Continuous Time Semi-Markov Model to Optimise the Efficacy of World Health Organization HIV- naïves Staging Criterion in Nigeria
DOI:
https://doi.org/10.56919/usci.2541.012Keywords:
Continuous Time, HIV-naive, Holding Time, Interval Transition Probability, Semi-Markov process, Opportunistic InfectionAbstract
Study’s Excerpt:
- A Continuous Time semi-Markov model was used to analyze HIV/AIDS stage transitions at General Hospital Minna.
- Over 10 years, no direct transition from asymptomatic HIV to late-stage AIDS was observed.
- Opportunistic infections influenced transitions, with stage 1 probabilities rising significantly over 50 months.
- Virtual transition probabilities showed a gradual decrease which stabilized as patients reached advanced stages.
- Findings emphasize the need for timely interventions to prevent inevitable progression to AIDS in untreated patients.
Full Abstract:
Continuous Time semi-Markov model to study the transition among the various categorised HIV/AIDs stages has been presented in this paper. The model was used to appraise the staging of HIV- infected clients reported at General Hospital Minna, Niger State, Nigeria, for 10 years. The result indicated no transition from the asymptomatic stage of HIV to late/advanced AIDs . However, transition occurs among the other stages due to the presence of Opportunistic Infections (OIs), which translate to gradual increment in the graphs of interval transition probabilities for all Specifically, this study shows some increase in the transition probability from stages 2, 3 and 4 to stage 1 from about 0.081718, 0.011421 and 0.003908 in the first month to about 0.331054, 0.189427 and 0.061666 in the fifty months . The graph derived from virtual transition probabilities shows the gradual monotone decrease after fifty (50) months. The result indicates that,, and attained the values of about 0.778442, 0.490655, 0.504554, and 0.614515 for the first few months. In fifty months, the percentage decrease is about 33.1%, 18.9%, and 6.1% for stages 2, 3 and 4, respectively. However, there is a slow drop followed by stability in the client’s trajectory at various better threshold stages when infinity is attained. These underscore that all HIV-naïve clients eventually transition to the AIDs stage, especially when therapeutic intervention is lacking. The model established in this study could assist Health Care Providers (HCP), Epidemiologists, Medical Statisticians, and other funding organisations in planning for the treatment, surveillance, management, and intervention for the ever-increasing scourge of HIV/AIDs.
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