Тип публикации: статья из журнала
Год издания: 2022
Идентификатор DOI: 10.3889/oamjms.2022.6717
Ключевые слова: coronavirus, morbidity, recovery rates, susceptibility to disease
Аннотация: BACKGROUND: The globalization processes have led to the fact that several infections have acquired the character of pandemics and cause significant economic and social damage. This problem is far from being resolved and requires various studies. The study aimed to develop a mathematical model reflecting the time dependence of the parameters characterizing the spread of the pandemic. AIM: This work aims at obtaining the time dependence of epidemiological parameters by the method of differential modeling. METHODS: Since in this study there were unknown laws that make it possible to compose differential equations, which represent a differential model of the process under study, several assumptions (hypotheses) were put forward concerning the course of this process with small changes in the parameters – variables. RESULTS: By solving differential equations of the constructed model, the desired epidemiological parameters were obtained, that is, the laws reflecting the change in the number of susceptible to the disease, number of people infectious patients depending on time, and the time at which the number of infectious patients will be the maximum, that is, the time point corresponding to the peak of the pandemic. CONCLUSION: The epidemic situation is described by a system of equations (usually differential), which, depending on the type of model, in one way or another determines the dynamics of the transition of individuals from one group to another. Differential models make it possible not only to predict the development of the situation but also to evaluate various epidemiological parameters. © 2022 Nadezhda Cherkunova.
Издание
Журнал: Open Access Macedonian Journal of Medical Sciences
Выпуск журнала: Vol. 10
Номера страниц: 22-26
ISSN журнала: 18579655
Издатель: Scientific Foundation SPIROSKI
Персоны
- Cherkunova N. (Sayano-Shushensky Branch, Siberian Federal University, Russian Federation)
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