  In this study, we formulate a mathematical model incorporating age specific
transmission dynamics of COVID-19 to evaluate the role of vaccination and
treatment strategies in reducing the size of COVID-19 burden. Initially, we
establish the positivity and boundedness of the solutions of the model and
calculate the basic reproduction number. We then formulate an optimal control
problem with vaccination and treatment as control variables. Optimal
vaccination and treatment policies are analysed for different values of the
weight constant associated with the cost of vaccination and different
transmissibility levels. Findings from these suggested that the combined
strategies(vaccination and treatment) worked best in minimizing the infection
and disease induced mortality. In order to reduce COVID-19 infection and
COVID-19 induced deaths to maximum, it was observed that optimal control
strategy should be prioritized to population with age greater than 40 years.
Not much difference was found between individual strategies and combined
strategies in case of mild epidemic ($R_0 \in (0, 2)$). For higher values of
$R_0 (R_0 \in (2, 10))$ the combined strategies was found to be best in terms
of minimizing the overall infection. The infection curves varying the
efficacies of the vaccines were also analysed and it was found that higher
efficacy of the vaccine resulted in lesser number of infection and COVID
induced death.
