The Impact of Non-Pharmaceutical Interventions and Vaccination on Reducing the Spread of COVID-19

In the current paper, we construct a mathematical model for the spread of corona virus disease (COVID-19) using a system of non-linear ordinary differential equations by including the effect of two dose vaccinations. The proposed model divides the total population into eight classes, namely, susceptible, exposed, first dose vaccinated, second dose vaccinated, asymptomatic, symptomatic, hospitalized and recovered. We present key mathematical analysis, including positivity, boundedness, and sensitivity analysis of the model. The basic reproduction number R0 was computed using the next generation matrix approach and is approximately equal to 1.3635. We introduced two time dependent control variables u1(t) for public awareness about COVID-19 vaccines and u2(t) for treatment of hospitalized individuals. At the end, the numerical simulation results of the model are obtained using MatLab software and the impact of controlling variables are discussed. The simulation results showed that both control strategies are effective in reducing the disease, but the first intervention namely, public awareness about COVID-19 vaccines, is more effective than the second intervention strategy, treatment of hospitalized individuals.