Forecasting of the Infant Mortality Rate in Iraq
DOI:
https://doi.org/10.21928/uhdjst.v9n2y2025.pp357-362Keywords:
Forecasting, Infant, Mortality Rate, IraqAbstract
This study investigates applying the GM(1,1) model to forecast the infant mortality rate (IMR) in Iraq from 2025 to 2034, utilizing historical data spanning 2015–2024. The findings indicate a consistent decline in IMRs during the analyzed period, reflecting effective public health interventions. The model’s parameters were estimated using the Ordinary Least Squares method, revealing an intercept of 0.0278 and a slope of 26.7693. The forecasting accuracy of the GM(1,1) model was exceptional, demonstrated by a Mean Absolute Percentage Error of only 0.2869% and a precision rate of 99.7131%, categorizing the forecasts as highly accurate. Projected IMRs show a continued decline, decreasing from 20.55 deaths per 1000 live births in 2025 to approximately 16.00 by 2034. These results underscore the utility of the GM(1,1) model in providing reliable forecasts to inform health policy and intervention strategies aimed at improving maternal and child health in Iraq.
References
World Bank. “Mortality Rate, Infant (Per 1,000 Live Births) - Iraq,” 2023. Available from: https://data.worldbank.org [Last accessed on 2025 Mar 24].
H. Wang, X. Li and J. Li. “Predicting infant mortality using machine learning algorithms: A comparative study”. Journal of Biomedical Informatics, vol. 108, pp. 103501, 2020.
S. O. Salih. “Utilising backpropagation networks for predicting infant mortality rates in Northern Iraq.” International Journal of Forecasting, vol. 38, no. 2, pp. 123-135, 2022.
World Health Organization. “Maternal and Child Health: A Global Challenge.” 2021. Available from: https://www.who.int [Last accessed on 2025 Mar 24].
S. P. Nyoni. “Forecasting trends in infant mortality rates in Iraq using time series analysis.” Journal of Health Policy and Management, vol. 29, no. 4, pp. 147-156, 2022.
World Health Organization. “Global Health Observatory Data Repository.” 2021. Available from: https://www.who.int/data/gho [Last accessed on 2025 Mar 24].
J. L. Deng. “Grey system theory: New theory and practice.” Journal of Grey System, vol. 1, no. 1, pp. 1-24, 1988.
X. Wang, Y. Xiao and Q. Xu. “Application of grey prediction models in health and epidemiology: A literature review.” Health Informatics Journal, vol. 25, no. 1, pp. 26-36, 2019.
R. Zhang, T. Liu, and J. Wang. “Evaluating forecast accuracy of models: A focus on infant health.” International Journal of Public Health, vol. 62, no. 3, pp. 433-444, 2017.
United Nations. “Sustainable Development Goals.” 2020. Available from: https://sdgs.un.org/goals [Last accessed on 2025 Mar 24].
P. Li, T. Wang, and L. Zhao. “Integrating socio-economic indicators with forecasting models in health studies.” Statistical Modelling in Healthcare, vol. 5, no. 3, pp. 34-49, 2021.
D. H. Ahmed, S. H. Mohamad and R. H. R. Karim. Using single exponential smoothing model and grey model to forecast corn production in Iraq during the period (2022-2030).” University of Kirkuk Journal For Administrative and Economic Science, vol. 13, no. 3, pp. 261-271, 2023.
G. D. Li, S. Masuda and M. Nagai. “Predictor design using an improved grey model in control systems.” International Journal of Computer Integrated Manufacturing, vol. 28, no. 3, pp. 297-306, 2015.
J. Liu, S. Liu and Z. Fang. “Fractional-order reverse accumulation generation GM(1,1) model and its applications.” Journal of Grey System, vol. 27, no. 4, pp. 52-62, 2015.
J. Deng. “Introduction to grey system theory.” The Journal of Grey System, vol. 1, no. 1, pp. 1-24, 1989.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Awayi Ghazy Abdulkareem, Lana Abdul Hamed Muhamed Nury, Soran Husen Mohamad
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
