Control (management)

Statistics

Virology

Stability (learning theory)

Telecommunications

Computer science

Mathematical optimization

Environmental health

Coronavirus disease 2019 (COVID-19)

Immunology

Mathematics

Vaccination

Population

Infectious disease (medical specialty)

Artificial intelligence

Optimal control

Mathematical model

Medicine

Control theory (sociology)

Disease

Machine learning

Frame (networking)

Pathology

Results in Physics

We are considering a new COVID-19 model with an optimal control analysis when vaccination is present. Firstly, we formulate the vaccine-free model and present the associated mathematical results involved. Stability results for R0<1 are shown. In addition, we frame the model with the vaccination class. We look at the mathematical results with the details of the vaccine model. Additionally, we are considering setting controls to minimize infection spread and control. We consider four different controls, such as prevention, vaccination control, rapid screening of people in the exposed category, and people who are identified as infected without screening. Using the suggested controls, we develop an optimal control model and derive mathematical results from it. In addition, the mathematical model with control and without control is resolved by the forward–backward Runge–Kutta method and presents the results graphically. The results obtained through optimal control suggest that controls can be useful for minimizing infected individuals and improving population health.

Mathematical modeling and optimal control of the COVID-19 dynamics