dc.description.abstract |
When a pandemic occurs, it can cost fatal damages to human life. Therefore, it is important to
understand the dynamics of a global pandemic in order to find a way of prevention. This project
contains an empirical study regarding the dynamics of the current COVID-19 pandemic. We have
formulated a dynamic model of COVID-19 pandemic by subdividing the total population into six
different classes namely susceptible, asymptomatic, infected, recovered, quarantined, and
vaccinated. The basic reproduction number corresponding to our model has been determined.
Moreover, sensitivity analysis has been conducted to find the most important parameters which
can be crucial in preventing the outbreak. Numerical simulations have been made to visualize the
movement of population in different classes and specifically to see the effect of quarantine and
vaccination processes. The findings from our model reveal that both vaccination and quarantine
are important to curtail the spread of COVID-19 pandemic. The present study can be effective in
public health sectors for minimizing the burden of any pandemic. |
en_US |