Characterizing the Dynamics of Covid-19 Based on Data - Isea, Raúl (Journal of Current Viruses and Treatment Methodologies, 2021)
The objective of this paper is to apply datadriven discovery of dynamics modeling to obtain a system of differential equations that allows us to describe the transmission dynamics of Covid-19, based on the number of confirmed cases and deaths reported daily. This methodology was applied in four different countries: Brazil, Colombia, Venezuela, and the United States. The main advantage is that only one differential equation is needed to characterize the dynamic of Covid-19 without any mathematical assumption.
Keywords: Covid-19; Data driven; SINDy; Model; SARS-CoV-2.