A MULTI-STATE ASSESSMENT OF THE RECOVERY PROCESS OF HIV PATIENTS UNDER ANTIRETROVIRAL THERAPY

Abstract

The human immunodeficiency virus (HIV) remains a significant global public health
challenge. This study employs multi-state models to assess the recovery process in HIV
patients under antiretroviral therapy (ART). A retrospective study design with 1948 HIV
patients using Secondary data. Based on probability transition matrix ( ) of the Markov chain,
HIV patients on antiretroviral therapy were able to transit from the unsuppressed viral load
state () to target not detected () with a transition probability of 0.9059, with the lowest
transition from low level viremia () to unsuppressed viral load () with a transition probability
of 0.0402. The limiting distribution () of the states is 0.9079, 0.0730, and 0.0190 respectively
indicating that HIV patients are likely to remain in recovery target not detected state () in the
long run. The binary logistic regression analysis demonstrates significant factors influencing
the recovery process of HIV patients under antiretroviral therapy. Specifically, Regimen1
shows a notable odds ratio with favorable outcomes compared to the reference group
Additionally, age is a significant factor, with an odds ratio which suggest an increase in the
odds of adverse outcomes for each additional year of age Furthermore, FirstCD4 is
associated with a reduction in the odds of unfavorable outcomes, with an odds ratio with
(p<0.05). This study employs multi-state models to evaluate HIV recovery under ART using
retrospective data from 1,948 patients. Results indicate a high transition probability (0.9059)
from unsuppressed viral load to undetectable status and long-term stability in recovery (π₁ =
0.9079). Logistic regression identifies regimen type, age, and initial CD4 count as
significant factors influencing recovery (p<0.05), highlighting the effectiveness of multi-state
models in assessing HIV treatment outcomes.