If less strict interventions are in favor, substantially increased testing rates are needed to avoid overall higher infection dynamics. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable. A further key contributor is the potential delay of the intervention implementation. In contrast, the negative effect of less strict interventions can be overcome by high commuter testing rates. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. We find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario. The virus dynamics in the regions (German counties) are initialized randomly with incidences between 75 and 150 weekly new cases per 100,000 inhabitants (red zones) or below (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20% of all counties). We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type, metapopulation model with particular focus on commuter testing. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests. In addition, we face the spread of novel variants. Despite the vaccination process in Germany, a large share of the population is still susceptible to SARS-CoV-2.
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