The spreading of Covid-19 in Mexico: A diffusional approach
In this work, we analyze the spreading of Covid-19 in Mexico using the spatial SEIRD epidemiologic model. We use the information of the 32 regions (States) that conform the country, such as population density, verified infected cases, and deaths in each State. We extend the SEIRD compartmental epide...
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doaj-9a305414019f4abb9e2280e484bc15cb2021-07-23T04:48:41ZengElsevierResults in Physics2211-37972021-08-0127104555The spreading of Covid-19 in Mexico: A diffusional approachCarlos G. Aguilar-Madera0Gilberto Espinosa-Paredes1E.C. Herrera-Hernández2Jorge A. Briones Carrillo3J. Valente Flores-Cano4Víctor Matías-Pérez5Universidad Autónoma de Nuevo León, Facultad de Ciencias de la Tierra, C.P. 67700, Linares, MexicoUniversidad Autónoma Metropolitana-Iztapalapa, Área de Ingeniería en Recursos Energéticos, CDMX 09340, Mexico; Corresponding author.Centro de Investigación y Estudios de Posgrado, Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, Av. Dr. Manuel Nava 6, Zona Universitaria, 78210 San Luis Potosí, MexicoUniversidad Autónoma de Nuevo León, Facultad de Ciencias de la Tierra, C.P. 67700, Linares, MexicoUniversidad Autónoma de Nuevo León, Facultad de Ciencias de la Tierra, C.P. 67700, Linares, MexicoUniversidad Autónoma de Nuevo León, Facultad de Ciencias de la Tierra, C.P. 67700, Linares, MexicoIn this work, we analyze the spreading of Covid-19 in Mexico using the spatial SEIRD epidemiologic model. We use the information of the 32 regions (States) that conform the country, such as population density, verified infected cases, and deaths in each State. We extend the SEIRD compartmental epidemiologic with diffusion mechanisms in the exposed and susceptible populations. We use the Fickian law with the diffusion coefficient proportional to the population density to encompass the diffusion effects. The numerical results suggest that the epidemiologic model demands time-dependent parameters to incorporate non-monotonous behavior in the actual data in the global dynamic. The diffusional model proposed in this work has great potential in predicting the virus spreading on different scales, i.e., local, national, and between countries, since the complete reduction in people mobility is impossible.http://www.sciencedirect.com/science/article/pii/S2211379721006574CoronavirusCovid-19MexicoSpreadingSEIRD modelDiffusion |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Carlos G. Aguilar-Madera Gilberto Espinosa-Paredes E.C. Herrera-Hernández Jorge A. Briones Carrillo J. Valente Flores-Cano Víctor Matías-Pérez |
spellingShingle |
Carlos G. Aguilar-Madera Gilberto Espinosa-Paredes E.C. Herrera-Hernández Jorge A. Briones Carrillo J. Valente Flores-Cano Víctor Matías-Pérez The spreading of Covid-19 in Mexico: A diffusional approach Results in Physics Coronavirus Covid-19 Mexico Spreading SEIRD model Diffusion |
author_facet |
Carlos G. Aguilar-Madera Gilberto Espinosa-Paredes E.C. Herrera-Hernández Jorge A. Briones Carrillo J. Valente Flores-Cano Víctor Matías-Pérez |
author_sort |
Carlos G. Aguilar-Madera |
title |
The spreading of Covid-19 in Mexico: A diffusional approach |
title_short |
The spreading of Covid-19 in Mexico: A diffusional approach |
title_full |
The spreading of Covid-19 in Mexico: A diffusional approach |
title_fullStr |
The spreading of Covid-19 in Mexico: A diffusional approach |
title_full_unstemmed |
The spreading of Covid-19 in Mexico: A diffusional approach |
title_sort |
spreading of covid-19 in mexico: a diffusional approach |
publisher |
Elsevier |
series |
Results in Physics |
issn |
2211-3797 |
publishDate |
2021-08-01 |
description |
In this work, we analyze the spreading of Covid-19 in Mexico using the spatial SEIRD epidemiologic model. We use the information of the 32 regions (States) that conform the country, such as population density, verified infected cases, and deaths in each State. We extend the SEIRD compartmental epidemiologic with diffusion mechanisms in the exposed and susceptible populations. We use the Fickian law with the diffusion coefficient proportional to the population density to encompass the diffusion effects. The numerical results suggest that the epidemiologic model demands time-dependent parameters to incorporate non-monotonous behavior in the actual data in the global dynamic. The diffusional model proposed in this work has great potential in predicting the virus spreading on different scales, i.e., local, national, and between countries, since the complete reduction in people mobility is impossible. |
topic |
Coronavirus Covid-19 Mexico Spreading SEIRD model Diffusion |
url |
http://www.sciencedirect.com/science/article/pii/S2211379721006574 |
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