Browsing by Author "Vidisha Vallabh"

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    ARIMA based projection of infant mortality rate by the year 2030: a comparative analysis of India and Madhya Pradesh
    (SCOPUS, 2025) Abhinav Bahuguna; Akanksha Uniyal; Vidisha Vallabh
    Background Infant mortality is an important predictor of a government’s commitment to its people. Global infant deaths have declined since past decades but at a pace that leaves much to be desired. India’s declining pattern of trends is encouraging but the low performance of individual states like Madhya Pradesh (MP) indicates an urgent need for policy revision and implementation. Methods This paper forecasts the Infant mortality rate (IMR) of India and MP by the year 2030 through autoregressive integrated moving average (ARIMA) model after obtaining stationarity by differencing the series of IMR once. The Akaike’s information criterion and Bayesian information criterion have been used for the selection of best ARIMA model amongst other existing choices. The model diagnostics through Ljung and Box test shows absence of autocorrelation in the residuals (p>0.05). Results The findings through ARIMA(3, 1, 0) foretell a declining IMR from 27 to 20 per thousand live births (from 2021 to 2030) in India. Similarly, MP is expected to experience reduction in infant deaths from 44 to 39 per thousand live births (from 2021 to 2030). The deployed model is well fitted as mean absolute percentage error lies below 5%. During 2010–20, India and MP witnessed a decadal reduction of 40% and 31% in IMR, respectively. From the year 2010 onwards, India experienced the highest annual reduction of 8.1% in IMR during 2015–16. Similarly, MP encountered a decrease of 6.5% in IMR recently (2019–20), which is the highest declining annual IMR in the state during past ten years. Conclusions The projected figures on IMR are satisfactory for policy makers at national level, but MP is still miles away to achieve acceptable IMR as compared to the country’s IMR. The state requires more attention and focus on exploring reasons and identifying underlying factors responsible for higher IMR across its demographic structure including socio-economic characteristics.