Abstract

MECIO PADRON, Daniel; BAYOLO SOLER, Gabriela  and  MARRERO SEVERO, Aymée. Analysis of Mathematical Model with risk perception for the CoVid19. Results for Cuba. RCIM [online]. 2020, vol.12, n.2  Epub Dec 01, 2020. ISSN 1684-1859.

In Epidemiology, Population Models have played an important role, dividing the study population into subpopulations according to the attributes that distinguish them, allowing the dynamics of social contagion of a given disease to be represented, especially at times of epidemic outbreak. This work explains how the transmission of diseases is represented through mathematical models defined by differential equations.

In this proposal, a mathematical model defined by differential equations is formulated to represent the transmission of SarsCov2, distinguishing between symptomatic and asymptomatic infected populations of CoVid19, with functions that simulate government and individual actions in the face of risk perception. An analysis of the results obtained in Cuba is also presented.

Keywords : population mathematical model; SarsCov2; CoVid19; epidemic outbreak; active cases; prevalence; epidemilogical classes.

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