Professor Petar Kocovic calculated when the end of the epidemic would give the exact date

crown crown, Photo: EPA

Epidemics adhere to mathematical rules, and many mathematicians and data scientists around the world have shown fairly accurate projections of the course and end of the epidemic with their models. Professor Petar Kočović has created a model that interprets the epidemic in Serbia, compares it to other countries in the world, and predicts when we can expect a complete reduction in infection.

The epidemic in Serbia, as long as the trends are the same as in the previous 10 days, should end around May 26, 2020. An increasing number of infected people are expected, with a tendency to decrease around zero.

According to a cursory survey of the SARS epidemic, swine flu, and especially coronaviruses, these viruses behaved mathematically, according to the Gauss curve. Data is only entered for the number of infected daily.

There is no mathematical model to predict a new wave well in advance, but it looks like a tsunami forecast: Forecasts can start as soon as the event begins to unfold. Consequently, a warning may be issued that the possibility of a (new) epidemic exists.

The Gaussian distribution allows us to define nine levels that indicate specific dates for a new warning (more positive or negative than the previous one), somewhat like in meteorology, when meteorological alarms are defined.

Modeling the epidemic, its course and end, and the steps to be taken during an epidemic is one possible process. The mathematical model is based on the work of the famous German mathematician and physicist Johann Karl Friedrich Gauss, the best mathematician of antiquity, who noted the appearance of the distribution of a series of events and worked on it in 1794 and 1795. Because the events under observation form a bell, this distribution is also called normal distribution or popular bell curve.

The model was supplemented by the French mathematician Pierre Simon markus de Laplas in the current form, so this distribution is also called Gaus-Laplas.

Gaussian and Sigmund curve, Photo: printskrin

Gaus also found his place on the obverse of 10 notes of German Marks, which were in circulation from 1898 to 2001, on the merits of mathematical development. This methodology is used in many engineering and economic and marketing disciplines.

For the purposes of Kovid-19, we will use the term epidemiological day instead of the word event.

So at first the infection was one or none infected on a daily basis. Then the thing exploded, so the number of infected people increased. Then it starts to shrink. And that reduction will be around zero, depending on a couple of factors: a) the discipline of the population to apply measures of physical distance and b) the epidemic so that it does not explode.

The model is based on input from the World Health Organization around the world and a medical crisis staff for Serbia. This information overlaps with Serbia, but this is not the case for many sites around the world dealing with the same subject.

Gaussian curve, Photo: printskrin

Regardless of the source of the data, they can be entered under the Gaussian model, but the curve itself and the estimate of the end of the epidermis may differ. Very often the differences are small. Otherwise, it is the fault of each day separately and the entry of new data has nothing to do with the previous days.

The Gaussian curve compensates for the smaller rise and fall, which we call a wave, as well as more waves. If there is a dramatic increase in the number of patients daily, then you have to move to a multi-wave model, for which, for now, there is no need.

A new epidemic cannot be predicted, especially if there is a break in the data (for example, in the summer, so continue on, for example, October).