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Epidemics are run through the mathematics of rules, and many mathematicians and experts around the world have shown, according to their models, rather thin projections of the end of the epidemic.
Source: RTS
PHOTO: TANJUG / SAVA RADOVANOVIC / en
As Professor Peter Koovi explained to RTS, he created a model that interprets the epidemic in Serbia, compares it to other countries in the world, and predicts when we can expect a full infection.
As long as the trends are the same as in the previous ten days, according to Professor Koovia’s model, the coronavirus epidemic in Serbia should end around May 26, 2020. An increasing number of infected people are expected, with a tendency to decrease around zero.
Examples of SARS, swine flu, and especially coronaviruses show that viruses behaved mathematically, according to the Gaussian curve. Only data is entered for the amount of livestock per day, explains Professor Koovi.
On the other hand, he said, there is no mathematical model to predict a possible new wave well in advance, but even for the tsunami forecast, the forecasts can offer an immediate response as the event begins to unfold. Consequently, a warning may be issued that there is a possibility of a recurring epidemic.
The Gaussian distribution allows us to define nine levels that mark specific dates for a new alert.
Because of this, the observed events form a bell, this distribution is also called the normal distribution or popular bell curve.
The model was supplemented by the French mathematician Pierre Simon Markus de Laplas in its current form, so this distribution is also called Gaus-Laplas.
So initially, on a daily basis, the infection was one or none won. Then the thing exploded, so the number of wages increased. Then it starts to shrink. And that reduction will be around zero, depending on some factors: a) the discipline of the population to apply physical distance measures, and b) that the epidemic does not explode, Professor Koovi told RTS.
The model is based on input from the world by the World Health Organization, and for Serbia, a medical crisis tab. This information overlaps with Serbia, but this is not the case for many sites in the world dealing with the same subject.
The Gaussian curve compensates for the smaller rise and fall, which we call a wave, as well as more waves. As Professor Koovi explains, in case there is a dramatic increase in the number of patients on a daily basis, then one has to switch to a multi-wave model, by the name, for now, it is not necessary.
A new epidemic cannot be predicted, especially if there is a break in the data, for example during the summer, so it continues into, say, October, Professor Peter Koovi concludes.
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