Control Strategies to Contain SARS-CoV-2 in a Data Driven SIR Model for the State of Michigan, USA

Abstract

In this paper we use a data driven SIR model to capture the dynamics of the spread of the SARS-CoV-2 pandemic in the state of Michigan. The model is then used to formulate an optimal control problem in which we perform sensitivity analysis involving vaccine efficacy and capacity, and vaccination willingness by the public. We obtain numerical approximations for best strategies for vaccination, treatment, and social distancing measures and their effect on the spread of the virus.