  In this study, we propose a time-dependent
Susceptible-Exposed-Infected-Recovered (SEIR) model for the analysis of the
SARS-CoV-2 epidemic outbreak in three different countries, the United States of
America, Italy and Iceland using public data inherent the numbers of the
epidemic wave. Since several types and grades of actions were adopted by the
governments, including travel restrictions, social distancing, or limitation of
movement, we want to investigate how these measures can affect the epidemic
curve of the infectious population. The parameters of interest for the SEIR
model were estimated employing a composite likelihood approach. Moreover,
standard errors have been corrected for temporal dependence. The adoption of
restrictive measures results in flatten epidemic curves, and the future
evolution indicated a decrease in the number of cases.
