Utilizing the ARIMA Model to Determine Future Trends of Neonatal Mortality Rate to Inform Neonatal Healthcare Strategies in Cameroon
Abstract
Review of SDG progress should be part of
national plans and budgets. Time series forecasting techniques detect abnormal
future trends of health events, hence their use will guide planning, decisions
and allocation of resources to maternal and child health programs. This
research uses annual time series data on neonatal mortality rate (NMR) for
Cameroon 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
(2) variable. The optimal model based on AIC is the ARIMA (2,2,2) model. The
ARIMA model predictions indicate that NMR will hover around 25 deaths per 1000
live births throughout the forecast period. Hence, policymakers are encouraged
to focus on capacitating primary healthcare and regular training of healthcare
workers on essential newborn care and basic& emergency obstetric care.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Independent Researcher & Health Economist, Harare, Zimbabwe
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