Fig 1.
Rate of flow of the system (6).
Table 1.
Details of variables involved in the model.
Table 2.
Details of parameters.
Table 3.
Parameters values.
Fig 2.
The graph shows the data fitting of HIV cases versus the model solution, the bold ‘dot’ defines the HIV cases, while the line shows the model solution: (a) model versus data fitting with 95%, (b) model versus data fit, and (c) the residual plot.
Table 4.
Sensitivity analysis of .
Fig 3.
is a function of τ and β1, (a) 3D plot, and (b) a contour plot.
Fig 4.
is a function of τ and ω, (a) 3D plot, and (b) a contour plot.
Fig 5.
is a function of τ, and ψ1, (a) 3D plot, and (b) a contour plot.
Fig 6.
is a function of τ and ν1, (a) 3D plot, and (b) a contour plot.
Fig 7.
is a function of β1 and ν1, (a) 3D plot, and (b) a contour plot.
Fig 8.
The plot shows the variation in τ.
Numerical results for infected, AIDS-infected, and people under treatment are shown, respectively, by (a-c).
Fig 9.
The impact of β1 on the components of the model.
(a-c) shows respectively the infected, AIDS-infected, and treatment populations.
Fig 10.
The impact of β2 on the disease compartment model: Sub-figures (a-c) denote, HIV, AIDS, and treatment populations.
Fig 11.
Individuals that follow safe sexual practices throughout their lives: Sub-figures (a-c) denote, HIV, AIDS, and treatment populations.
Fig 12.
The model simulation of HIV infected and AIDS infected populations with ψ2 = 0.133 and without treatment ψ2 = 0.
Subfigures: (a) HIV-infected, (b) AIDS-infected population.