Author(s)

David Adedia¹, Salifu Nanga¹, Simon Kojo Appiah², Anani Lotsi³, Daniel A. Abaye^1*

¹School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Volta Region, Ghana.
²Department of Mathematics, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
³Department of Statistics, University of Ghana, Legon, Ghana.

The Millennium Development Goal (MDG) 5 advocated the reduction of maternal mortality rates significantly by 2015, however, maternal mortality rates continue to rise. Here, we modelled maternal mortality data for the years 2000 to 2013 obtained from a public hospital in Kumasi, Ghana. We applied the Box-Jenkins approach of univariate form of time series autoregressive integrated moving average (ARIMA). The output revealed that the ARIMA (1, 1, 1) model was most appropriate to model and predict monthly maternal cases with Akaike information criterion (AIC) value of 117.02 and Bayesian information criterion (BIC) value of 125.91. The Shapiro-Wilk normality test confirmed normality of the residuals. The Ljung-Box test on the residuals showed no serial correlation. The model was then validated based on the measures of accuracy. The results showed that the maternal mortality cases for the years 2000 to 2011 are high: minimum 3, median 11, mean 12 and maximum cases of 26 per month. The predicted mortality cases were 10 to 11 monthly for years 2012 to 2013, indicating that the target of MDG 5 could not be achieved by 2015. Fresh and perceptive strategies are urgently needed to arrest the unacceptably high death rates.

Maternal Mortality, MDG 5, Box-Jenkins Methodology, ARIMA, Model Validation, Ghana

Adedia, D. , Nanga, S. , Appiah, S. , Lotsi, A. and Abaye, D. (2018) Box-Jenkins’ Methodology in Predicting Maternal Mortality Records from a Public Health Facility in Ghana. Open Journal of Applied Sciences, 8, 189-202. doi: 10.4236/ojapps.2018.86016.