A mathematical model of tuberculosis and COVID-19 coinfection with the effect of isolation and treatment - Inayaturohmat, Fatuh; Anggriani, Nursanti; Supriatna, Asep K. (Frontiers in Applied Mathematics and Statistics, 2022)
In this research, we developed a coinfection model of tuberculosis and COVID-19 with the effect of isolation and treatment. We get two equilibriums: Disease-Free equilibrium is a state in which no infection of tuberculosis and COVID-19 occurs. Endemic equilibrium is a state in which there are not only the infections of tuberculosis and COVID-19 but also coinfection of tuberculosis and COVID-19. We assumed that the parameters follow the uniform distribution, and then we took 1000 samples of each parameter using Latin Hypercube Sampling (LHS). Next, the samples were sorted by ranking. Finally, we used the Partial Rank Correlation Coefficient (PRCC) to find the correlation between the parameters with compartments. We analysed the PRCC for three compartments, infected individuals with COVID-19, infected individuals with tuberculosis, and coinfected individuals with COVID-19 and tuberculosis. The most sensitive parameters are the recovery rate and the infection rate of each COVID-19 and tuberculosis. We performed the optimal control in the form of prevention for COVID-19 and tuberculosis. The numerical simulation shows that these controls effectively reduce the infected population. We also concluded that the effect of isolation has an immediate impact on reducing the number of COVID-19 infections while the effect treatment has an impact that tends to take a longer time.