Mathematical Modeling of Treatment Switch for People Living With HIV
| dc.contributor.advisor | Manalebish Debalike (PhD) | |
| dc.contributor.author | Helen Girma | |
| dc.date.accessioned | 2025-08-05T01:26:31Z | |
| dc.date.available | 2025-08-05T01:26:31Z | |
| dc.date.issued | 2025-06 | |
| dc.description.abstract | This thesis develops and analyzes a deterministic compartmental model to optimize treatment switching strategies for HIV/AIDS Antiretroviral Therapy (ART). Motivated by the critical need to mitigate drug resistance and prolong treatment efficacy, we extend the classical Susceptible-Infected-Treatment (SIT) framework to incorporate three distinct ART cocktail classes. The model explicitly allows strategic switching of patients between these classes to manage viral load and suppress resistance emergence. We formulate a system of nonlinear ordinary differential equations capturing population dynamics between susceptible (S), infected (I), and three treated compartments (T1, T2, T3), with bidirectional switching rates between T −classes. The parameters include drug efficacy, switching rates, and resistance development thresholds. Analytical methods establish the basic reproduction number ( R0) and equilibrium stability, while sensitivity analysis identifies dominant control parameters. Numerical simulations evaluate optimal switching protocols under varying epidemiological scenarios. The results show that structured switching between cocktails significantly delays treatment failure and reduces cumulative resistance compared to static regimens. An adaptive ”cycling” strategy, guided by viral load thresholds, is shown to be most effective in sustaining long-term treatment viability. The model provides quantitative evidence for personalized rotation-based ART policies, providing practitioners with a framework to maximize therapeutic outcomes while conserving limited drug options. | |
| dc.identifier.uri | https://etd.aau.edu.et/handle/123456789/6050 | |
| dc.language.iso | en_US | |
| dc.publisher | Addis Ababa University | |
| dc.subject | HIV/AIDS | |
| dc.subject | Mathematical Model | |
| dc.subject | Treatment Switching | |
| dc.subject | Compartmental Model | |
| dc.subject | Reproduction Number | |
| dc.subject | ART Drug Resistance | |
| dc.title | Mathematical Modeling of Treatment Switch for People Living With HIV | |
| dc.type | Thesis |