Mathematical modeling to mitigate the effects of COVID-19 in the tourism sector in Peru
Descripción del Articulo
Based on the need to make accurate decisions in the face of the COVID-19 pandemic in Peru, pandemic in Peru, specifically for the recovery of the tourism sector. For this purpose, a characterization of the behavior of the pandemic was carried out in the first three months of its development, based o...
Autores: | , , , |
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Formato: | artículo |
Fecha de Publicación: | 2020 |
Institución: | Universidad Le Cordon Bleu |
Repositorio: | Revistas - Universidad Le Cordon Bleu |
Lenguaje: | español |
OAI Identifier: | oai:ojs2.52.234.130.152:article/173 |
Enlace del recurso: | https://revistas.ulcb.edu.pe/index.php/REVISTAULCB/article/view/173 |
Nivel de acceso: | acceso abierto |
Materia: | COVID-19, tourism, mathematical modeling, decision-making COVID-19, turismo, modelación matemática, toma de decisiones |
Sumario: | Based on the need to make accurate decisions in the face of the COVID-19 pandemic in Peru, pandemic in Peru, specifically for the recovery of the tourism sector. For this purpose, a characterization of the behavior of the pandemic was carried out in the first three months of its development, based on the analysis of trends and the determination of the effective reproduction number (Rt) from statistical-mathematical methods. A variant of the SIR mathematical model was applied to forecast the possible evolution of the pandemic. This model was adjusted with the GlobalSearch optimization strategy of the MATLAB software. His solution used the MATLAB function ode23tb, which uses a combined Runge-Kutta algorithm with a trapezoidal rule algorithm. With the application of the Kaizen strategy as a means of continuous improvement, a set of actions were proposed that could be carried out today and that would allow the recovery of the tourism sector to be faced in a better situation. The behavior of the Rt and the simulation carried out showed that the mitigation measures established are insufficient to substantially reduce the impact of the pandemic, predicting that, by the end of 2020, the number of infected could reach the figure of 840 thousand and the deaths would exceed the 44 thousand. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).