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Since the early months of 2020, non-pharmaceutical interventions (NPIs) --implemented at varying levels of severity and based on widely-divergentperspectives of risk tolerance -- have been the primary means to controlSARS-CoV-2 transmission. We seek to identify how risk tolerance and vaccinationrates impact the rate at which a population can return to pre-pandemic contactbehavior. To this end, we develop a novel feedback control method fordata-driven decision-making to identify optimal levels of NPIs acrossgeographical regions in order to guarantee that hospitalizations will notexceed a given risk tolerance. Results are shown for the state of Colorado, andthey suggest that: coordination in decision-making across regions is essentialto maintain the daily number of hospitalizations below the desired limits;increasing risk tolerance can decrease the number of days required todiscontinue NPIs, at the cost of an increased number of deaths; and ifvaccination uptake is less than 70\%, at most levels of risk tolerance, returnto pre-pandemic contact behaviors before the early months of 2022 may newlyjeopardize the healthcare system.

Planning a Return to Normal after the COVID-19 Pandemic: Identifying Safe Contact Levels via Online Optimization