SARS-CoV-2 multivariable representation in South American countries by using dynamic Biplot and ARIMA modeling infections and lethality

Authors

DOI:

https://doi.org/10.53591/easi.v1i2.1857

Keywords:

Coronavirus, COVID-19, ARIMA, Biplot

Abstract

The coronavirus (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus that has generated a global health crisis. On March 11, 2020, this disease was classified as a pandemic, the most affected regions were Latin America and the Caribbean, due to various factors such as population density, and incapacity in health systems, among others. In this study, a general analysis of the data on infections and deaths from ten South American countries will be carried out, to identify which country has best managed the pandemic according to its contagion and lethality results. A prediction was made for the number of infections and deaths caused by Covid-19, using data reported to the WHO (World Health Organization). The ARIMA model and the dynamic Biplot method were used for this study to represent the analysis. It was found that Peru has a high case fatality rate compared to the countries analyzed, and Peru has a higher number of deaths from the disease.

Author Biographies

Luis Pilacuan, Universidad de Salamanca. Salamanca, España

Ingeniero Industrial (2012). Facultad de Ingeniería Industrial. Universidad de Guayaquil. Ecuador

Master in Business Administration (2015). Escuela de Administración de Empresas. Escuela Superior Politécnica del Litoral. Ecuador

Beatriz Salmon, Universidad de Guayaquil. Guayaquil, Ecuador

Ingeniero Industrial. Facultad de Ingeniería Industrial, Universidad de Guayaquil. Guayaquil, Ecuador

Diana Gallegos-Zurita, Universidad de Guayaquil. Guayaquil, Ecuador

Electr. Eng. (2009) egresada de la ESPOL. M.Sc. en Enseñanza de la Física, ESPOL (2015). Actualmente, trabaja en la carrera de Telemática de la Universidad de Guayaquil (UG). Es investigadora en el área de Enseñanza de la Física (Facultad de Ingeniería Industrial-UG). Su trabajo de investigación está dirigido hacia la educación en ingeniería, mecánica, electricidad, y magnetismo.

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Published

2022-12-29

How to Cite

Pilacuan, L., Salmon, B., & Gallegos, D. (2022). SARS-CoV-2 multivariable representation in South American countries by using dynamic Biplot and ARIMA modeling infections and lethality. EASI: Engineering and Applied Sciences in Industry, 1(2), 46–52. https://doi.org/10.53591/easi.v1i2.1857

Issue

Vol. 1 No. 2 (2022): Production and operation management: social problem solving (July-December Issue)

Section

Research articles

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Copyright (c) 2022 Luis Pilacuan-Bonete, Beatriz Salmon-Cedeño, Diana Gallegos-Zurita

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