TIME SERIES ANALYSIS AND FORECAST OF INFANT MORTALITY RATE IN NIGERIA: AN ARIMA MODELING APPROACH Page No: 5049-5059

Friday Ewere and Donalben Onome Eke

Keywords: Nigeria, ARIMA, forecasting, time series analysis, infant mortality.

Abstract: Childhood mortality in general and infant mortality in particular has long been a public health menace in Nigeria. Identified as one of the barometers for the measurement of any population’s state of health, health facilities and well being, relevant authorities in government and stakeholders in public health have all moved to reduce and possibly eliminate its occurrence with little success. This is evident in the fact that Nigeria was one of the countries that failed to meet the Millennium Development Goal (MDG) for the reduction of childhood mortality by two-thirds in 2015. Having failed to achieve MDG 4, genuine concerns of her ability to achieve the Sustainable Development Goal (SDG) 3.2 by 2030 has led to an inquest into the country’s chances of reducing childhood mortality rate occurring within the first year of life. The present study utilized the Auto-Regressive Integrated Moving Average (ARIMA) model for to make forecast of infant mortality in Nigeria up to the year 2030 using data obtained from the United Nation’s Inter Agency Group for Childhood Mortality Estimation (UN-IGME). The ARIMA (1, 1, 1) model selected predicted a reduction of up to 30% by 2030 at 95% confidence interval.



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