4.6 Article

Personalized Virus Load Curves for Acute Viral Infections

期刊

VIRUSES-BASEL
卷 13, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/v13091815

关键词

viral load; patient specific; mathematical modeling; SARS-CoV-2

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资金

  1. Natural Sciences and Engineering Research Council (NSERC) [RGPIN-2017-04158, RGPIN-2019-06435]

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An explicit function describing virus-load curves on a patient-specific level has been introduced in this study, based on simple and intuitive model parameters. The model has been validated on various datasets, showing wide distributions of model parameters and providing a new way to analyze virus load data as well as estimate exponential growth rates of infection phases. The virus load function, target model, and exponential approximations exhibit excellent fits for the data considered.
We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis of acute viral infections without solving a full virus load dynamic model. We validate our model on data from mice influenza A, human rhinovirus data, human influenza A data, and monkey and human SARS-CoV-2 data. We find wide distributions for the model parameters, reflecting large variability in the disease outcomes between individuals. Further, we compare the virus load function to an established target model of virus dynamics, and we provide a new way to estimate the exponential growth rates of the corresponding infection phases. The virus load function, the target model, and the exponential approximations show excellent fits for the data considered. Our virus-load function offers a new way to analyze patient-specific virus load data, and it can be used as input for higher level models for the physiological effects of a virus infection, for models of tissue damage, and to estimate patient risks.

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