Department of Analytical, Physical, and Social Sciences, Carlow University, 3333 Fifth Ave, Pittsburgh, PA, 15213, USA.
Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47408, USA.
Bull Math Biol. 2021 May 26;83(7):79. doi: 10.1007/s11538-021-00909-0.
The pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has quickly spread worldwide, creating a serious health crisis. The virus is primarily associated with flu-like symptoms but can also lead to severe pathologies and death. We here present an ordinary differential equation model of the intrahost immune response to SARS-CoV-2 infection, fitted to experimental data gleaned from rhesus macaques. The model is calibrated to data from a nonlethal infection, but the model can replicate behavior from various lethal scenarios as well. We evaluate the sensitivity of the model to biologically relevant parameters governing the strength and efficacy of the immune response. We also simulate the effect of both anti-inflammatory and antiviral drugs on the host immune response and demonstrate the ability of the model to lessen the severity of a formerly lethal infection with the addition of the appropriately calibrated drug. Our model emphasizes the importance of tight control of the innate immune response for host survival and viral clearance.
严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）的大流行爆发迅速在全球范围内蔓延，造成了严重的健康危机。该病毒主要与流感样症状有关，但也可能导致严重的病理和死亡。我们在这里提出了一个关于宿主对 SARS-CoV-2 感染的免疫反应的常微分方程模型，该模型拟合了从恒河猴中收集的实验数据。该模型是根据非致死性感染的数据进行校准的，但也可以复制各种致死性情况的行为。我们评估了模型对控制免疫反应强度和效力的生物学相关参数的敏感性。我们还模拟了抗炎和抗病毒药物对宿主免疫反应的影响，并证明了通过添加适当校准的药物，该模型能够减轻以前致命感染的严重程度。我们的模型强调了宿主生存和病毒清除过程中对先天免疫反应的严格控制的重要性。
