Improving Neonatal Survival Rates in Sri Lanka through Utilization of Forecasts Produced By the ARIMA Model
Abstract
This study uses annual time series data on
neonatal mortality rate (NMR) for Sri Lanka from 1960 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 (1,1,5) model. The study results indicate that neonatal mortality
will remain low throughout the forecast period. Therefore, we encourage the
government of Sri Lanka to design local policies that will keep neonatal deaths
under control by focusing on improving quality, affordability and accessibility
of maternal and child health care services at all levels particularly primary healthcare.
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. 452-459
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.
World Health Organization (WHO) (2019). SDG 3: Ensure healthy
lives and promote wellbeing for all at all ages.
UNICEF (2018). Every Child alive. New York: UNICEF.
UN Office for Coordination of Humanitarian Affairs (OCHA)
(2018). Global Humanitarian Overview: 2018. Geneva.
Lawn J. E., Blencowe H., Kinney M.V., Bianchi F., and Graham
W. J (2016). Evidence to inform the future for maternal and newborn health.
Best Pract Res Clin Obstetr Gynaecol. 2016, 36, 169–83.
UNICEF (2019). Child Mortality 2019. New York: United Nations
Children’s Fund.
UN (2020) sustainable development goals.
https://www.un.org/sustainabl development/development-agenda.