  The COVID-19 pandemic has affected all countries of the world producing a
substantial number of fatalities accompanied by a major disruption in their
social, financial, and educational organization. The strict disciplinary
measures implemented by China were very effective and thus were subsequently
adopted by most world countries to various degrees. The infection duration and
number of infected persons are of critical importance for the battle against
the pandemic. We use the quantitative landscape of the disease spreading in
China as a benchmark and utilize infection data from eight countries to
estimate the complete evolution of the infection in each of these countries.
The analysis predicts successfully both the expected number of daily infections
per country and, perhaps more importantly, the duration of the epidemic in each
country. Our quantitative approach is based on a Gaussian spreading hypothesis
that is shown to arise as a result of imposed measures in a simple dynamical
infection model. This may have consequences and shed light in the efficiency of
policies once the phenomenon is over.
