Abstract
In this article we analyze the evolutionary dynamics of the novel
coronavirus epidemic (covid-19) using observed data from several cities
and places in the world. We have used a SIR-type (Susceptible,
Infectious and Recovered) model improved with some adaptions in order to
increase its predictive skills, i.e., we have included the circulation
restriction effect and considered a phenomenon we have called adherence
zone, generating the Modified SIR model (ModSIR). Comparing the results
produced with ModSIR with real observations obtained for several places
in the world we have found that ModSIR presented good predictive skill,
as long as combined with good enough parametric identification. At the
end of this article we present a study in which we simulated an epidemic
in a hypothetical city of 211000 inhabitants. We have extracted several
useful conclusions by analyzing some epidemic scenarios in which we
evaluate epidemic control by adopting the circulation restriction as a
control variable.