To ensure the robustness of our results, we investigated the relationship between various environmental variables (climate, host susceptibility to COVID-19, international human mobility, and socioeconomic factors) and the number of COVID-19 cases (per 1 million population) using the two different approaches: conventional multiple linear regression and random forest, which is a machine-learning model [15]. We separately modeled the cumulative number of COVID-19 cases (per 1 million population) in successive periods from December 2019 to June 30, 2020.