Modeling Age Patterns of Under-5 Mortality: Results From a Log-Quadratic Model Applied to High-Quality Vital Registration Data

Abstract

Information about how the risk of death varies with age within the 0–5 age range represents critical evidence for guiding health policy. This study proposes a new model for summarizing regularities about how under-5 mortality is distributed by detailed age. The model is based on a newly compiled database that contains under-5 mortality information by detailed age in countries with high-quality vital registration systems, covering a wide array of mortality levels and patterns. It uses a log-quadratic approach in predicting a full mortality schedule between ages 0 and 5 on the basis of only one or two parameters. With its larger number of age-groups, the proposed model offers greater flexibility than existing models in terms of both entry parameters and model outcomes. We present applications of this model for evaluating and correcting under-5 mortality information by detailed age in countries with problematic mortality data.

Maternally derived antibody titer dynamics and risk of hospitalized infant dengue disease

“…Below the threshold, all infants are equally susceptible to infection and have a constant risk of hospitalized dengue disease upon infection, independent of antibody concentrations (non-ADE scenario). For both of these scenarios, we also consider model versions where infant vulnerability to hospitalized disease given a DENV infection declines exponentially from birth as a function of infant age, consistent with underlying frailty decreasing over the first year of life ( 16 , 17 ). We find that the ADE scenario is able to reconstruct the observed age distribution of hospitalized infant dengue cases, both with and without an age-specific disease vulnerability effect ( SI Appendix , Table S3 and Fig.…”

Divergent age patterns of under-5 mortality in south Asia and sub-Saharan Africa: a modelling study

“…Predictions can be obtained from any single mortality rate within the age range 0 years to 5 years ( appendix p 2). 4 …”

“…3 Greater precision in empirical estimates of age-specific mortality is also necessary for modelling mortality in settings in which empirical data are not available. 4,5 Case studies focusing on rural zones of The Gambia and Senegal between 1961 and 1983 identified an unusual age pattern of under-5 mortality. 3,[6][7][8] A 1985 study 8 summarised these findings and showed that, in these populations, mortality was 2-to-3 times higher between the ages of 1 year and 5 years than would be expected on the basis of Brass's African Standard (an existing model for mortality in Africa).…”

“…3 Greater precision in empirical estimates of age-specific mortality is also necessary for modelling mortality in settings in which empirical data are not available. 4 , 5 …”

“…We used a model developed in 2022 that is based on high-quality historical and contemporary vital registration data from 25 high-income countries sourced from the Under-5 Mortality Database. 4 Using a multiplicity of retrospective and prospective data sources, we compared age patterns of under-5 mortality in LMICs with predictions from the vital registration model, which allowed us to assess the extent to which these age patterns diverge from those seen historically in high-income countries at similar rates of under-5 mortality.…”