Background: Human immunodeficiency virus/acquired immune deficiency 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, Poissongamma, Poisson-normal, and Poisson-normal-gamma models were applied to study overdispersion 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 significant for the progression of CD4+ cell counts were age of the patient, time since seroconversion, and sex at 5% level of significance. 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 fit.
Background of the StudyProstitution is the business or practice of engaging in sexual relation in exchange for payment or some other benefit. It is illegal in some countries and is divided by four branches. There is street prostitution, house-based prostitution, phone-based prostitution and hotel-based prostitution (Free Merriam-Webster Dictionary [1], 2013; Prostitution Law & Legal Definition, 2013) [2]. Street prostitution is a form of sex work in which women engage in sexual activity working on streets. These women commonly work during night-time sat majority of road sites, main streets, in front of bars and other hot spot areas in which their clients visit commonly for entertainment and drinking purpose. A. House Based Prostitution: -This kind of prostitution is performed at their own houses and some house owners which sells alcoholic drinks. B. Phone Based Prostitution:-This kind of prostitution is performed at a hotel, girls leave their phone numbers and photos at a hotel room and where ever they got a call they perform their duty. C.Hotel Based Prostitution: -This kind of prostitution is performed at a hotel; this type of works got a room at that hotel and spends their day time in there then start working at night time.Women have been tricked into prostitution with guarantees of decent job opportunity in the town or abroad or have been kidnapped and the forced to work as prostitution. Family expectation and problem are common factors why many enter the prostitution business. Women in a particular area pressured to pay their Sibling educations or support a sick family number. Other aspect such as a functional family or constraints the abuse from parents have led ad-
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