Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America

Carlos Martin-Barreiro; Xavier Cabezas; Víctor Leiva; Pedro Ramos-De Santis; John A. Ramirez-Figueroa; Erwin J. Delgado; Carlos Martin-Barreiro; Xavier Cabezas; Víctor Leiva; Pedro Ramos-De Santis; John A. Ramirez-Figueroa; Erwin J. Delgado

doi:10.3934/math.20231155

AIMS Mathematics

2023, Volume 8, Issue 10: 22693-22713. doi: 10.3934/math.20231155

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Research article

Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America

1.
Facultad de Ciencias Naturales y Matemáticas, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador
2.
Centro de Estudios e Investigaciones Estadísticas, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador
3.
Escuela de Ingeniería Industrial, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile

Received: 25 April 2023 Revised: 05 June 2023 Accepted: 15 June 2023 Published: 17 July 2023
MSC : 62H25, 62H30

Many studies have been performed in different regions of the world as a result of the COVID-19 pandemic. In this work, we perform a statistical study related to the number of vaccinated cases and the number of deaths due to COVID-19 in ten South American countries. Our objective is to group countries according to the aforementioned variables. Once the groups of countries are built, they are characterized based on common properties of countries in the same group and differences between countries that are in different groups. Countries are grouped using principal component analysis and K-means analysis. These methods are combined in a single procedure that we propose for the classification of the countries. Regarding both variables, the countries were classified into three groups. Political decisions, availability of resources, bargaining power with suppliers and health infrastructure among others are some of the factors that can affect both the vaccination process and the timely care of infected people to avoid death. In general, the countries acted in a timely manner in relation to the vaccination of their citizens with the exception of two countries. Regarding the number of deaths, all countries reached peaks at some point in the study period.
- clustering analysis,
- data science,
- disjoint PCA,
- K-means analysis,
- multivariate statistical analysis,
- $\texttt{R}$ software,
- SARS-Cov2,
- unsupervised methods
Citation: Carlos Martin-Barreiro, Xavier Cabezas, Víctor Leiva, Pedro Ramos-De Santis, John A. Ramirez-Figueroa, Erwin J. Delgado. Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America[J]. AIMS Mathematics, 2023, 8(10): 22693-22713. doi: 10.3934/math.20231155

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Abstract

Many studies have been performed in different regions of the world as a result of the COVID-19 pandemic. In this work, we perform a statistical study related to the number of vaccinated cases and the number of deaths due to COVID-19 in ten South American countries. Our objective is to group countries according to the aforementioned variables. Once the groups of countries are built, they are characterized based on common properties of countries in the same group and differences between countries that are in different groups. Countries are grouped using principal component analysis and K-means analysis. These methods are combined in a single procedure that we propose for the classification of the countries. Regarding both variables, the countries were classified into three groups. Political decisions, availability of resources, bargaining power with suppliers and health infrastructure among others are some of the factors that can affect both the vaccination process and the timely care of infected people to avoid death. In general, the countries acted in a timely manner in relation to the vaccination of their citizens with the exception of two countries. Regarding the number of deaths, all countries reached peaks at some point in the study period.

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