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

  • Norma Ortiz-Robinson Grand Valley State University
  • Cyrus Foster-Bey
Keywords: modeling, optimal control, COVID-19, SIR

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.

Published
2021-09-24
How to Cite
Ortiz-Robinson, Norma, and Cyrus Foster-Bey. 2021. “Control Strategies to Contain SARS-CoV-2 in a Data Driven SIR Model for the State of Michigan, USA”. Letters in Biomathematics 8 (1), 179–189. https://lettersinbiomath.journals.publicknowledgeproject.org/index.php/lib/article/view/463.
Section
Research