Modeling Multivariate Longitudinal Factors on HIV Patients Cell Counts at Gonder University Specialized Hospital, Ethiopia

Department of Statistics, College of Computing and Informatics, Haramaya University, P.O.Box: 138, Dire Dawa, Ethiopia

^*Corresponding author: Alebachew Abebe, Department of Statistics, College of Computing and Informatics, Haramaya University, P.O.Box: 138, Dire Dawa, Ethiopia; Email: [email protected]

Received Date: May 6, 2024

Publication Date: July 17, 2024

Citation: Abebe A. (2024). Modeling Multivariate Longitudinal Factors on HIV Patients Cell Counts at Gonder University Specialized Hospital, Ethiopia. Mathews J Surgery. 7(2):32.

Copyright: Abebe A. © (2024)

ABSTRACT

Modeling of multivariate longitudinal data provides a unique opportunity in studying the joint evolution of multiple response variables over time. This study was modeling of multivariate longitudinal data cell counts on HIV infections at Gondar districts were used two different multivariate repeated measurement with a kronecker product covariance and random coefficient mixed models. The study was based on data from 566 per four visits HIV infections were enrolled in the first 4 visits of the 5-year secondary data with retrospective study design. Both models of HIV infections cell counts values of CD4 and CD8 increase over time while hemoglobin decreases over time. Those models results reveals that a strong positive correlation between CD4 and CD8 cells, but the correlation between CD4 and hemoglobin as well as the correlation between CD8 and hemoglobin are not statistically significant. Consequently, the study suggests that concerned bodies should focus on awareness creation to increase cell counts of CD4 and CD8 over time while hemoglobin decrease over time for HIV infections at Gondar districts, Ethiopia.

Keywords: HIV Infections, Cell Counts, Multivariate Longitudinal Data, Kronecker Product Covariance, Random Coefficients