INVESTIGATION OF THE SPREAD OF THE COVID-19 VIRUS IN A LARGE URBAN AGGLOMERATION USING A DIFFERENTIAL EPIDEMIOLOGICAL MODEL AND THE POTENTIAL IT’S APPLICATIONS IN SOFTWARE

UDC 519.8
DOI: 10.36871/2618-9976.2024.03.004

Authors

Valentin A. Markovsky,
Master of Science–intensive Technologies and Economics of Innovation, ITMO University, St. Petersburg, Russia
Ruslan I. Mamedguliev,
Master of Business Informatics, ITMO University, St. Petersburg, Russia
Lyubov P. Sazhneva,
Candidate of Science (Economics), Associate Professor, ITMO University, St. Petersburg, Russia
Irina A. Savina,
Master of Science–intensive Technologies and Economics of Innovation, ITMO University, St. Petersburg, Russia
Maria S. Chebrova,
Bachelor of Applied Computer Science and Physics, Moscow Institute of Physics and Technology, Moscow, Russia

Abstract

In this article, the authors considered a differential model that is used to analyze epidemiological data and predict the development of a pandemic of coronavirus infection. The real data were data on the spread of morbidity in Moscow, a large agglomeration with a high population density, a city of federal significance. In addition, the potential of using the model in special software is described.

Keywords

Agglomeration, Differential model, Information system, Digital urbanism, Epidemiology