根据病毒 RNA 量和病毒滴度,为 COVID-19 患者建立 SARS-CoV-2 病毒动态模型。

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Daichi Yamaguchi, Ryosuke Shimizu, Ryuji Kubota
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引用次数: 0

摘要

靶细胞有限模型是定量了解病毒动态的数学建模方法之一,在以前的研究中已被用于描述严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)的病毒 RNA 图谱。然而,这些模型主要是利用大流行初期的患者数据建立的。此外,没有任何报告关注病毒滴度的概况。在本研究中,我们使用了反映当前临床情况的数据来描述病毒 RNA 和病毒滴度的动态特征,在当前临床情况下,Omicron 变体已成为流行病,SARS-CoV-2 疫苗也已上市。5212 例病毒 RNA 水平和 5216 例病毒滴度的连续数据来自 720 例冠状病毒病 2019(COVID-19)患者,这些患者参加了 ensitrelvir 的 II/III 期研究。我们的模型假设生产性感染的细胞只产生感染性病毒,而感染性病毒可转化为非感染性病毒,该模型已被用于描述病毒 RNA 水平和病毒滴度的动态变化。据估计,未接种疫苗的患者从感染到症状出现的时间(tinf)为 3.0 天,比接种疫苗的患者短。作为幂函数,接种疫苗患者的免疫相关参数是未接种疫苗患者的 1.1 倍。我们的模型可以预测 COVID-19 患者从感染到症状出现的病毒动态。疫苗接种情况是影响 tinf 和免疫功能的一个因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Development of a SARS-CoV-2 viral dynamic model for patients with COVID-19 based on the amount of viral RNA and viral titer

Development of a SARS-CoV-2 viral dynamic model for patients with COVID-19 based on the amount of viral RNA and viral titer

The target-cell limited model, which is one of the mathematical modeling approaches providing a quantitative understanding of viral dynamics, has been applied to describe viral RNA profiles of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in previous studies. However, these models have been developed mainly using patient data from the early phase of the pandemic. Furthermore, no reports focused on the profiles of the viral titer. In this study, the dynamics of both viral RNA and viral titer were characterized using data reflecting the current clinical situation in which the Omicron variant has become epidemic and vaccines for SARS-CoV-2 have become available. Consecutive data for 5212 viral RNA levels and 5216 viral titers were obtained from 720 patients with coronavirus disease 2019 (COVID-19) in a phase II/III study for ensitrelvir. Our model assumed that productively infected cells would produce only infectious viruses, which could be transformed into non-infectious viruses, and has been used to describe the dynamics of both viral RNA levels and viral titer. The time from infection to symptom onset (tinf) of unvaccinated patients was estimated to be 3.0 days, which was shorter than that of the vaccinated patients. The immune-related parameter as a power function for the vaccinated patients was 1.1 times stronger than that for the unvaccinated patients. Our model allows the prediction of the viral dynamics in patients with COVID-19 from the time of infection to symptom onset. Vaccination status was identified as a factor influencing tinf and the immune function.

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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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