Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda

This paper shows the impact of control measures on the predictive COVID-19 mathematical model in Rwanda through sensitivity analysis of the basic reproduction number $$ . We have introduced different levels of the control measures in the model, precisely, 90%, 80%, 60%, 40%, 20%, 0% and studied their effects on the variation of the model variables. The results from numerical simulations reveal that the more the adherence to the control measures at the percentage of 90%, 80%, 60%, 40%, 20%, 0%, the more the number of COVID-19 cases, hospitalized and deaths reduces which indicates the reduction of the spread of the pandemic in Rwanda. Moreover, It was shown that the transition rate from the infectious compartment is very sensitive to $$ as the increase/decrease in its value increases/decreases the value of $$ and this leads to the high spread or the containment of the pandemic respectively.