Lessons learned from the COVID-19 pandemic in Latin America: A Data Science standpoint

In the 21st century, the world has faced the devastating impacts of three acute respiratory diseases: Middle East respiratory Syndrome (MERS), Severe Acute respiratory Syndrome (SARS), and COVID-19, which evolved into a pandemic. These diseases have not only caused a large number of deaths but have also damaged the economies of the affected regions. Particularly, countries in the Latin American and Caribbean (LAC) region have faced additional challenges due to more significant social inequalities, limited access to Healthcare services, and precarious living conditions, and it is not clear how these challenges impacted the effects of the mitigation actions adopted by each country. However, this understanding is crucial to guide measures to mitigate Health and socioeconomic impacts if (or when) new acute respiratory diseases emerge, especially in these countries. A retrospective study was conducted to model the dynamics of variation in COVID-19 mortality in LAC countries and to analyze its association with vaccination strategies, containment measures, mobility restrictions, and socioeconomic factors. The study methodology applied clustering techniques that revealed two distinct clusters based on sociodemographic characteristics, followed by the application of XGBoost to model the dynamics of variation in deaths in the countries of each cluster over time. Finally, the SHAP Values technique was applied to understand the associations between mortality and factors such as vaccination, containment measures, and mobility restrictions. The study provides evidence that economic support and the completion of the vaccination scheme were especially relevant in reducing COVID-19 mortality. Two distinct groups of countries were detected, one characterized by a greater vulnerability. The most important interventions for understanding COVID-19 mortality varied between pre- and post-vaccination periods. In the pre-vaccination period, containment measures were the most important interventions for mortality in the less vulnerable countries, while population mobility was more important in the more vulnerable countries. In the post-vaccination period, vaccination coverage was the most important intervention for mortality in the less vulnerable countries, while containment measures impacted the more vulnerable countries.

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Publication Details

Journal
PLoS ONE
Published
2025-05-30
DOI
https://doi.org/10.1371/journal.pone.0324171
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.37
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article

Lessons learned from the COVID-19 pandemic in Latin America: A Data Science standpoint

J. Villar, Paula Maçaira, Fernanda Baião
1 citations
PLoS ONE
COVID-19 epidemiological studies
1.37
article

Lessons learned from the COVID-19 pandemic in Latin America: A Data Science standpoint

J. Villar, Paula Maçaira, Fernanda Baião
article en
1 citations

Abstract

In the 21st century, the world has faced the devastating impacts of three acute respiratory diseases: Middle East respiratory Syndrome (MERS), Severe Acute respiratory Syndrome (SARS), and COVID-19, which evolved into a pandemic. These diseases have not only caused a large number of deaths but have also damaged the economies of the affected regions. Particularly, countries in the Latin American and Caribbean (LAC) region have faced additional challenges due to more significant social inequalities, limited access to Healthcare services, and precarious living conditions, and it is not clear how these challenges impacted the effects of the mitigation actions adopted by each country. However, this understanding is crucial to guide measures to mitigate Health and socioeconomic impacts if (or when) new acute respiratory diseases emerge, especially in these countries. A retrospective study was conducted to model the dynamics of variation in COVID-19 mortality in LAC countries and to analyze its association with vaccination strategies, containment measures, mobility restrictions, and socioeconomic factors. The study methodology applied clustering techniques that revealed two distinct clusters based on sociodemographic characteristics, followed by the application of XGBoost to model the dynamics of variation in deaths in the countries of each cluster over time. Finally, the SHAP Values technique was applied to understand the associations between mortality and factors such as vaccination, containment measures, and mobility restrictions. The study provides evidence that economic support and the completion of the vaccination scheme were especially relevant in reducing COVID-19 mortality. Two distinct groups of countries were detected, one characterized by a greater vulnerability. The most important interventions for understanding COVID-19 mortality varied between pre- and post-vaccination periods. In the pre-vaccination period, containment measures were the most important interventions for mortality in the less vulnerable countries, while population mobility was more important in the more vulnerable countries. In the post-vaccination period, vaccination coverage was the most important intervention for mortality in the less vulnerable countries, while containment measures impacted the more vulnerable countries.

PLoS ONEVol. 20(5)
Pontifícia Universidade Católica do Rio de Janeiro (BR)
Good health and well-being
Openalex Percentile: Top 21%
COVID-19 epidemiological studies
1.37
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