Modeling causes of death: an integrated approach using CODEm.

Kyle J Foreman,Rafael Lozano,Alan D Lopez,Christopher Jl Murray

doi:10.1186/1478-7954-10-1

Abstract

BackgroundData on causes of death by age and sex are a critical input into health decision-making. Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them. However, cause of death data are often not available or are subject to substantial problems of comparability. We propose five general principles for cause of death model development, validation, and reporting.MethodsWe detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death. Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes. The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates. All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance.ResultsEnsemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval. We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers.ConclusionsCODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification. We demonstrate the utility of CODEm for the estimation of several major causes of death.

Highlights

Data on causes of death by age and sex are a critical input into health decision-making
Cause of Death Ensemble model (CODEm) - an integrated cause of death modeling environment We have developed a cause of death modeling environment to facilitate work on modeling cause-specific mortality for a large number of countries, which can be applied to any cause of death for which data are available
While we use this database to illustrate the application of CODEm, in principle CODEm can be applied to any cause of death dataset

Summary

Introduction

Data on causes of death by age and sex are a critical input into health decision-making. Cause of death data are often not available or are subject to substantial problems of comparability. Whether or not a cause of death is increasing or decreasing is important information as to whether current disease control efforts are working or inadequate. The fundamental challenge for most countries, is that cause of death data are often not available or subject to substantial problems of comparability. Even in the 89 countries with complete vital registration systems and medical certification of causes of death in 2009, many issues of comparability remain [6,7,8]. Generating national assessments of causes of death by age, sex, and year requires a strategy and methodology to deal with this diverse set of data issues

Methods

Results

Conclusion