Modelling the Efficacy of Antiretroviral Treatment in HIV Patients: Case of Dr George Mukhari Academic Hospital in Tshwane, Gauteng Province, South Africa
Madimetja Marcus Motshwane1 & Solly Matshonisa Seeletse2 Show affiliations
- Department of Statistics and Operations Research, Sefako Makgatho Health Sciences University, South Africa
- Department of Mathematics and Statistics, Tshwane University of Technology, South Africa
American Journal of Applied Sciences, Volume 13, Issue 8, pp. 924–931 · doi.org/10.3844/ajassp.2016.924.931
Abstract
This paper used survival analysis to evaluate the efficacy of antiretroviral (ARV) treatment in HIV patients and also to determine if ARVs reduces the risk of HIV/AIDS. Secondary data were collected from files archived in Tshepang Clinic in Dr George Mukhari Academic Hospital in Tshwane, Gauteng Province of South Africa. Survival time was regressed on influential variables that affect survival. The statistical data analysis was conducted using STATA. Both descriptive and inferential statistics were used in the analysis of data. Of the 318 patients tested, 292 (92%) were alive after treatment and 26 (8%) had died. Survival time was regressed on influential variables (gender, age, education level, marital status, township, CD4 count and viral load) affecting survival. The epidemiological measure of effect was the hazard ratio. At the 5% level of significance, significant hazard ratios were characterized by hazard ratios that are significantly different from “1”, p<0.05 and 95% Confidence Interval (CI). The combination of Regimen 1 and 2 of ARVs had a positive and significant impact on the lives of patients around the hospital’s jurisdiction. The Cox Proportional Hazards Model was identified as the most suitable for the Tshepang data. An equation and models are provided.
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Motshwane, M. M. & Seeletse, S. M. (2016). Modelling the Efficacy of Antiretroviral Treatment in HIV Patients: Case of Dr George Mukhari Academic Hospital in Tshwane, Gauteng Province, South Africa. American Journal of Applied Sciences, 13(8), 924–931. https://doi.org/10.3844/ajassp.2016.924.931
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