This work presents an extended and age-band compartmentalised SEIR model that allows describing the spread evolution of SARS-CoV-2 and evaluating the effect of different detection rates, vaccination strategies or immunity periods. The model splits up the population into fifteen age groups of 5 years each, linked through a statistical interaction matrix that includes seventeen health states within each age group. An age-dependent transmission rate takes into account infectious between the groups as well the effect of interventions such as quarantines and mobility restrictions. Further, the proposal includes a nonlinear switched controller for model tuning purposes guarantying a simple and fast adjusting process. To illustrate the model potentials, the particular case of COVID-19 evolution in Argentina is analysed by simulation of three scenarios: (i) different detection levels combined with mobility restrictions, (ii) vaccination campaigns with re-opening of activities and (iii) vaccination campaigns with possible reinfections. The results exhibit how the model can aid the authorities in the decision making process.