Modelling the spread of covid-19 in the capital of Brazil using numerical solution and cellular automata. (October 2021)

• Record Type: Journal Article
• Authors: Cavalcante, André Luís Brasil; Borges, Lucas Parreira de Faria; Lemos, Moisés Antônio da Costa; Farias, Márcio Muniz de; Carvalho, Hervaldo Sampaio
• Is Part Of: Computational biology and chemistry. Volume 94(2021)
• Publication Date: 2021-10
• Subjects: COVID-19 -- SIR model -- SEIRD model -- Cellular automata -- Federal District; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2021.107554
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: The Cellular Automata model organically clarify the spread of COVID-19. This research predicts the spread of COVID-19 in confined spaces with random movements of people. Numerical open-code modeling was developed. The model supports the decision-maker in small places (i.e., supermarkets). Abstract: The novel coronavirus disease 2019 (COVID-19) still challenges researchers due to its spread and deaths. Hence, the classical epidemic SIR and SEIRD models inspired by the epidemic's outbreak are widely used to predict the evolution of the disease. In addition to classical approaches, describing complex phenomena through Cellular Automata (CA) is a highly effective way to understand the iterations on a populated system. The present research analyzed the usage of CA to generate an epidemic-computational model from a micro perspective based on parameters obtained through a statistical fit from a macro perspective. After validating SIR and SEIRD models with the government official data for Brasilia, Brazil, the authors applied the obtained parameters to the Cellular Automata model. The CA model simulated the spread of the virus from infected to uninfected people in a restrained environment (i.e., a supermarket) under several varied conditions applying an approach never adopted before. The manner of applying CA in this research proved to represent an essential tool in predicting the spread of the coronavirus in confined spaces with random movements of people. The CA numerical open-source presented has the purpose of clarifying how the spread occurs not only as a mathematical curve but in an organic way. The numerical simulations from the CA model allowed the authors to conclude that markets and stores are relevant places where might be infections. Thus, every local store and the market owner should reason about the aspects that could avoid the spread of the disease, coming up with efficient solutions. Each environment has specific features that only those who know them are the ones capable of managing.