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Modelling Spatiotemporal Survival patterns and Survival Analysis of HIV-TB Co-Infected Patients in selected Counties in Kenya

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dc.contributor.author Okemwa, Benard Onserio
dc.date.accessioned 2023-12-16T08:20:09Z
dc.date.available 2023-12-16T08:20:09Z
dc.date.issued 2023
dc.identifier.uri http://ir.mu.ac.ke:8080/jspui/handle/123456789/8583
dc.description.abstract The illnesses tuberculosis (TB) and the human immunodeficiency virus/acquired immune deficiencies syndrome (HIV/AIDS), which result in approximately 10 million illnesses and 1.45 million fatalities each year, account for a sizeable share of the global burden. HIV survival rates are decreased by co-infection with TB because it is more difficult to manage and treat HIV. The objective of the project was to mimic in a few Kenyan counties the spatial-temporal survival dynamics of patients who also had TB and HIV infections. The study's specific objectives included comparing the survival rates of patients receiving ART and TB treatment in a few Kenyan counties with those receiving ART alone, analyzing geographic variations in associated patient deaths, demonstrating the spatial-temporal the distributions of HIV/TB fatalities, and using a Bayesian model to look into regional/county demographic factors associated with survival rates in a few Kenyan counties. A retrospective collaborative research methodology was used in the project. The patients who received co-therapy for TB and ART maintenance at medical hospital through January 1, 2015, and December 31, 2019, comprised the target population. This information was compiled using the National AIDS & STIs Control Program (NASCOP) database, which contains all the records of patients from the chosen Kenyan counties that had associated with HIV and TB. The Kaplan-Meier estimator was used to calculate the survival function. A Cox Proportional Hazard Regression Analysis was fitted in a multivariate analysis to assess subject survival trends and the influence of covariates on survival time. The fit of the data to the Cox proportionate hazard regression model is given by the log component likelihood function. The hazard ratios for every covariate data, under consideration were tested for statistical significance using the Log-rank, Score, and Wald tests. A Bayesian model was created to display the temporal and spatial variance in mortality hazard by County in Kenya. STATA 14.2 and Bayes 3.0.2 were used for the analysis. The results showed that 2,555 (7.9%) of the HIV and TB patients in Kenya reported passing away five years after starting ART. The mean duration of event incidence for the category receiving both ART and treatment for TB was 4 years, according to the mean surviving time for the resultant (dead) cases of 4 years. The study's log-rank test showed a p-value of 0.00, indicating that the two curves were statistically independent from one another. The p-value of 0.000, which was lower than the value of the p- value at the 5% significance threshold, demonstrates this. The probabilistic survival of those with HIV and TB mutual infection is thus impacted by ART and TB treatment. More persons with TB and HIV illnesses survived more time when they obtained both ART and antibiotics for TB compared to when they only received ART up until about the 750th day. Between 2015 and 2019, the study also discovered geographical disparities in the mortality rate for HIV-TB patients. The study also found that over a five-year period, the frequency of TB and HIV mortality varied in the selected Counties. The study discovered that ART and TB therapies, marital status, gender, WHO diagnostic stage, age, weight, and institution of residence are the key factors influencing HIV-TB patients' survival rates. Starting medicine later in the course of the medical condition may have less of an effect on lowering TB/HIV than targeted therapies in the initial few weeks and months after ART began. HIV-rationality. As a result, the use of ART and TB treatments, as well as demographic variables and geographic determinants, each have a statistically noteworthy impact on the life expectancy of HIV/TB infected as well individuals. The study urges the MoH to give preference to the use underlying ART and TB medication, the assessment of demographic traits, and spatial variables in order to increase survival en_US
dc.language.iso en en_US
dc.publisher Moi University en_US
dc.subject Tuberculosis en_US
dc.subject HIV en_US
dc.title Modelling Spatiotemporal Survival patterns and Survival Analysis of HIV-TB Co-Infected Patients in selected Counties in Kenya en_US
dc.type Thesis en_US


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