Parameter identifiability for extensions of the Fisher-KPP model #

Yue Liu, Philip K Maini, Ruth E Baker

10:50 Wednesday in 2Q50/51.

Part of the Epidemiology and statistical learning session.

Abstract #

The Fisher-KPP model is one of the simplest partial differential equation models exhibiting travelling wave behaviour, and has been widely used to model the growth and spread of populations in biology. When applying the model to experimental data, it is often tempting to generalize the model with additional parameters to obtain a better fit. However, this increase in model complexity also increases the difficulty of estimating the parameter values. In this study, we use a profile likelihood approach to investigate parameter identifiability in extensions of the Fisher-KPP model on both simulated data, and experimental data from a cell invasion assay. We focus on the effects of the forms of the kinetic terms, model misspecifications, and amount of data. We also quantify the amount of data required to justify a more complex model, and explore ways to design experiments to yield data more useful for parameter identification.