Abstract:
How do pandemics affect for-profit and not-for-profit organizations differently? To address this question, we analyze optimal lockdowns in a two-sector continuous-time individual-based mean-field epidemiological model. We uncover a unique solution that depends on network structure, lockdown effectiveness, and the planner's tolerable infection incidence. Using unique data on nursing home networks in the United States, we calibrate the model and jointly quantify state-level lockdown effectiveness and preference for enforcing stringent containment strategies during the COVID-19 pandemic. We also empirically validate simulation results derived from the theoretical analyses. We find that for-profit nursing homes experience higher COVID-19 death rates than not-for-profit nursing homes. In addition, this differential health effect increases with lockdown effectiveness.
