Identifying Solutions to Address Adverse Neonatal Outcomes in Tanzania Using Forecasts Produced By the ARIMA Model
Abstract
The emergence of new global health challenges
such as outbreaks of infectious diseases, rise in chronic medical conditions,
climate change, civil wars and economic recessions have stalled efforts to end
all preventable deaths among under five children and older age groups around
the world. Addressing maternal and child mortality is a global health priority
hence there is need to channel adequate resources to maternal and child health
programs in every country. Appropriate health policies can be designed by
utilizing time series forecasting approaches such as the ARIMA model for the
early detection of abnormal future trends of health events. In addition, substantial
progress made in the achievement of health-related SDGs such as infrastructure
development, poverty alleviation, sustainable agriculture, economic growth,
peace and security has a positive impact on health. This study uses annual time
series data on neonatal mortality rate (NMR) for Tanzania from 1968 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 (3,1,0) model. The ARIMA model predictions
indicate that neonatal mortality is anticipated to drop from approximately 20
in 2020 down to around 15 deaths per 1000 live births by the end of 2030.
Therefore, the Tanzanian government should craft appropriate neonatal policies
to effectively deal with the problem of death of newborns. Special attention
should be given to the promotion of institutional deliveries, capacitating
primary healthcare and retention of healthcare workers.
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. 467-474
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