A mathematical model of tuberculosis and COVID-19 coinfection with the effect of isolation and treatment

In this research, we developed a coinfection model of tuberculosis and COVID-19 with the effect isolation treatment. We obtained two equilibria, namely, disease-free equilibrium endemic equilibrium. Disease-free is state in which no infection occurs. Endemic there occurs not only but also COVID-19. assumed that parameters follow uniform distribution, then, took 1,000 samples each parameter using Latin hypercube sampling (LHS). Next, were sorted by ranking. Finally, used partial rank correlation coefficient (PRCC) to find between compartments. analyzed PRCC for three compartments, individuals infected COVID-19, tuberculosis, coinfected tuberculosis. The most sensitive are recovery rate performed optimal control form prevention numerical simulation shows these controls effectively reduce population. concluded has an immediate impact on reducing number infections, while treatment tends take longer time.