Submit Manuscript | http://medcraveonline.com Introduction Background Human immunodefciency virus/acquired immune de ficiency syndrome (HIV/AIDS) have caused the world most distressing tragedy and danger. More than 2 5 million people worldwide have died of AIDS since 1981, as reported by Avert Org. 1 In 2005 Ethiopia launched free ART, over 71, 000 were initiated by the end of November 2006. 241 hospitals and health centers are now providing HIV care and treatment services in regions of the country . According to Bayeh et al., 2 enumeration of CD4+ T cell count has been useful to initiate and monitor therapy in HIV infected individuals taking potent ART. Count data are collected repeatedly over time in many applications, such as biology, epidemiology, and public health. Such data are often characterized by the following features: correlation due to the repeated measures is usually accounted for using subject-specifc random effects, which are assumed to be normally distributed. The sample variance may exceed the mean, over-dispersion. Hence, appropriate modeling approaches which can overcome these issues and which lighten data analysis are needed. Statement of the problem The CD4+ cell count still remains the major determinant or measure of the cell mediated immunity. Currently, there is no enough evidence showing that all the ART centers in Ethiopia have implemented research tools to monitor patient’s immune (CD4) response to HAART within a specifed time frame and identifcation of factors that might be associated with the poor CD4-Lymphocyte response to HAART. Hence, this study seeks to answer the following questions: I. Does HAART have a positive effect on the HIV/AIDS patients immune system based on an indication of their gained CD4+cell Biom Biostat Int J. 2016;3(1):17‒25. 17 ©2016 Tekle. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and build upon your work non-commercially. Statistical analysis of cd4+ cell counts progression of hiv-1-positive patients enrolled in antiretroviral therapy at hossana district queen elleni mohamad memorial hospital, south ethiopia Volume 3 Issue 1 - 2016 Getachew Tekle Department of Statistics, Jimma University, Ethiopia Correspondence: Getachew Tekle, Department of Statistics, College of Natural Science, Jimma University as a Partial Fulfllment for the Requirements of Masters of Science (MSc) Degree in Biostatistics, Ethiopia, Email Received: December 08, 2015 | Published: January 09, 2016 Abstract Background: Human immunodefciency virus/acquired immune defciency syndrome (HIV/AIDS) have caused the world most shocking tragedy and risk. Mortality among patients on HAART is associated with high baseline levels of HIV RNA, WHO stage III or IV at the beginning of treatment, low body mass index, severe anemia, low CD4+ cell count, type of ART treatment, gender, resource-poor settings, and poor adherence to HAART. Objective: The main objective of this study was to make use of appropriate modeling approach to CD4+ cell progression and identify the potential risk factors affecting the CD4+ cell progression of ART patients in Hossana District Queen Elleni Mohamad Memorial Hospital. Methods: In this longitudinal retrospective based study secondary data was used from Hossana District Queen Elleni Mohamad Memorial Hospital. The study population consists of 222 HIV-1-positive patients, measured repeatedly at least one time on each patient who are 15 years old or older those treated with ART drugs from September 2011 to May 2014. The data was analyzed using SAS 9.2 version procedure NLMIXED. Poisson, Poisson- gamma, Poisson-normal, and Poisson-normal-gamma models were applied to study over- dispersion and correlation in the data. Results: A total of 222 adult ART HIV-1-positive patients were included in this study. Out of these ART patients, 131(59%) were female patients and 91(41%) were male patients; 65(29.30%) were followed the drug combinations properly; the mean and standard deviation of baseline CD4+ cell counts were 355.9 and 321.4 cells per milliliter of blood, respectively; the mean and standard deviation of age of patients (p=0.0001) were 31.06 and 8.50 years, respectively; patients were followed for a mean of 24 months (p=0.0001). The analysis showed that the covariates signifcant for the progression of CD4+ cell counts were age of the patient, time since seroconversion, and sex at 5% level of signifcance. Conclusion: On average CD4+ cell count increases after patients initiated to the HAART program (the disease rate declines). The progression of end outcome depends on patient’s baseline socio-demographic characteristics. For the presence of over-dispersion, and clustering, the Poisson-normal-gamma model results in improvement in model ft. Keywords: CD4+ cell count, Poisson-normal-gamma model, Over dispersion, Correlation Biometrics & Biostatistics International Journal Research Article Open Access