Clustering Countries in the Context of the Pandemic and Underlying Conditions

Abstract:

The COVID-19 pandemic has revealed the state of underlying conditions of countries in terms of health system, sanitary infrastructure, governance, among others. This study aims to classify countries using COVID-19-related variables such as the lethality rate, the contagion growth rate, the stringency index, and underlying conditions of countries directly related to COVID-19 such as access to clean water, hospital beds per 10000 inhabitants, government effectiveness index, population older than 65 years old and economic growth rate. To determine the clusters of a set of countries from all continents (29 from Africa, 35 from Asia, 35 from Europe, 11 from North America, 2 from Oceania and 8 from South America), the k-means partitioning method is used. This approach consists in constructing partitions and evaluate their intra-class and inter-class similarity. Based on the results, three clusters are identified: i. Severely affected countries with high stringency and moderate capacity, ii. Moderately affected countries with moderate stringency and high capacity and iii. Severely affected countries with low stringency but low capacity.

Año de publicación:

2022

Keywords:

Fuente:

google