Modeling Mortality amongst Children under Five Years in Ghana: Comparism of Different Modeling Techniques

Abstract

Child mortality is regarded as one of the most revealing measures of society’s ability to meet the needs of its people.The Millennium Development Goal 4 (MDG 4) advocates a reduction of under-five mortality rate by two-thirds between 1990 and 2015. The main objective of this study was to develop a validated set of statistical models and select the most appropriate model to predict mortality among children under five and to compare the influence of selected risk factors on the probability of death before the age of 5 years among children in Ghana. The study revealed that the kth Nearest Neighbor was the most efficient in modeling Mortality in Children under five with a CCR of 83%.This is followed by Logistic Regression with a CCR of 81% and the least was Neural Network with a CCR of 80%. The highest educational level of mother, Age of mother at birth, Type of toilet facility used by family, alcohol consumption and the wealth index of family were discovered as the most important variables in predicting mortality amongst children under five in Ghana across all models. The study recommended that policy holders must ensure that every household has a place of convenience that is hygienic which has the tendency to prevent diseases like diarrhea which can result in the death of children under five. The government must also intensify public education on the dangers and effect of child mortality on society and also carry out measures to help reduce mortality significantly