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This article discusses the epidemiological susceptible-infected-recovered (SIR) and susceptible-exposed-infected-recovered (SEIR) models, which are used to analyze the dynamics of the spread of viral pneumonia among the population. These models allow us to predict the development of the epidemic, assess the risks of infection, and determine the potential burden on the healthcare system. The SIR and SEIR models contribute to more accurate early diagnosis and assessment of the severity of the disease, helping to make timely decisions on epidemic management. The main results of this study indicate that the SEIR model gave more realistic results than SIR, taking into account the latency period and interactions between people in the early stages of infection in Uzbekistan. Using the SEIR model allowed the government to correctly assess the initial phases of the disease and understand the variability of the infection in Uzbekistan.

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Analysis and Selection of an Appropriate Model for Analyzing the Current State and Spread of COVID-19 in Uzbekistan Based on SIR and SIER Models

  • 会议论文

  • 发表日期：

    2026年

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  • Nodira Naim,
  • Maxina Mansurova,
  • Avaz Kuvnakov

摘要

This article discusses the epidemiological susceptible-infected-recovered (SIR) and susceptible-exposed-infected-recovered (SEIR) models, which are used to analyze the dynamics of the spread of viral pneumonia among the population. These models allow us to predict the development of the epidemic, assess the risks of infection, and determine the potential burden on the healthcare system. The SIR and SEIR models contribute to more accurate early diagnosis and assessment of the severity of the disease, helping to make timely decisions on epidemic management. The main results of this study indicate that the SEIR model gave more realistic results than SIR, taking into account the latency period and interactions between people in the early stages of infection in Uzbekistan. Using the SEIR model allowed the government to correctly assess the initial phases of the disease and understand the variability of the infection in Uzbekistan.