  We present a phenomenological procedure of dealing with the COVID--19 data
provided by government health agencies of eleven different countries. Instead
of using the (exact or approximate) solutions to the SIR (or other) model(s) to
fit the data by adjusting the time--independent parameters included in those
models, we introduce dynamical parameters whose time--dependence may be
phenomenologically obtained by adequately extrapolating a chosen subset of the
daily provided data. This phenomenological approach works extremely well to
properly adjust the number of infected (and removed) individuals in time, for
the countries we consider. Besides, it can handle the sub--epidemic events that
some countries may experience. In this way, we obtain the evolution of the
pandemic without using any a priori model based on differential equations.
