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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%, 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.

Wir nutzen ein detailliertes agentenbasiertes Simulationsmodell, um den Einfluss von höheren Homeoffice-Quoten und Schulschließungen auf den Verlauf der Covid-19-Pandemie bis Ende Februar 2021 abzuschätzen. Ausgehend vom derzeitigen Niveau von 25% würde eine dauerhafte Erhöhung der Homeoffice-Quote um 10 Prozentpunkte ab Ende Januar dazu führen, dass die Zahl der Neuinfektionen Ende Februar um gut ein Viertel niedriger wäre. Der Infektionszahlen bremsende Effekt von Schul- und Kitaschließungen rührt zu großen Teilen daher, dass mindestens ein Elternteil zu Hause bleiben muss.