Coronavirus Disease 2019 (COVID-19) Dynamics Considering the Influence of Hospital Infrastructure

This paper deals with the mathematical modeling and numerical simulations related to the coronavirus dynamics. A description is developed based on the framework of susceptible-exposed-infectious-removed model. Removed population is split into recovered and death populations allowing a better comprehension of real situations. Besides, total population is reduced based on the number of deaths. Hospital infrastructure is also included into the mathematical description allowing the consideration of collapse scenarios. Initially, a model verification is carried out calibrating system parameters with data from China outbreak that is considered a benchmark due the availability of data for the entire cycle. Afterward, numerical simulations are performed to analyze COVID-19 dynamics in Brazil. Results show several scenarios showing the importance of social isolation. System dynamics has a strong sensitivity to transmission rate showing the importance of numerical simulations to guide public health decision strategies.