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SURVIVAL ANALYSIS OF DATA ON HUMAN IMMUNODEFICIENCY VIRUS FOR INFECTED CHILDREN FROM THE AGES OF ONE TO TEN YEARS

DOI: https://doi.org/10.33003/jobasr

S.M. Oguche

A. Isah

U. Abdullahi

S.Y. Sayuti

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A Publication of the Faculty of Physical Sciences, Federal University Dutsin-Ma, Dutsin-Ma, Katsina State, Nigeria.
Abstract
This research utilised the survival analysis technique to study human immunodeficiency virus (HIV) data among children infected from the ages of one to ten years old. The aim was to fit a survival analysis model to HIV data of infected children. The study adopted the Gompertz parametric survival model to fit the HIV data and estimated the survival functions using the Kaplan-Meier estimator. Additionally, exploratory analysis was performed on the data. The predictor variables of interest included age, weight, height, sex, mother-to-child transmission, residence, viral load, HIV and education status of the parents. The Akaike Information Criterion (AIC) for the Gompertz model was found to be 569.167, which was lower than the AIC for the Cox proportional model of 858.0897. Similarly, the Bayesian Information Criterion (BIC) for the Gompertz model was 609.1889, which was lower than the BIC for the Cox proportional model of 890.8348. These results indicated that the Gompertz model provided a better fit to the data. The analysis revealed that only viral load was a statistically significant predictor of the event, with a p-value of 0.000, indicating its significance at the 0.05 level. Based on these findings, it was recommended that pregnant women should attend antenatal care and adhere to all instructions provided by health practitioners. Special attention should be given to children born to HIV-positive mothers due to mother-to-child transmission and those with an unsuppressed viral load, as they are at a higher risk of mortality.
References
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