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The data consist of child/infant mortality and maternal mortality for a period of 2007-2018 obtained from Tamale Metropolis Health Directorate. These data were investigated statistically by fitting an appropriate model using auto regressive integrated moving average (ARIMA) and the linear trend with seasonal terms (LTST) approach. Data was analysed using R-consol, statistical package for social science (SPSS) and Microsoft Excel. The appropriate model was selected for each of the variables studied based on its coefficient of determination. After a careful evaluation it was evident that linear trend with seasonal terms (LTST) model best fits the under five deaths data whereas the auto regressive integrated moving average (ARIMA) model fitting infant and maternal mortality data in the Tamale Metropolis. It was also evident that there existed a negative significant correlation between the number who died at infant, the number of children dying before their fifth birthday (under five deaths) and the number dying at infant existed a highly positive significantly correlation and finally the time (month) within which live birth occurred in the Metropolis also showed a positive significant correlation with the number of live births in the Metropolis.
- et al. (Sat,) studied this question.