Tracking Kenya’s Future Progress towards Substantial Reduction of under Five Mortality by 2030 using Artificial Neural Networks

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONIIndependent Researcher & Health Economist, Harare, Zimbabwe

Vol 6 No 7 (2022): Volume 6, Issue 7, July 2022 | Pages: 313-316

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 18-08-2022

doi Logo doi.org/10.47001/IRJIET/2022.607066

Abstract

This study uses annual time series data on under five mortality rate (U5MR) for Kenya from 1960 to 2020 to predict future trends of U5MR over the period 2021 to 2030. Residuals and forecast evaluation criteria indicate that the applied model is stable in forecasting U5MR. The ANN (12, 12, 1) model projections indicate that U5MR will remain around 42 deaths per 1000 live births throughout the out of sample period. Therefore, we implore the Kenyan government to allocate more resources to the maternal and child health (MNCH) program in order to address all the health challenges that contribute to high numbers of under five deaths especially in the rural areas.

Keywords

ANN, Forecasting, U5MR


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Tracking Kenya’s Future Progress towards Substantial Reduction of under Five Mortality by 2030 using Artificial Neural Networks” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 7, pp 313-316, July 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.607066

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