Modeling the Evolution of SARS-CoV-2 Using a Fractional-Order SIR Approach

To show the potential of non-commensurable fractional-order dynamical systems in modeling epidemiological phenomena, we will adjust parameters a fractional generalization SIR model to describe population distributions generated by SARS-CoV-2 France and Colombia. Despite completely different contexts both countries, see how system presented here manages adequately them thanks flexibility provided differential equations. The data for Colombia were obtained from records published Colombian Ministry Information Technology Communications March 24 July 10, 2020. Those taken information Solidarity Health May 1 September 6, As methodology implemented this study, conducted an exploratory analysis focused on solving means transformation method. In addition, adjusted using sophisticated optimization method known as Bound Optimization BY Quadratic Approximation (BOBYQA) algorithm. According results, maximum error percentage evolution susceptible, infected, recovered populations was 0.05%, 19%, 6%, respectively, while that 0.003%, 38%, respectively. This considered which disease began spread human intervention did not imply substantial change community.