Forecasting Indian infant mortality rate: An application of autoregressive integrated moving average model

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.