Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America
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 countrie...
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-07-01
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| Series: | AIMS Mathematics |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.20231155?viewType=HTML |
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| author | Carlos Martin-Barreiro Xavier Cabezas Víctor Leiva Pedro Ramos-De Santis John A. Ramirez-Figueroa Erwin J. Delgado |
| author_facet | Carlos Martin-Barreiro Xavier Cabezas Víctor Leiva Pedro Ramos-De Santis John A. Ramirez-Figueroa Erwin J. Delgado |
| author_sort | Carlos Martin-Barreiro |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T20:52:37Z |
| format | Article |
| id | doaj.art-d82d8c9d8e5c47b4a97188bf2028a5d1 |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-03-12T20:52:37Z |
| publishDate | 2023-07-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-d82d8c9d8e5c47b4a97188bf2028a5d12023-08-01T01:26:06ZengAIMS PressAIMS Mathematics2473-69882023-07-01810226932271310.3934/math.20231155Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South AmericaCarlos Martin-Barreiro0Xavier Cabezas1Víctor Leiva 2Pedro Ramos-De Santis3John A. Ramirez-Figueroa4Erwin J. Delgado51. Facultad de Ciencias Naturales y Matemáticas, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador1. 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, Ecuador3. Escuela de Ingeniería Industrial, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile1. Facultad de Ciencias Naturales y Matemáticas, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, Ecuador1. 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, Ecuador1. Facultad de Ciencias Naturales y Matemáticas, Escuela Superior Politécnica del Litoral ESPOL, Guayaquil 090902, EcuadorMany 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.https://www.aimspress.com/article/doi/10.3934/math.20231155?viewType=HTMLclustering analysisdata sciencedisjoint pcak-means analysismultivariate statistical analysis$\texttt{r}$ softwaresars-cov2unsupervised methods |
| spellingShingle | 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 AIMS Mathematics clustering analysis data science disjoint pca k-means analysis multivariate statistical analysis $\texttt{r}$ software sars-cov2 unsupervised methods |
| title | Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America |
| title_full | Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America |
| title_fullStr | Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America |
| title_full_unstemmed | Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America |
| title_short | Statistical characterization of vaccinated cases and deaths due to COVID-19: methodology and case study in South America |
| title_sort | statistical characterization of vaccinated cases and deaths due to covid 19 methodology and case study in south america |
| topic | clustering analysis data science disjoint pca k-means analysis multivariate statistical analysis $\texttt{r}$ software sars-cov2 unsupervised methods |
| url | https://www.aimspress.com/article/doi/10.3934/math.20231155?viewType=HTML |
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