14: Cause-Specific Mortality Long-Term Projections over Country, Sex, and Age

Music City Center 

Reliable and actionable mortality forecasts are crucial for reducing premature deaths and improving healthy life expectancy at national and global levels. While significant progress has been made over the past two decades, the United Nations Population Division projects a slowdown in mortality gains, posing a challenge to ongoing public health efforts. A critical gap in cause-specific mortality forecasts by sex and age at country-specific and global levels hinders the ability of organizations like the WHO to effectively redirect resources and accelerate progress. In this talk, we address the challenges of projecting cause-specific mortality over a long forecast horizon, including data quality, regional heterogeneity, the complexity of competing risks, and preventing unreasonably extreme trends over the long term. We will extend the singular value decomposition (SVD) based Lee-Carter model into a Bayesian setting to provide country-, age-, and gender-specific projections with uncertainty bounds. The improved mortality estimation and forecasts support WHO's efforts to accelerate progress in healthy life expectancy and prevent premature mortality worldwide.

Mortality Forecasting

Bayesian Hierarchical Modeling

Time Series

Multiple Populations 

Section on Statistics in Epidemiology