Modelos matemáticos convencionales para la evaluación de la dinámica del brote de CoViD-19 en la Provincia de Loja

Abstract

Abstract: Mathematical models have become one of the most important and democratic tools available worldwide for predicting the evolution of COVID-19 and determining the impact of social measures and biosafety actions to control the pandemic. Most of them are simple and elegant models formulated almost a century ago. Here, we propose the use of the logistic model and the Hill equation to fit the confirmed cases in the Province of Loja (Ecuador). These models are the solution to differential equations, which describe the dynamics of infections in a closed population with N confirmed cases. The database was obtained from infographics reported by the National Risk Management Service. The period consisted of 307 data points, during the first outbreak in Ecuador, which occurred from February 29, 2020, to December 31, 2020. The coefficient of determination (푅2) is 0.987613, 0.997946, 0.995193, and 0.99883 for the exponential model, simple logistic model, differential logistic model, and Hill model, respectively. These results indicate that the models fit well, but the Hill model is the best.