TY - JOUR
T1 - Statistical characterization of vaccinated cases and deaths due to COVID-19
T2 - methodology and case study in South America
AU - Martin-Barreiro, Carlos
AU - Cabezas, Xavier
AU - Leiva, Víctor
AU - Santis, Pedro Ramos De
AU - Ramirez-Figueroa, John A.
AU - Delgado, Erwin J.
N1 - Publisher Copyright:
© 2023 the Author(s), licensee AIMS Press.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - K-means analysis
KW - R software
KW - SARS-Cov2
KW - clustering analysis
KW - data science
KW - disjoint PCA
KW - multivariate statistical analysis
KW - unsupervised methods
UR - http://www.scopus.com/inward/record.url?scp=85164912001&partnerID=8YFLogxK
U2 - 10.3934/math.20231155
DO - 10.3934/math.20231155
M3 - Article
AN - SCOPUS:85164912001
SN - 2473-6988
VL - 8
SP - 22693
EP - 22713
JO - AIMS Mathematics
JF - AIMS Mathematics
IS - 10
ER -