Your browser doesn't support javascript.
loading
A multi-group SEIRA model for the spread of COVID-19 among heterogeneous populations.
Contreras, Sebastián; Villavicencio, H Andrés; Medina-Ortiz, David; Biron-Lattes, Juan Pablo; Olivera-Nappa, Álvaro.
Afiliação
  • Contreras S; Laboratory for Rheology and Fluid Dynamics, Universidad de Chile, Beauchef 850, Santiago 8370448, Chile.
  • Villavicencio HA; Centre for Biotechnology and Bioengineering, Universidad de Chile, Beauchef 851, Santiago 8370448, Chile.
  • Medina-Ortiz D; Centre for Biotechnology and Bioengineering, Universidad de Chile, Beauchef 851, Santiago 8370448, Chile.
  • Biron-Lattes JP; Centre for Biotechnology and Bioengineering, Universidad de Chile, Beauchef 851, Santiago 8370448, Chile.
  • Olivera-Nappa Á; Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Chaos Solitons Fractals ; 136: 109925, 2020 Jul.
Article em En | MEDLINE | ID: mdl-32501373
ABSTRACT
The outbreak and propagation of COVID-19 have posed a considerable challenge to modern society. In particular, the different restrictive actions taken by governments to prevent the spread of the virus have changed the way humans interact and conceive interaction. Due to geographical, behavioral, or economic factors, different sub-groups among a population are more (or less) likely to interact, and thus to spread/acquire the virus. In this work, we present a general multi-group SEIRA model for representing the spread of COVID-19 among a heterogeneous population and test it in a numerical case of study. By highlighting its applicability and the ease with which its general formulation can be adapted to particular studies, we expect our model to lead us to a better understanding of the evolution of this pandemic and to better public-health policies to control it.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article