Forecasting Indian infant mortality rate: An application of autoregressive integrated moving average model - Amit K Mishra; Chandar Sahanaa; Mani Manikandan (Wolters Kluwer Medknow Publications, 2019)
BACKGROUND: The Infant Mortality Rate (IMR) reflects the socioeconomic development of a nation. The IMR was reduced by 28% between 2015 and 2016 (National Family Health Survey-4 [NFHS-4]) as compared to 2005-2006 (NFHS-3), from 57/1000 to 41/1000 live births. The target fixed by the Government of India for IMR in 2019 is 28/1000 live births (National Health Policy, 2017). One of the most common methods of forecasting this is the autoregressive integrated moving average (ARIMA) model. A forecast of IMR can help implementation of interventions to reduce the burden of infant mortality within the target range. MATERIALS AND METHODS: The objective of the study was to give a detailed explanation of ARIMA model to forecast the IMR (2017-2025). Secondary data analysis and forecast were done for the available year and IMR data extracted from "open government data platform India" website. RESULTS: The forecast of the sample period (1971-2016) showed accuracy by the selected ARIMA (2, 1, 1) model. The postsample forecast with ARIMA (2, 1, 1) showed a decreasing trend of IMR (2017-2025). The forecast IMR for 2025 is 15/1000 live births. CONCLUSION: In the current study, long-time series IMR data were used to forecast the IMR for 9 years. The data showed that IMR would decline from 33/1000 live births in 2017 to 15/1000 live births in 2025. When the actual data for another year (2017) are available, the model can be checked for validity and a more accurate forecast can be performed.