Determination of Expected Future Trends of Annual Neonatal Mortality Rate for Togo Using the ARIMA Model
Abstract
This study uses annual time series data on
neonatal mortality rate (NMR) for Togo from 1965 to 2019 to predict future
trends of NMR over the period 2020 to 2030. Unit root tests have shown that the
series under consideration is an I (1) variable. The optimal model based on AIC
is the ARIMA (0,1,1) model. The ARIMA model predictions indicate that neonatal
mortality is expected to decline from around 24 in 2020 to approximately 18
deaths per 1000 live births by the end of 2030. Therefore, we encourage the
health authorities in this country to draft and implement country specific
strategies in order to substantially reduce neonatal deaths to at least 12 per
1000 live births by 2030. Neonatal health strategies should include staff
retention initiatives, ensuring availability of medical supplies and regular
training of healthcare workers on essential newborn care.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Independent Researcher & Health Economist, Harare, Zimbabwe
IRJIET, Volume 7, Issue 8, August 2023 pp. 482-488
Box, D. E., and Jenkins, G. M. (1970). Time Series Analysis,
Forecasting and Control, Holden Day, London.
Nyoni, T. (2018). Box-Jenkins ARIMA Approach to Predicting
net FDI Inflows in Zimbabwe, University Library of Munich, MPRA Paper No.
87737.
Koum DCK., Essomba NE., Ngaba G., Sintat S., Ndombo PK., and
Coppieters Y (2015). Morbidité et facteurs de risque de mortalité néonatale
dans un hôpital de référence de Douala. Pan Afr Med J, 20: 258.
Diouf J B (2018). Etude de la mortalité hospitalière au
service de pédiatrie de l'hôpital Roi Baudouin de Guédiawaye. Pan African
Medical Journal Conference Proceedings, 9, 9, 6.
