HIV Infection Progression Monitoring System Based on CD4 Counts and Wishart Distribution

The human immunodeficiency virus (HIV) is a viral infection that destroys the human immune system, resulting in the acquired immunodeficiency syndrome (AIDS). The management and care of patients on antiretroviral therapy (ART) consumes a large portion of the health budget of many countries. ART improves the lives of the HIV patients. However, benefiting from the treatment remains to be low due to the nonadherence, adverse events, and treatment failure associated with the transmitted drug resistance mutations (TDRMs). Extra care is therefore required in prescribing switch of ART regimens for HIV-naive patients. We propose a disease monitoring system, which depends on how the HIV-naive patients respond to the ART regimen. We model cluster of differentiation 4 (CD4) counts data measured at every 3 months in a period of 48 weeks on a cohort of 87 HIV-naive patients on ART, from Zambia. We demonstrate how to apply the Bayesian Wishart distribution to model CD4 counts, leading to an informative HIV progression monitoring system. We found a steady increase in the average of the CD4 counts (from 219 to 315) for HIV-naive patients on the ART regimen. The average was still below the expected 500 CD4 counts for a normal person. The derived precision matrix shows an increase in probability of potency of the ART regimen, which ranges from 0.1261 to 0.8678. An early detection is crucial as it allows for timely switch of regimen from first to second line or to the third line. The proposed HIV disease progression monitoring system for HIV-naive patients on ART regimen that is based on CD4 counts could enable physicians make informed decisions on the management and care of the patients.