Numerical modeling of the impact of quarantine measures on the dynamics of the epidemiological process based on the SEIRD model

About the author:

Nina I. Eremeeva, Cand. Sci. (Phys.-Math.), Associate Professor, Department of Higher Mathematics, Dimitrovgrad Engineering and Technological Institute, National Research Nuclear University MEPhI (Dimitrovgrad); vm-diti.mifi@yandex.ru; ORCID: 0000-0001-6160-2572

Abstract:

The COVID-19 epidemic has once again demonstrated the importance of predicting the development of various processes and calculating the consequences. “How effective is the introduction of strict quarantine measures?” and “Will the quarantine be able to stop the epide­mic?” — these questions still have no clear answer.

This article aims to answer these questions using mathematical modeling tools using the SEIRD model, modified to account for the peculiarities of the spread of COVID-19. The SEIRD model belongs to the class of differential dynamic models, which allows quick experimentation to predict the spread of the disease and calculate its influence on the development of certain processes.

Based on numerical modeling, the author demonstrates that insufficient quarantine measures provide only a temporary effect. After they end, with an insufficient level of “population immunity”, the epidemic starts growing again, leading to a second morbidity peak.

This paper presents numerical calculations to track the duration impact and quarantine measures’ severity on the dynamics of the epidemiological process. The results show that strict restrictive measures are not always effective, and strict short-term measures have less effect than softer, but long-term measures.

In addition, the author provides an example of finding the parameters of quarantine measures that ensure fixed limits on the morbidity level during the epidemic.

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