Structural and Practical Identifiability Analysis of Models for Syncytia Growth

Syncytia are multinucleated cells that can occur due to virus infection of cells. Mathematical models in the form of ordinary differential equations can be used to simulate the growth syncytia. Several novel ODE models can explain syncytia growth. Before employing these models on actual data, it is essential to analyze their structural(theoretical) and practical identifiability. Structural identifiability is an inherent property of each model and its parameters, referring to our ability to determine parameter values for the model. Practical Identifiability analysis of a model is concerned with accurately determining parameter values given experimental error. Obtaining accurate parameter values allows us to make conclusions about our data within the context of our model that can provide insight into the nature of the spread of syncytia. These two techniques allow us to determine whether or not the parameters of a model are identifiable with the data we plan to collect. Consequentially, we can plan experiments adequately to truly parameterize the data in the contexts of our models to help make better conclusions.