This research builds upon the previous publications claiming that the male sex population and both sex individuals of advanced age are more susceptible to COVID-19's risks. Relations between sex and age gradients are explored analytically based upon the proposed log-polynomial regression model of COVID-19 mortality. This model enables predicting mortality risk at any arbitrary age, as well as the derivation of several useful secondary metrics:•Sex differential: a ratio of male-to-female death

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... sks for a given age group.•Age parity: age at which both sexes have an equal vulnerability.•Age lag: the number of years to subtract from a male's age to match a female's death risk.•Male equal risk age: male's age at which male's odds of dying from COVID-19 will equate female's given the cutoff age. These metrics allow solving such practical problems as, e.g., prioritizing vaccine based on COVID-19 mortality risk associated with sex and age. Modeling techniques, refined in the paper, are by no means unique to COVID-19 and would apply to analyses of other diseases.