  When studying the evolution of complex systems one refers to model
representations comprising various descriptive parameters. There is hardly
research where system evolution is described on the base of information flows
in the system. The paper focuses on the link between the dynamics of
information and system evolution. Information, exchanged between different
system's parts, before being processed is first provided with meaning by the
system. Meanings are generated from the perspective of hindsight, i.e. against
the arrow of time. The same information can be differently interpreted by
different system's parts (i,e,provided with different meanings) so that the
number of options for possible system development is proliferated. Some options
eventually turn into observable system states. So that system evolutionary
dynamics can be considered as due to information processing within the system.
This process is considered here in a model representation. The model under
study is Triple Helix (TH) model, which was earlier used to describe
interactions between university, industry and government to foster innovations.
In TH model the system is comprised of three interacting parts where each part
process information ina different way. The model is not limited to the sphere
of innovation and can be used in a broader perspective. Here TH is
conceptualized in the framework of three compertment model used to describe
infectious disease. The paper demonstrates how the dynamics of information and
meaning can be incorporated in the description of Covid-19 infectious
propagation. The results show correspondence of model predictions with
observable infection dynamics.
