Parsimonious models of in-host viral dynamics and immune response

Mathematical models of in-host viral dynamics and immune response are a vital tool for patient-specific estimation of the initial viral load, prediction of the course of an infection, etc. The COVID-19 pandemics has given impetus to the development of models with an ever-increasing degree of complex...

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Bibliographic Details
Published inApplied mathematics letters Vol. 145
Main Authors Lu, Hannah, Giannino, Francesco, Tartakovsky, Daniel M.
Format Journal Article
LanguageEnglish
Published United States Elsevier 07.07.2023
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Summary:Mathematical models of in-host viral dynamics and immune response are a vital tool for patient-specific estimation of the initial viral load, prediction of the course of an infection, etc. The COVID-19 pandemics has given impetus to the development of models with an ever-increasing degree of complexity. We show that one of the most popular models---the Target Cell Limited model---fails the identifiability test, i.e., its parameters cannot be uniquely inferred from readily available data such as viral load measurements. Here, we present a model that is both identifiable and parsimonious according to information criteria. Our model's predictions match both reported observations of COVID-19 patients and predictions of its more complex counterparts.
Bibliography:SC0023163
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
ISSN:0893-9659
1873-5452