MATHEMATICAL MODELING OF THE COVID-19 EPIDEMIC: METHODS, SCENARIOS, AND PRACTICAL APPLICABILITY

This article presents a systematic literature review of current approaches to mathematical modeling of the COVID-19 epidemic. It examines classical compartmental models (SIR, SEIR and their modifications), time-series models (ARIMA, SSA), hybrid models incorporating artificial intelligence elements, as well as agent-based and stochastic models. The applicability of these models is analyzed across different epidemiological contexts, including resource-constrained countries such as the Kyrgyz Republic. Particular attention is given to the application of the SEIR model within the CoMo Consortium platform. The main strengths and limitations of various models are described, along with recommendations for adapting them to local conditions.