We study optimal dynamic lockdowns against COVID-19 within a commuting network. Our framework integrates canonical spatial epidemiology and trade models and is applied to cities with varying initial viral spread: Seoul, Daegu, and the New York City metropolitan area (NYM). Spatial lockdowns achieve substantially smaller income losses than uniform lockdowns. In the NYM and Daegu—with large initial shocks—the optimal lockdown restricts inflows to central districts before gradual relaxation, while in Seoul it imposes low temporal but large spatial variation. Actual commuting reductions were too weak in central locations in Daegu and the NYM and too strong across Seoul.