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This study introduces a computational model designed to simulate the human immune response to SARS-CoV-2, validated against data from multiple clinical studies. The model captures the temporal dynamics of mature CD4 \(^+\) T cells, mature CD8 \(^+\) T cells, viral load, and antibody levels across three COVID-19 severity profiles: mild, severe, and critical. In all simulated scenarios, the model-generated trajectories remained primarily within the confidence intervals of empirical data, demonstrating its capacity to qualitatively reproduce key trends in immune responses across varying disease severities.

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A Computational Immune Approach for Modeling Different Levels of Severity in COVID-19 Infections

  • 会议论文

  • 发表日期：

    2025年

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  • Laura Polverari e Silva,
  • Marcelo Lobosco,
  • Ruy Freitas Reis

摘要

This study introduces a computational model designed to simulate the human immune response to SARS-CoV-2, validated against data from multiple clinical studies. The model captures the temporal dynamics of mature CD4 \(^+\) T cells, mature CD8 \(^+\) T cells, viral load, and antibody levels across three COVID-19 severity profiles: mild, severe, and critical. In all simulated scenarios, the model-generated trajectories remained primarily within the confidence intervals of empirical data, demonstrating its capacity to qualitatively reproduce key trends in immune responses across varying disease severities.