HIV data for Livingstone district health facilities (2016)

Published: 15 July 2019| Version 1 | DOI: 10.17632/f7wfdbrfys.1
Urban Nchimunya Haankuku


The human immune virus (HIV) is a viral infection that destroys the human immune system resulting in acquired immunodeficiency syndrome (AIDS). If untreated, it can reduce the cluster of CD4 positive T-cells and increases the HIV viral load, thus causing AIDS. The Zambia HIV prevalence rate is among the highest in the sub-Saharan region. According to WHO, HIV/AIDS is a major cause of death in Zambia, with about a million deaths attributed to HIV/AIDS-related causes. With no HIV vaccine readily available and no permanent cure for HIV/AIDS, the antiretroviral (ARV) drug that slows the spread of the virus remains the only option. The ARV shuts down viral reproduction as well as reduces the immune suppression caused by HIV. Taking a combination of three ARV drugs from different classes suppresses the reproduction of the virus. The administration of ARV has challenges of Transmitted Drug Resistance Mutation strains (TDRMs) in the treatment of HIV naïve patients. In this article, we formulate a technique for determining an optimal ARV combination using Bayesian statistical methods. The proposed technique assist the medical personnel responsible in deciding the optimal ARV combination per patient in the presence of TDRMs test. We developed a transition probability matrix chart for each combination. Using the data from Zambia, we demonstrate the computation process and provide an interpretation of the obtained results. The findings from the analysis indicate that the probability of patients remaining on first baseline combinations namely, 1, 2, 3, 4, 5 and 6 are: 0.96, 0.99, 0.97, 0.91, 0.96, and 0.96 respectively. The probabilities obtained can be used to choose an optimal ARV combination in the presence of Transmitted Drug Resistance Mutation Strains because you can isolate the particular drugs which the patient is resistance.



Bayesian Statistics