Background: The novel coronavirus disease 2019 (COVID-19) is an infectious disease that presents an urgent challenge to global health and economy.

Objectives: To assess the effects of population median age and mean ambient temperature on the COVID-19 global pandemic burden.

Methods: We used databases from open access public domains to record population median age, mean ambient temperature, and the numbers of COVID-19 cases and deaths on days 14 and 28 from the pandemic outbreak for each country in the world. We then calculated the correlation between these parameters.

Results: The analysis included 202 countries. A univariate analysis showed that population median age significantly correlated with the cumulative number of cases and deaths, while mean ambient temperature showed a significant inverse correlation with the cumulative number of deaths on days 14 and 28 from the epidemic outbreak. After a multivariate logistic regression analysis only population median age retained its statistically significant correlation.

Conclusions: Country population median age significantly correlated with COVID-19 pandemic burden while mean ambient temperature shows a significant inverse correlation only in univariate analysis. Countries with older populations encountered a heavier burden from the COVID-19 pandemic. This information may be valuable for health systems in planning strategies for combating this global health hazard.