Mathematical modeling of Ebola virus (EBOV)-host dynamics during infection and treatment in vivo is in its infancy due to few studies with frequent viral kinetic data, lack of approved antiviral therapies, and limited insight into the timing of EBOV infection of cells and tissues throughout the body. Current in-host mathematical models simplify EBOV infection by assuming a single homogeneous compartment of infection. In particular, a recent modeling study assumed the liver as the largest solid organ targeted by EBOV infection and predicted that nearly all cells become refractory to infection within seven days of initial infection without antiviral treatment. We compared our observations of EBOV kinetics in multiple anatomic compartments and hepatocellular injury in a critically ill patient with Ebola virus disease (EVD) with this model's predictions. We also explored the model's predictions, with and without antiviral therapy, by recapitulating the model using published inputs and assumptions. Our findings highlight the challenges of modeling EBOV-host dynamics and therapeutic efficacy and emphasize the need for iterative interdisciplinary efforts to refine mathematical models that might advance understanding of EVD pathogenesis and treatment.

中文翻译：

---

在感染和治疗过程中模拟埃博拉病毒宿主动态的挑战。

埃博拉病毒（EBOV）宿主在体内感染和体内治疗过程动力学的数学模型尚处于起步阶段，原因是很少进行频繁的病毒动力学数据研究，缺乏批准的抗病毒疗法，并且对细胞和组织EBOV感染时间的了解有限整个身体。当前的宿主数学模型通过假设单个均质感染区室来简化EBOV感染。特别是，最近的一项模型研究假设肝脏是EBOV感染靶向的最大实体器官，并预测几乎所有细胞在未经抗病毒治疗的初始感染后7天内对感染都是难治的。我们将该模型对重症埃博拉病毒病（EVD）患者的多个解剖区室EBOV动力学和肝细胞损伤的观察结果进行了比较” 的预测。通过使用公开的输入和假设对模型进行概括，我们还探讨了使用或不使用抗病毒治疗的模型预测。我们的发现凸显了对EBOV宿主动力学和治疗功效进行建模的挑战，并强调了跨学科的迭代努力以完善数学模型的必要性，这些数学模型可能会增进对EVD的发病机理和治疗的了解。