Abstract
This article aims to calculate the COVID-19 Pandemic Vulnerability Index (COVID-19-PVI) across Brazilian municipalities, positing that vulnerability to the coronavirus is linked to socioeconomic disparities in this continental-sized country. From data collection on epidemiological, socioeconomic, demographic, and public health systems, it was possible to rank which features were most influential in the spread of COVID-19 using the artificial intelligence implicit in the boosting tree regression method. To ensure the robustness of the findings, this index is tested in Pearson correlations leading to conclusions about which regions were most vulnerable to the pandemic and its consequences, the importance of the spatial distribution of General Hospitals during the COVID-19 outbreak, and the influence of population density on the advancement of the coronavirus in the country.