We revisit well-established concepts of epidemiology, the Ising-model, and percolation theory. Also, we employ a spin = 1/2 Ising-like model and a (logistic) Fermi-Dirac-like function to describe the spread of Covid-19. Our analysis show that: () in many cases the epidemic curve can be described by a Gaussian-type function; () the temporal evolution of the accumulative number of infections and fatalities follow a logistic function; () the key role played by the quarantine to block the spread of Covid-19 in terms of an interacting parameter between people. In the frame of elementary percolation theory, we show that: () the percolation probability can be associated with the probability of a person being infected with Covid-19; () the concepts of blocked and non-blocked connections can be associated, respectively, with a person respecting or not the social distancing. Yet, we make a connection between epidemiological concepts and well-established concepts in condensed matter Physics.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006539 | PMC |
| http://dx.doi.org/10.1016/j.physa.2021.125963 | DOI Listing |
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