Abstract:
Abstract: HIV/AIDS continues to be a major public health concern and cause of
death in the world. Even though WHO recommended viral load testing as the
preferred monitoring approach to diagnose and confirm ARV treatment failure, but
in most cases, factors influencing the trend of viral load were not well identified. The
main objective of this study was to modeling the change of viral load and identifying its associated factors among HIV positive patients. In this retrospective longitudinal data analysis, data was collected from 287 HIV positive patients registered
for ART between January 2017 and June 2019 in Zewditu hospital and unstructured
covariance structure was parsimonious for the data. Linear mixed model with
different random effect were applied to the data. Linear mixed model with random
intercept and slope were selected as a best model to fit the data based on different
model selection criteria. The findings of the study revealed that there was
a decrement over time in the log VL of patients with HIV on ART. Furthermore, time,
baseline CD4 count, WHO clinical stage, functional status of the patient, adherence,
smoking status, initial ART Regimen and time interaction with adherence and WHO
stage were found to be significant predictors of log VL evolution. Linear mixed
model with random intercept and slope were selected to fit the data based on
different information criteria. There was a significant variation in log VI of patients
at baseline and through ART treatment time. Therefore, patients should take ART
regimens with good adherence to decrease their viral load over time.
Subjects: Health & Society;; Health Conditions;; Public Health Policy and Practice
