| Abstract: |
| In the earliest months of the COVID-19 pandemic, societies across the world resorted to social distancing to slow the spread of the SARS-CoV-2 virus. Due to the economic impacts of social distancing, a desire to relax those measures quickly arose. To characterize a range of possible strategies for control and to understand the consequences of relaxing those measures in such a situation, we performed an optimal control analysis of a mathematical model of SARS-CoV-2 transmission. Given that the pandemic was already underway and controls had already been initiated, we calibrated our model to data from the USA as of May 2020 and focused our analysis on optimal controls through December 2021. We found that a major factor that differentiated strategies that prioritize lives saved versus reduced time under control is how quickly control is relaxed once social distancing restrictions expired in May 2020. Strategies that maintained control at a high level until at least summer 2020 allowed for tapering of control thereafter and minimal deaths, whereas strategies that relaxed control in the short term led to fewer options for control later and a higher likelihood of exceeding hospital capacity. Our results also highlight that the potential scope for controlling COVID-19 until a vaccine became available depended on epidemiological parameters about which there was considerable uncertainty at the time, including the basic reproduction number and the effectiveness of social distancing. |
|