The double-gap life expectancy forecasting model

Life expectancy is highly correlated over time among countries and between males and females. These associations can be used to improve forecasts. Here we propose a method for forecasting female life expectancy based on analysis of the gap between female life expectancy in a country compared with the record level of female life expectancy in the world. Second, to forecast male life expectancy, the gap between male life expectancy and female life expectancy in a country is analysed. We present these results for various developed countries. We compare our results with forecasts based on the Lee–Carter approach and the Cairns–Blake–Dowd strategy. We focus on forecasting life expectancy at age 0 and remaining life expectancy at age 65

The Linear Link: Deriving Age-Specific Death Rates from Life Expectancy

The prediction of human longevity levels in the future by direct forecasting of life expectancy offers numerous advantages, compared to methods based on extrapolation of age-specific death rates. However, the reconstruction of accurate life tables starting from a given level of life expectancy at birth, or any other age, is not straightforward. Model life tables have been extensively used for estimating age patterns of mortality in poor-data countries. We propose a new model inspired by indirect estimation techniques applied in demography, which can be used to estimate full life tables at any point in time, based on a given value of life expectancy at birth. Our model relies on the existing high correlations between levels of life expectancy and death rates across ages. The methods presented in this paper are implemented in a publicly available R package

timriffe/covid_age

A global demographic database of COVID-19 cases and deaths

Data Resource Profile: COVerAGE-DB: a global demographic database of COVID-19 cases and deaths

Riffe T, Acosta E, Aburto JM, et al. Data Resource Profile: COVerAGE-DB: a global demographic database of COVID-19 cases and deaths. International Journal of Epidemiology. 2021;50(2):390-390f