Interactions between SARS-CoV-2 and the immune system during infection are complex. However, understanding the within-host SARS-CoV-2 dynamics is of enormous importance for clinical and public health outcomes. Current mathematical models focus on describing the within-host SARS-CoV-2 dynamics during the acute infection phase. Thereby they ignore important long-term post-acute infection effects. We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection scenarios differentiating between distinct variant-specific properties of the reinfecting virus. Together, the model’s ability to describe not only the acute but also the long-term post-acute infection dynamics provides a more realistic description of key outcomes and allows for its application in clinical and public health scenarios.

中文翻译：

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SARS-CoV-2 宿主内（再）感染动力学的数学模型

感染期间 SARS-CoV-2 与免疫系统之间的相互作用非常复杂。然而，了解宿主内 SARS-CoV-2 的动态对于临床和公共卫生结果至关重要。目前的数学模型侧重于描述急性感染阶段宿主内 SARS-CoV-2 的动态。因此，他们忽略了重要的长期急性感染后影响。我们提出了一个数学模型，它不仅描述了急性感染阶段的 SARS-CoV-2 感染动态，而且还通过概括临床观察到的长期急性感染后效应（例如感染数量的恢复）来扩展当前的方法。易感上皮细胞恢复到感染前的初始稳态水平，个体内永久且完全清除感染，免疫减弱，并在感染后形成长期免疫能力水平。最后，我们使用我们的模型及其对长期急性感染后动态的描述来探索区分再感染病毒的不同变体特异性特性的再感染场景。总之，该模型不仅能够描述急性感染，而且能够描述长期急性感染后动态，为关键结果提供了更真实的描述，并允许其在临床和公共卫生场景中的应用。