Parameter estimation and identifiability of a HIV-1 model

In this work, some identifiability and sensitivity properties of a reduced complexity model for the Human Immunodeficiency Virus 1 (HIV-1) infection are considered. In addition to study the effect of parameters on the model states, the impact of the data sampling frequency on a cost used for parameter estimation is also addressed. The conclusions are used as guidelines to identify models from clinical data in two case studies in which the patients did not follow the prescribed therapy.