Mathematical Modeling and Sensitivity Analysis of COVID-19 and Tuberculosis Coinfection with Vaccination

This research combines the COVID-19 and BCG vaccination subpopulations to examine the spread of COVID-19 coinfection and tuberculosis (TB) using a compartmental mathematical model.The model analysis yields the non-endemic and endemic equilibrium points in addition to the basic reproduction number.The vaccination variable in the model can reduce the incidence of COVID-19, TB, and coinfection.A sensitivity analysis using elasticity index is conducted and the result is that the natural death rate parameter is the most influential in relation to the accelerated spread of COVID-19 co-infection with tuberculosis.Additionally, we conduct a timedependent sensitivity analysis to determine how varying parameter values influence each subpopulation.By using this technique, we calculate the sensitivity index after reaching equilibrium of several groups of parameters, and the result is that resusceptible, immunity rate, symptomatic transition rate of TB, COVID-19 recovery rate, and natural death rate are the most influential for each group of parameters on the dynamics of each subpopulation.