  A phenomenological model to describe the Corona Virus(covid-19) Pandemic
spread in a given population is developed. It enables the identification of the
key quantities required to form adequate policies for control and mitigation in
terms of observable parameters using the Landau-Stuart equation. It is intended
to be complementary to detailed simulations and methods published recently by
Ferguson and collaborators, March 16, (2020). The results suggest that the
initial growth/spreading rate gamma-c of the disease, and the fraction of
infected persons in the population p-i can be used to define a
`retardation/inhibition coefficient' k-star , which is a measure of the
effectiveness of the control policies adopted.
  The results are obtained analytically and numerically using a simple Python
code. The solutions provide both qualitative and quantitative information. They
substantiate and justify two basic control policies enunciated by WHO and
adopted in many countries: a) Systematic and early intensive testing
individuals for covid-19 and b) Sequestration policies such as `social/physical
distancing' and population density reduction by strict quarantining are
essential for making k-star greater than 1, necessary for suppressing the
pandemic. The model indicates that relaxing such measures when the infection
rate starts to decrease as a result of earlier policies could simply restart
the infection rate in the non-infected population. Presently available
available statistical data in WHO and other reports can be readily used to
determine the the key parameters of the model. Possible extensions to the basic
model to make it more realistic are indicated.
