A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB

In this article, a novel fractional order model has been introduced in Caputo sense for HIV-TB co-infection in the presence of exogenous reinfection and recurrent TB along with the treatment for both HIV and TB. The main aim of considering the fractional order model is to incorporate the memory effect of both diseases. We have analyzed both sub-models separately with fractional order. The basic reproduction number, which measures the contagiousness of the disease, is determined. The HIV sub-model is shown to have a locally asymptotically stable disease-free equilibrium point when the corresponding reproduction number, RH, is less than unity, whereas, for R-H > 1, the endemic equilibrium point comes into existence. For the TB sub-model, the disease-free equilibrium point has been proved to be locally asymptotically stable for R-T < 1. The existence of TB endemic equilibrium points in the presence of reinfection and recurrent TB for R-T < 1 justifies the existence of backward bifurcation under certain restrictions on the parameters. Further, we numerically simulate the fractional order model to verify the analytical results and highlight the role of fractional order in co-infection modeling. The fractional order derivative is shown to have a crucial role in determining the transmission dynamics of HIV-TB co-infection. It is concluded that the memory effect plays a significant role in reducing the infection prevalence of HIV-TB co-infection. An increment in the number of recovered individuals can also be observed when the memory effect is taken into consideration by introducing fractional order model.

Automated summary

In this article, a novel fractional order model is introduced for HIV-TB co-infection to incorporate the memory effect of both diseases. The analysis of both HIV and TB sub-models shows the stability of disease-free equilibrium points and the existence of endemic equilibrium points. Numerical simulations confirm the role of fractional order in co-infection modeling. Memory effect plays a significant role in reducing infection prevalence and increasing the number of recovered individuals when introduced in the fractional order model.