Related Experiment Video
Updated: Nov 2, 2025
Author Spotlight: Enhancing Understanding and Treatment Strategies with the NEC-on-a-Chip Model
Published on: July 28, 2023
Global diarrhoea-associated mortality estimates and models in children: Recommendations for dataset and study
Egle Butkeviciute1, Holly J Prudden2, Mark Jit3
1Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Background:
Multiple factors contribute to variation in disease burden, including the type and quality of data, and inherent properties of the models used. Understanding how these factors affect mortality estimates is crucial, especially in the context of public health decision making. We examine how the quality of the studies selected to provide mortality data, influence estimates of burden and provide recommendations about the inclusion of studies and datasets to calculate mortality estimates.
Methods:
To determine how mortality estimates are affected by the data used to generate model outputs, we compared the studies used by The Institute of Health Metrics and Evaluation (IHME) and Maternal and Child Epidemiology Estimation (MCEE) modelling groups to generate enterotoxigenic Escherichia coli (ETEC) and Shigella-associated mortality estimates for 2016. Guided by an expert WHO Working Group, we applied a modified Newcastle-Ottawa Scale (NOS) to evaluate the quality of studies used by both modelling groups.
Results:
IHME and MCEE used different sets of ETEC and Shigella studies in their models and the majority of studies were high quality. The distribution of the NOS scores was similar between the two modelling groups. We observed an overrepresentation of studies from some countries in SEAR, AFR and WPR compared to other WHO regions.
Conclusion:
We identified key differences in study inclusion and exclusion criteria used by IHME and MCEE and discuss their impact on datasets used to generate diarrhoea-associated mortality estimates. Based on these observations, we provide a set of recommendations for future estimates of mortality associated with enteric diseases.
