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Evaluating the Within-Host Dynamics of Ranavirus Infection with Mechanistic Disease Models and Experimental Data

机译:用机理性疾病模型和实验数据评估鼻病毒的宿主内部动力学

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摘要

Mechanistic models are critical for our understanding of both within-host dynamics (i.e., pathogen replication and immune system processes) and among-host dynamics (i.e., transmission). Within-host models, however, are not often fit to experimental data, which can serve as a robust method of hypothesis testing and hypothesis generation. In this study, we use mechanistic models and empirical, time-series data of viral titer to better understand the replication of ranaviruses within their amphibian hosts and the immune dynamics that limit viral replication. Specifically, we fit a suite of potential models to our data, where each model represents a hypothesis about the interactions between viral replication and immune defense. Through formal model comparison, we find a parsimonious model that captures key features of our time-series data: The viral titer rises and falls through time, likely due to an immune system response, and that the initial viral dosage affects both the peak viral titer and the timing of the peak. Importantly, our model makes several predictions, including the existence of long-term viral infections, which can be validated in future studies.
机译:机理模型对于我们了解宿主内部动力学(即病原体复制和免疫系统过程)和宿主之间动力学(即传播)都是至关重要的。但是,宿主内部模型通常不适合实验数据,可以用作假设检验和假设生成的可靠方法。在这项研究中,我们使用病毒滴度的机理模型和经验,时间序列数据来更好地了解蛙病毒在两栖动物宿主中的复制以及限制病毒复制的免疫动力学。具体来说,我们将一套潜在模型拟合到我们的数据中,其中每个模型都代表有关病毒复制和免疫防御之间相互作用的假设。通过正式模型比较,我们发现了一个简化的模型,该模型捕获了我们时间序列数据的关键特征:病毒滴度会随时间上升或下降,这可能是由于免疫系统反应引起的,并且初始病毒剂量会影响峰值病毒滴度和高峰时间。重要的是,我们的模型做出了一些预测,包括长期病毒感染的存在,可以在以后的研究中进行验证。

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