Bereket Kefale, Jonine Jancey, Amanuel T. Gebremedhin, Daniel Gashaneh Belay, Gavin Pereira, Gizachew A. Tessema
Purpose This methodological systematic review aimed to identify and synthesise the existing under-five mortality (U5M) estimation methods globally. Methods We searched seven databases including Medline, Embase, Scopus, Web of Science, CINAHL, Global Health, and ProQuest Central, as well as grey literature sources from inception to September 25, 2025. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023465476). Results Fifty-six studies were included in this review. The most frequently employed child mortality estimation method was the indirect method (n = 16), followed by the Global Burden of Disease (GBD) study method (n = 12) and the direct method (n = 11). The most commonly applied models were spatiotemporal Gaussian process regression and the Bayesian B-spline bias-reduction model. Substantial variation was observed across studies in geographical scope, temporal coverage, data sources, uncertainty quantification, statistical modelling, and bias adjustment. Conclusions There are substantial variations in U5M estimation methods, with challenges in data availability, uncertainty estimation, and bias adjustment. These findings highlight the need to harmonise methodological approaches and refine estimation methods. Strengthening vital registration systems is essential to ensure accurate, reliable data to inform evidence-based decision-making and track progress towards U5M reduction targets. © 2025 The Authors.
Curtin School of Population Health, Curtin University, Perth, WA, Australia; Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia; enAble Institute, Curtin University, Perth, WA, Australia; School of Nursing and Midwifery, Edith Cowan University, Perth, WA, Australia; Nutrition and Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia; Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; School of Public Health, University of Adelaide, Adelaide, SA, Australia; WHO Collaborating Centre for Climate Change and Health Impact Assessment, Perth, Australia; Faculty of Medicine, Universitas Negeri Malang, Indonesia; Institute for Health Research, University of Notre Dame, Fremantle, Australia
