Using hierarchical clustering analysis to evaluate COVID-19 pandemic preparedness and performance in 180 countries in 2020.

ABSTRACT:

Objective

To rank and score 180 countries according to COVID-19 cases and fatality in 2020 and compare the results to existing pandemic vulnerability prediction models and results generated by standard epidemiological scoring techniques.

Setting

One hundred and eighty countries' patients with COVID-19 and fatality data representing the healthcare system preparedness and performance in combating the pandemic in 2020.

Design

Using the retrospective daily COVID-19 data in 2020 broken into 24 half-month periods, we applied unsupervised machine learning techniques, in particular, hierarchical clustering analysis to cluster countries into five groups within each period according to their cumulative COVID-19 fatality per day over the year and cumulative COVID-19 cases per mi

SUBMITTER: Sadeghi B 

PROVIDER: S-EPMC8578186 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature