Ural Federal University: Scientists Built a Mathematical Model of Infection Spreading

Scientists at Ural Federal University have created a mathematical model that describes the development and spread of epidemics. This model is universal and would be suitable for studying any mass disease, including coronavirus infection or the new monkeypox virus. The model covers basic factors such as the rate of recovery or infection, for example. When all parameters are taken into account, scientists are able to draw up scenarios for the spread of the epidemic and identify possible ways of acting on the disease to prevent or suppress it. A description of the model is published in The European Physical Journal Special Topics.

“The idea of our study is to show the variability, the complexity of the consequences of fluctuations depending on the ratio of parameters. For example, we found that limiting the number of contacts, that is, quarantine, is indeed effective in reducing the incidence of disease and suppressing the virus. Moreover, according to the mathematical calculation, in a proportional ratio it gives a better result in the fight against the spread of infection than the use of medications that reduce mortality or increase the intensity of recovery,” says Lev Ryashko, Professor of the Department of Theoretical and Mathematical Physics at the Ural Federal University.

The model considers the rate of spread of infection, which depends on the intensity of contact between healthy people and infected people, the mortality rate caused by the disease, the rate of recovery, etc. Scientists pay special attention to the fact that all factors are of random nature and any even small quantitative change has a significant impact on the outcome of the epidemic spread.

“We built a mathematical model of the dynamic interaction between healthy and infected elements of the overall population system. For example, the number of human contacts is random: today you meet 10 people, and tomorrow you meet 20. Every such fluctuation can have a significant impact on changing the scenario of disease spread. In some situations, these changes may lead to complete recovery of the infected part of the population, while in others, on the contrary, to its extinction,” explains Lev Ryashko.

The research was supported by the Russian Science Foundation (project № 21-11-00062). Previously, a group of mathematicians developed a model that allows us to study and identify the internal mechanisms of complex dynamic phenomena of neuronal activity, biochemistry of cellular processes, changes in ecological systems, etc.