Prevalence and predictors of viral load suppression in adults living with HIV in the western region of Ghana: A cross-sectional study.

Background: Although antiretroviral therapy is beneficial and available free of cost to patients, several roadblocks still prevent patients from reaching viral suppression. This research aimed to determine the prevalence rate of viral suppression among people living with HIV in the western region of Ghana and identify the factors contributing to viral non-suppression.

Methods: A cross-sectional study was conducted on 7199 HIV-positive adults. All data from the Sekondi Public Health Laboratory database was exported to Microsoft Excel and then verified and filtered before being exported to STATA 16.1. Viral non-suppression was modeled statistically using logistic regression.

Results: Viral load suppression was achieved in 5465 (75.91%) study participants who received antiretroviral treatment. However, 1734 participants (24.0%) did not achieve viral suppression. Patients with poor adherence to ARV (AOR 0.30; 95% CI 0.16, 0.58) and fair adherence to ARV (AOR 0.23; 95% CI 0.12, 0.45) were associated with a lower odd of viral non-suppression. Patients with six (6) months to two (2) years of treatment before viral load testing (AOR 0.67; 95% CI 0.46, 0.98) were also associated with a lower likelihood of viral non-suppression.

Conclusions: The rate of non-suppression was high, and the suppression rate fell short of the UNAIDS target. Poor ARV adherence, fair ARV adherence, and a treatment duration of six (6) months to two (2) years before viral load testing appear to be obstacles to viral load suppression. The research findings seem to suggest that viral load testing supports viral non-suppression. Therefore, using viral load tests to monitor medication's effects on health can motivate patients to adhere to their prescribed medication regimen. More research is needed to determine whether viral load testing can improve adherence. Given the high rate of virologic failure, the study highlights the importance of identifying antiretroviral resistance patterns.