Abstract: The methods that were employed in this paper analyzed HIV data. The aim was to evaluate the evolution of HIV positive patients to bring out some significant factors associated with this pathology on individuals in Kiambu county, Kenya. Many clinical situations can be described in terms of the conditions that individuals can be in, how they can move among such states (transitions), and how likely such moves are (transition probabilities). State transition models were monitored by serial measurements of CD4 cells per unit volume mm3 of blood in an HIV patient as a tool for modeling HIV disease progression. WHO disease staging system for HIV infection was used to analyze data. HIV progression was analyzed through the application of a four state Markov model with reversible transitions. Some of the major findings of the study were that patients presenting with a CD4 count between 200 and 349 had a far lower chance of immune recovery and a significant chance of immunosuppression compared to patients of a higher CD4 count. Transition probabilities from states 1, 2, and 3 into state 4 increased as time progressed. The estimated total length of stay in state 1 was longer than state 2 and 3 respectively. The rate of decline in CD4 count decreased at lower levels of the indicator.
Keywords: transition probabilities, transition intensities, HIV progression, CD4 count, Markov model.
Title: Calculation of the Transition Probabilities and Intensities of HIV Progression in Kenya
Author: Stephen Kinyanjui Mwambura, Mwangi Daniel Wambugu
International Journal of Mathematics and Physical Sciences Research
ISSN 2348-5736 (Online)
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