  The discovery of SARS-CoV-2, the responsible virus for the Covid-19 epidemic,
has sparked a global health concern with many countries affected. Developing
models that can interpret the epidemic and give common trend parameters are
useful for prediction purposes by other countries that are at an earlier phase
of the epidemic; it is also useful for future planning against viral
respiratory diseases. One model is developed to interpret the fast-growth phase
of the epidemic and another model for an interpretation of the entire data set.
Both models agree reasonably with the data. It is shown by the first model that
during the fast phase, the number of new infected cases depends on the total
number of cases by a power-law relation with a scaling exponent equal to 0.82.
The second model gives a duplication time in the range 1 to 3 days early in the
start of the epidemic, and another parameter alpha = 0.1-0.5) that deviates the
progress of the epidemic from an exponential growth. Our models may be used for
data interpretation and for guiding predictions regarding this disease, e.g.
the onset of the maximum in the number of new cases.
