MODELLING AND FORECASTING OF MONTHLY REPORTED CASES OF HIV/AIDS VIRUS AT UYO, AKWA IBOM STATE
Abstract
Modelling of reported cases of HIVAIDS prevalence in Uyo was the main focused of this research. This research work investigated the stationarity of the univariate time series. The study used data based on monthly HIV/AIDS reported cases from January 2007 to December 2020AA obtained from the statistical record on HIV prevalence in State Action on Aids and HIV, Akwa Ibom State office. The methodology employed to analyze the data is based on mathematical models of ARIMA, which were computed and diagnosed. There has been a moderate increase in newly diagnosed HIV-infected Uyo populace, which calls for serious attention. From the results of parameter estimation of the models, AR1MA (1 1 1) model was the best model among the other ARIMA models using information criteria (AIC).
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