Epidemic Responses Under Uncertainty

We examine how policymakers react to a pandemic with uncertainty regarding key epidemiological parameters by embedding a macroeconomic SIR model in a robust control framework. We find that optimal policy under uncertainty generates optimal mitigation responses that are asymmetric with respect to the initial estimate of the pandemic’s severity. When underestimating the severity, the robust control approach leads to a harsher quarantine, closer to the true optimal level, compared to a naive approach. When overestimating, the planner initially implements a policy similar to the true optimal policy but fails to relax it as the pandemic abates.