Application of Longitudinal Count Data Models to Progression of CD4 Count: A Case of Debre Markos Referral Hospital

Belay, Desyebelew (2017) Application of Longitudinal Count Data Models to Progression of CD4 Count: A Case of Debre Markos Referral Hospital. Masters thesis, Addis Ababa University.

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Abstract

Even though the world is fighting HIV disease in unity and patients are getting antiretroviral therapy treatment, HIV disease continues to be a serious health issue for parts of the world and large number of AIDS related deaths are being registered every year. A number of studies have been conducted to assess factors related with the progression of the disease using surrogate endpoints like CD4 cell count. The main objective of this study was to make use of appropriate statistical models to analyze CD4 cell counts data and identify associated risk factors affecting the CD4 cell progression of patients under ART tra etment in Debre Markos Refferal Hospital. In this longitudinal retrospective cohort based study, data was collected from 445 HIV patients registered for ART treatment between September, 2005 and August, 2014 in the Hospital. Poisson, Poisson-Gamma, Poisson-Normal, and Poisson-Gamma-Normal models were applied to account for overdispersion and correlation in the data. Poisson-Gamma-Normal model with random intercept was selected as a best model to fit the data based on different model selection criteria. The findings of the study revealed that time in months, sex of patients, baseline WHO stage and baseline CD4 cell count were found to be significant factors for progression of HIV patients’ CD4 cell count. Patients who started ART at higher baseline CD4 counts evolved higher than those who started at lower CD4 counts. Therefore, patients should start ART treatment early to increase their CD4 cell count progression. Keywords: CD4 count, Longitudinal data analysis, Poisson-Normal Model, Poisson-GammaNormal model, Antiretroviral therapy (ART), HIV/AIDS

Item Type:	Thesis (Masters)
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics
Divisions:	Africana
Depositing User:	Selom Ghislain
Date Deposited:	12 Sep 2018 08:29
Last Modified:	12 Sep 2018 08:29
URI:	http://thesisbank.jhia.ac.ke/id/eprint/5184

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