  Coronavirus disease 2019 (COVID-19) is associated with a very high number of
casualties in the general population. Assessing the exact magnitude of this
number is a non-trivial problem, as relying only on officially reported
COVID-19 associated fatalities runs the risk of incurring in several kinds of
biases. One of the ways to approach the issue is to compare overall mortality
during the pandemic with expected mortality computed using the observed
mortality figures of previous years. In this paper, we build on existing
methodology and propose two ways to compute expected as well as excess
mortality, namely at the weekly and at the yearly level. Particular focus is
put on the role of age, which plays a central part in both COVID-19-associated
and overall mortality. We illustrate our methods by making use of
age-stratified mortality data from the years 2016 to 2020 in Germany to compute
age group-specific excess mortality during the COVID-19 pandemic in 2020.
