In a recent study posted to the medRxiv* preprint server, a team of researchers predicts the evolution of coronavirus disease 2019 (COVID-19) mortality rates across countries using a biological science-guided machine learning-based approach. However, a study exploring multiple factors affecting COVID-19 mortality rates individually and interdependently is needed. In the current study, researchers used a novel Fast Fourier Transformation (FFT) driven machine-learning algorithm to analyze the publically available data of COVID-19 mortality rate from 141 countries. They assessed the impact of eight biological and socioeconomic factors such as alcohol consumption, diabetes prevalence, gross domestic product (GDP) per capita, the global health index, meat consumption, milk consumption, PM2.5, and population density on the COVID-19 mortality rates. The 141 countries assessed in the current study varied in size and population and spanned across five continents.