A Dynamical Map to Describe Covid-19 Epidemics

dos Reis, E. V. M.; Savi, M. A.

This paper proposes a dynamical map to describe COVID-19 epidemics based on the classical susceptible-exposed-infected-recovered (SEIR) model. The novel map represents Covid-19 discrete-time dynamics standing for the infected, cumulative infected and vaccinated populations. The simplicity of the discrete description allows the analytical calculation of useful information to evaluate the epidemic stage and to support decision making. In this regard, it should be pointed out the estimation of the number death cases and the herd immunization point. Numerical simulations show the model capacity to describe Covid-19 dynamics properly representing real data and describing different scenario patterns. Real data of Germany, Italy and Brazil are of concern to verify the model ability to describe Covid-19 dynamics. The model showed to be useful to describe the epidemic evolution and the effect of vaccination, being able to predict different pandemic scenarios.