  In order to slow the spread of the CoViD-19 pandemic, governments around the
world have enacted a wide set of policies limiting the transmission of the
disease. Initially, these focused on non-pharmaceutical interventions; more
recently, vaccinations and large-scale rapid testing have started to play a
major role. The objective of this study is to explain the quantitative effects
of these policies on determining the course of the pandemic, allowing for
factors like seasonality or virus strains with different transmission profiles.
To do so, the study develops an agent-based simulation model, which is
estimated using data for the second and the third wave of the CoViD-19 pandemic
in Germany. The paper finds that during a period where vaccination rates rose
from 5% to 40%, large-scale rapid testing had the largest effect on reducing
infection numbers. Frequent large-scale rapid testing should remain part of
strategies to contain CoViD-19; it can substitute for many non-pharmaceutical
interventions that come at a much larger cost to individuals, society, and the
economy.
