Attacking the Covid-19 with the Ising-model and the Fermi-Dirac Distribution Function

We employ a spin $S$ = 1/2 Ising-like model and a Fermi-Dirac-like function to describe the spread of Covid-19. Our analysis, using the available official infections rate data reveals: $i$) that the epidemic curves, i.e., the number of reported cases $versus$ time, is well-described by a Gaussian function; $ii$) that the temporal evolution of the cumulative number of infected people follows a distorted Fermi-Dirac-like distribution function; $iii$) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an $interacting$ parameter, which emulates the contact between infected and non-infected people. An analysis of the epidemic curves for Ebola, SARS, and Influenza A/H1N1 is also presented and described by a Gaussian function as well. Our findings demonstrate the universal character of well-established concepts in condensed matter Physics and their applications in different areas.