Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antiviral treatments. In this work, based on the concept of virus spreadability in the host, antiviral effectiveness thresholds are determined to establish whether or not a treatment will be able to clear the infection. In addition, the virus dynamic in the host – including the time-to-peak and the final monotonically decreasing behavior – is characterized as a function of the time to treatment initiation. Simulation results, based on nine patient data, show the potential clinical benefits of a treatment classification according to patient critical parameters. This study is aimed at paving the way for the different antivirals being developed to tackle SARS-CoV-2.

描述 SARS-CoV-2 动力学和 COVID-19 患者相应免疫反应的数学模型对于评估抗病毒治疗可能的临床结果至关重要。在这项工作中，基于宿主中病毒传播性的概念，确定抗病毒有效性阈值以确定治疗是否能够清除感染。此外，宿主中的病毒动态——包括达到峰值的时间和最终的单调下降行为——被表征为治疗开始时间的函数。基于九个患者数据的模拟结果显示了根据患者关键参数进行治疗分类的潜在临床益处。这项研究旨在为开发不同的抗病毒药物来应对 SARS-CoV-2 铺平道路。