve

Using the data provided every day by the Spanish Ministry of Health, about the number of new cases affected by the pandemic each day, and the number of deaths, we have carried out the following analysis:

1. We have manipulated slightly the real data to take into account the weekend effect, pointed out by the minister, which consists in the fact that the figures for new cases for March 28, 29 and 30 are not faithful to the reality, because fewer cases are declared on the weekend (we are used to waiting until Monday to do it), and then, on Monday, all the missing cases get accumulated. As by then the curve had flattened, what we’ve done is replacing the data about new cases for those three days by the average of the three, thus redistributing the Monday excess between Saturday and Sunday. The following weekend, April 4, 5 and 6, we made the same correction. The attached figure represents the number of new cases for each day (red curve) and the number of deaths (green curve). The numbers in the abscissa of the figure represent days counted from the beginning of the data. Day 1 corresponds to March 3. Day 36 is April 7, the last day about which there were data when this post was published.