  In this paper the dynamics of an autonomous mathematical models of COVID-19
depending on a real parameter bifurcation, is controlled by switching
periodically the parameter value. For this purpose the Parameter Switching (PS)
algorithm is used. With this technique, it is proved that every attractor of
the considered system can be numerically approximated and, therefore, the
system can be determined to evolve along, e.g., a stable periodic motion or a
chaotic attractor. In this way, the algorithm can be considered as a chaos
control or anticontrol (chaoticization)-like algorithm. Contrarily to existing
chaos control techniques which generate modified attractors, the obtained
attractors with the PS algorithm belong to the set system attractors. It is
analytically shown that using the PS algorithm, every system attractor can be
expressed as a convex combination of some existing attractors. Moreover, is
proved that the PS algorithm can be viewed as a generalization of
Parrondo\textsc{\char13}s paradox.
