COVID-19 dynamics considering the influence of hospital infrastructure: an investigation into Brazilian scenarios

• Published in: Nonlinear dynamics Vol. 106; no. 2; pp. 1325 - 1346
• Main Authors: Pacheco, Pedro M. C. L., Savi, Marcelo A., Savi, Pedro V.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.10.2021; Springer Nature B.V
• Subjects: Automotive Engineering; Calibration; Classical Mechanics; Control; Coronaviruses; COVID-19; Disease transmission; Dynamical Systems; Engineering; Infrastructure; Mathematical models; Mechanical Engineering; Original Paper; Outbreaks; Public health; Simulation; System dynamics; Vibration; Viral diseases; Brazil; COVID-19; NCoV; Nonlinear dynamics; Mathematical models; Population dynamics; Coronavirus
• ISSN: 0924-090X; 1573-269X; 1573-269X
• DOI: 10.1007/s11071-021-06323-4

COVID-19 dynamics is one of the most relevant subjects nowadays, and, in this regard, mathematical modeling and numerical simulations are of special interest. This paper describes COVID-19 dynamics based on a novel version of the susceptible–exposed–infectious–removed model. Removed population is split into recovered and death populations allowing a better comprehension of real situations. Besides, the 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, Brazil outbreak is of concern, calibrating the model and developing numerical simulations. Results show several scenarios highlighting the importance of social isolation and hospital infrastructure. System dynamics has a strong sensitivity to transmission rate showing the importance of numerical simulations to guide public health decision strategies. Results also show that complex dynamical responses can emerge due to the oscillations of the transmission rate, being associated with distinct infection subsequent waves.