Identification of Neonatal Healthcare Solutions in Austria Using Empirical Evidence Generated By the ARIMA Model

Time series forecasting techniques continue to attract the attention of researchers globally. Their relevance in public health is well recognized as many researchers are using statistical, econometric and machine learning approaches to analyze linear and nonlinear data.This research paper uses annual time series data on neonatal mortality rate (NMR) for Austria 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 (5,1,4) model. The ARIMA model predictions indicate that NMR is likely to decline over the out-of-sample period. Therefore, the Austrian government must craft and implement neonatal policies to address causes of neonatal deaths so as to keep neonatal mortality under control.