Abstract
HIV infection leads to immune deficiency, increasing the risk of TB in people with HIV. HIV/TB co-infection increases the risk of death from TB or other opportunist infections. CD4 cell counts (cells/mm3) along with viral load are measures of treatment failure. This study purposed to apply shared frailty model in analyzing the survival and hazard rates of the TB/HIV co-infected persons. This work is very important because co-morbidity with TB and HIV is a rambling cause of death in Africa. The research employed a bivariate Gamma Frailty model to get the correlation amongst the HIV/TB outcomes to necessitate valid and reliable statistical inferencing. A survival frailty model on the CD4 counts is developed and fitted to factor in the unobserved heterogeneity that might occur in some observations. Ignoring some unobserved or unmeasured effects gives misguided estimates of survival. Thus, correcting these overdispersion or under-dispersion helps adjust these frailties. Frailty model provided a solid statistical analysis to CD4 data accounting for TB/HIV co-infection. The study also carried out some simulations along with the standard errors to compare the true values of the parameters. From the simulation findings, it is evident that precision and coverage improves with increase in sample size. Data used in this paper is from Kenya AIDS Indicator Survey (2012) which comprised of 648 HIV-positive patients, 10978 HIV-negative, and 2094 whose status was unknown. From the results, it is evident that the survival rate for the HIV positive individuals who are TB negative, with CD4 ≤ 310 is higher, at 0.9963 than that of the TB positive persons, at 0.975. The research finding points TB/HIV co-infection as a key factor for predicting immunological failure as measured by CD4 counts. The Kenyan government, and in particular the ministry of health should develop policies that mandate TB diagnosis among the PLHIV and linkage to TB treatment for the positive cases.
Highlights
The resurgence of tuberculosis and human immunodeficiency virus (HIV) infections is a big threat to the Kenyan population
HIV/TB coinfection is a significant factor in predicting immunological failure as indicated by CD4 counts [2]
We presented an approach to model immunological markers with an example of CD4 count using a shared frailty survival model
Summary
The resurgence of tuberculosis and HIV infections is a big threat to the Kenyan population. There is a dare need to use an adequate statistical model to analyze the survival rate for TB/HIV co-infected individuals. In response to this need, shared frailty models using R program were used to model the correlation amongst the observations. Tuberculosis (TB) is an opportunistic infection which strikes more severely in persons with weak immune system than the healthier systems. According Esmail et al, HIV weakens the immunology, escalating the risks of suffering from TB in persons with HIV [3]. In spite of having this knowledge, there is the need to model the correlation amongst the observations for the coinfections to make valid and reliable statistical inferences
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