We analyze the impact of different designs of COVID-19-related lockdown policies on economic loss and mortality using a micro-level simulation model, which combines a multi-sectoral closed economy with an epidemic transmission model. In particular, the model captures explicitly the (stochastic) effect of interactions between heterogeneous agents during different economic activities on virus transmissions. The empirical validity of the model is established using data on economic and pandemic dynamics in Germany in the first 6 months after the COVID-19 outbreak. We show that a policy-inducing switch between a strict lockdown and a full opening-up of economic activity based on a high incidence threshold is strictly dominated by alternative policies, which are based on a low incidence threshold combined with a light lockdown with weak restrictions of economic activity or even a continuous weak lockdown. Furthermore, also the ex ante variance of the economic loss suffered during the pandemic is substantially lower under these policies. Keeping the other policy parameters fixed, a variation of the consumption restrictions during the lockdown induces a trade-off between GDP loss and mortality. Furthermore, we study the robustness of these findings with respect to alternative pandemic scenarios and examine the optimal timing of lifting containment measures in light of a vaccination rollout in the population.

我们使用微观模拟模型分析了与 COVID-19 相关的封锁政策的不同设计对经济损失和死亡率的影响，该模型将多部门封闭经济与流行病传播模型相结合。特别是，该模型明确捕捉了不同经济活动期间异质主体之间相互作用对病毒传播的（随机）影响。该模型的实证有效性是利用 COVID-19 爆发后头 6 个月德国的经济和大流行动态数据建立的。我们表明，基于高发生率阈值的严格封锁和全面开放经济活动之间的政策诱导转换严格由替代政策主导，这是基于低发病率门槛，结合轻度封锁和对经济活动的弱限制，甚至是持续的弱封锁。此外，在这些政策下，大流行期间遭受的经济损失的事前差异也大大降低。保持其他政策参数不变，封锁期间消费限制的变化会导致 GDP 损失和死亡率之间的权衡。此外，我们研究了这些发现在替代大流行情景方面的稳健性，并根据人群中疫苗接种的情况检查了解除遏制措施的最佳时机。保持其他政策参数不变，封锁期间消费限制的变化会导致 GDP 损失和死亡率之间的权衡。此外，我们研究了这些发现在替代大流行情景方面的稳健性，并根据人群中疫苗接种的情况检查了解除遏制措施的最佳时机。保持其他政策参数不变，封锁期间消费限制的变化会导致 GDP 损失和死亡率之间的权衡。此外，我们研究了这些发现在替代大流行情景方面的稳健性，并根据人群中疫苗接种的情况检查了解除遏制措施的最佳时机。