  The global crisis caused by the COVID-19 pandemic, in conjunction with the
economic consequences and the collapse of health systems, has raised serious
concerns in Europe, which is the most affected continent by the pandemic since
it recorded 2,388,694 cases and 190,091 deaths (39.6% of the worldwide total),
of which 71.7% (136,238) are in the United Kingdom (43,414), Italy (34,708),
France (29,778), and Spain (28,338). Unlike other countries, Greece, with about
310 confirmed cases and 18 deaths per million, is one bright exception in the
study and analysis of this phenomenon. Focusing on the peculiarities of the
disease spreading in Greece, both in epidemiological and in implementation
terms, this paper applies an exploratory analysis of COVID-19 temporal spread
in Greece and proposes a methodological approach for the modeling and
prediction of the disease based on the Regression Splines algorithm and the
change rate of the total infections. Also, it proposes a hybrid spline
regression and complex network model of social distance measures evaluating and
interpreting the spread of the disease. The overall approach contributes to
decision making and support of the public health system and to the fight
against the pandemic.
