Non-pharmaceutical interventions (NPIs) are important to mitigate the spread of infectious diseases as long as no vaccination or outstanding medical treatments are available. We assess the effectiveness of the sets of non-pharmaceutical interventions that were in place during the course of the Coronavirus disease 2019 (Covid-19) pandemic in Germany. Our results are based on hybrid models, combining SIR-type models on local scales with spatial resolution. In order to account for the age-dependence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we include realistic prepandemic and recently recorded contact patterns between age groups. The implementation of non-pharmaceutical interventions will occur on changed contact patterns, improved isolation, or reduced infectiousness when, e.g., wearing masks. In order to account for spatial heterogeneity, we use a graph approach and we include high-quality information on commuting activities combined with traveling information from social networks. The remaining uncertainty will be accounted for by a large number of randomized simulation runs. Based on the derived factors for the effectiveness of different non-pharmaceutical interventions over the past months, we provide different forecast scenarios for the upcoming time.

只要没有疫苗接种或有效的医疗方法，非药物干预措施 (NPI) 对于减缓传染病的传播就非常重要。我们评估了德国 2019 年冠状病毒病 (Covid-19) 大流行期间采取的一系列非药物干预措施的有效性。我们的结果基于混合模型，将局部尺度上的 SIR 型模型与空间分辨率相结合。为了解释严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 的年龄依赖性，我们纳入了实际的流行病前和最近记录的年龄组之间的接触模式。非药物干预措施的实施将发生在改变接触模式、改善隔离或减少戴口罩等传染性时。为了考虑空间异质性，我们使用图形方法，并将通勤活动的高质量信息与社交网络的旅行信息相结合。剩余的不确定性将通过大量随机模拟运行来解释。根据过去几个月不同非药物干预措施有效性的推导因素，我们为未来提供了不同的预测情景。