Abstract / Summary
Abstract The present study introduces a mathematical model aimed at assessing the impact of HIV drug resistance (HIVDR) and resistance profiles on the transmission of HIV/AIDS in Botswana. We created two compartmental models: one for pre-resistance profiling and one for post-resistance profiling. The models include susceptible individuals, individuals infected with drug-sensitive or drug-resistant HIV, individuals receiving first-line ART, individuals receiving second-line or third-line ART, and individuals who have progressed to AIDS. We used Bayesian inference with Hamiltonian Monte Carlo sampling to estimate parameters from UNAIDS data from 2010 to 2023. Research reveals that resistance profiling lowers the reproduction number by making it easier to choose the right medication and reducing the transmission contribution of individuals receiving effective second-line or third-line ART. Using Lyapunov function theory, we found global asymptotic stability criteria for both disease-free and endemic equilibria. Numerical models demonstrate that elevating the resistance profiling proportion ρ transitions individuals from inefficient first-line to suitable regimens, markedly decreasing treatment failure rates and the progression of AIDS. The infectivity reduction parameter ξ in post-profiling reduces the force of infection. These results show that systematic resistance testing before starting ART, along with a quick switch to effective second-line and third-line regimens, is necessary to control HIVDR and reduce the spread of the disease in places like Botswana, where it is common.