Objective

The overall aim of this research is to develop statistical and mathematical models for CD4 trajectories and co-infection pattern of TB and HIV among HIV positive individuals on ART in Oromia Region Hospitals, Ethiopia.

Statistical and Mathematical Models of CD4 Trajectories and Co-infectionsAmong HIV Positive Individuals in Hospitals’ ART Clinics,

Oromia Regional State, Ethiopia, 2005-2009Fasil Tessema, Ziv Shkedy, Marc Aerts, Zenebe Melaku, Tsigereda Gadissa, Taye Tolera

Study setting and Methods

• Data is obtained from Hospitals who are giving ART service for HIV positive individuals in Oromia Regional State. The study included patients' datasets from 2005 to 2009.

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• For this analysis all HIV positive individuals’ started on ART from three regional (referral), three Zonal and three district hospitals with the highest patient flow in their category is included. These hospitals include Jimma, Adama and Assela referel, Ambo, Bishoftu and Fitche zonal and Limmu Genet, Shambu and Deder District Hospitals that constituted about 49% of HIV +ve cases.

• The individual level electronic databases in the different ART clinics will be utilized as main data source. The individual level electronic database captures the routinely collected baseline (intake form) and longitudinal information on follow-up form developed and standardized by Federal Ministry of Health.

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Ethical Issues•The research protocol was ethically approved by Public Health and Medical Sciences College, Jimma University Ethical Clearance committee and Oromia Regional Health Bureau Public Health Emergency and Research Core Process.•The de-identified data from ART clinic database of selected hospital was downloaded and exported for analysis.•After the dataset is downloaded, cleaning and edition is undergoing with the help of data managers at the different hospitals, ICAP data manager in Addis Ababa office and analysis will be done at Jimma University and at Hasselt University, Belgium.•Results of the study will be published in peer reviewed international professional journals and communicated to concerned bodies in the region and others continuously to inform policy and decision makers to improve HIV care and support services through meetings and conference presentations

Introduction

In studies of the effect of highly active antiretroviral therapy (HAART) in the treatment of HIV infection, the risk of progression to AIDS and patients’ clinical condition have often been indicated by immunological markers such as CD4+ cell counts. This marker plays an important role in evaluating ART in clinical HIV research.

This is a PhD work in the context of the IUC-JU project

PhD student: fasil.tessema@ju.edu.et

Supervisor: ziv.shkedy@uhasselt.be

Description of study subjects• A total of 23,300 HIV positive individuals started on

ART between 2005 and 2009

• Majority, 67.1%, of them were in the age group 20-39 years and 55.6% were females

• During the study period 1,463 (6.3%) of them died within the follow-up time after starting on ART

• At the time of admission, 51.9% were working, 33.2% ambulatory and 8.2% were bedridden

• With respect to WHO staging, 12.3%, 16.6%, 51.6% and 11.6% were at stage 1, 2, 3, & 4 respectively at start on ART

• Most commonly used criteria for starting on ART included low CD4 count (34.7%), clinical (7.4%), and both low CD4 count and clinical (30.0%)

Data AnalysisDifferent modeling techniques based on the structure of the data will be employed. Longitudinal models for discrete data will be used in order to describe the change in CD4+ count evolution overtime and to investigate associated factors with CD4 change patterns. These include hierarchical linear model or multilevel linear model, mixed models to handle between – and within subject variability by considering the repeated measurement data on CD4+.

Shi et al. and Rice and Wu proposed the following non-parametric mixed-effects model for longitudinal data:

yi(tij) = η(tij) + vi(tij) + εi(tij), j = 1, . . . , ni; i = 1, . . . , n

where n is the number of subjects and ni is the number of measurements taken from subject i. η(tij) models the fixed-effect or population curve; vi(tij) models individual variations from η(tij); εi(tij) are measurement errors; and yi(tij) are response (CD4) processes. The vi(t) and εi(tij) are assumed to be independent.

Fig. 2: Number of HIV Positive Individuals on ART by Sex and Hospital Category

Fig 1A. Distribution of Hospitals in Ethiopia

Fig. 1B: Hospitals in Oromia Region Fig. 1C: Sampled Hospitals

Regional Hospital

Zonal Hospital

District Hospitals

Fig. 3: ART starting year by Sex