Spread of Epidemic Disease on Edge-Weighted Graphs from a Database: A Case Study of COVID-19
Archivos
Fecha
2021
Profesor Guía
Formato del documento
Articulo
ORCID Autor
Título de la revista
ISSN de la revista
Título del volumen
Editor
MDPI
Ubicación
ISBN
ISSN
item.page.issne
item.page.doiurl
Facultad
Facultad de Medicina
Departamento o Escuela
Escuela de Enfermeria
Determinador
Recolector
Especie
Nota general
Resumen
The understanding of infectious diseases is a priority in the field of public health. This has generated the inclusion of several disciplines and tools that allow for analyzing the dissemination of infectious diseases. The aim of this manuscript is to model the spreading of a disease in a population that is registered in a database. From this database, we obtain an edge-weighted graph. The spreading was modeled with the classic SIR model. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics. Moreover, a deterministic approximation is provided. With database COVID-19 from a city in Chile, we analyzed our model with relationship variables between people. We obtained a graph with 3866 vertices and 6,841,470 edges. We fitted the curve of the real data and we have done some simulations on the obtained graph. Our model is adjusted to the spread of the disease. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics, in this case with real data of COVID-19. This valuable information allows us to also include/understand the networks of dissemination of epidemics diseases as well as the implementation of preventive measures of public health. These findings are important in COVID-19’s pandemic context.
Descripción
Lugar de Publicación
Auspiciador
Palabras clave
EDGE-WEIGHTED GRAPH, SIR MODEL, NETWORK, DISEASE, COVID-19
Licencia
Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).