How does interconnectedness affect the course of a pandemic? What are the optimal containment policies in an economy with connected regions? We embed a spatial SIR model into a multi-sector quantitative trade model. We calibrate it to US states and the COVID-19 pandemic and find that interconnectedness increases the death toll by 146,200 lives. State-level policies that reduce within-state economic activity mitigate welfare losses by more than a uniform national policy or a policy that only reduces mobility between states. The optimal policy in mitigating welfare losses generated by the pandemic combines local within- and between-state restrictions and saves 289,300 lives, despite significantly exacerbating economic losses and imposing mobility restrictions across states. Different timing of policies across states is key to minimize welfare losses. States like South Carolina might have imposed internal lockdowns too early but travel restrictions too late.

相互联系如何影响大流行病的进程？在区域相连的经济体中，最佳遏制政策是什么？我们将空间 SIR 模型嵌入到多部门量化贸易模型中。我们根据美国各州和 COVID-19 大流行对其进行校准，发现相互关联性使死亡人数增加了 146,200 人。减少州内经济活动的州级政策比统一的国家政策或仅减少州之间流动性的政策更能减轻福利损失。减轻大流行病造成的福利损失的最佳政策结合了地方内部和州际限制，挽救了 289,300 人的生命，尽管经济损失显着加剧并在各州之间实施了流动限制。各州不同的政策时机是减少福利损失的关键。