Examples

This section contains practical examples demonstrating how to use the lost_years package to calculate expected years lost using different data sources.

Overview

The examples showcase the three main functions of the package:

• lost_years_ssa: Calculate expected years lost using US Social Security Administration data

• lost_years_hld: Calculate expected years lost using international Human Life-Table Database

• lost_years_who: Calculate expected years lost using WHO life expectancy data

Available Examples

• Using lost_years
• Average Number of Years Lost For People Who Died of Coronavirus in China
• Prepare example input in DataFrame
• Get Human Life Table data columns from HLD dataset
• Assuming all the people who died were at the bottom of the age ranges
• Assuming all the people who died were at the top of the age ranges
• Assuming all the people who died were at the middle of the age ranges
• Assume the Longevity is the Same as People in the US
• Assume Everyone Lives Till 90
• Average Number of Years Lost For People Who Died of Coronavirus in France
• Prepare example input in DataFrame
• Get Human Life Table data columns from HLD dataset
• Assuming all the people who died were at the bottom of the age ranges
• Assuming all the people who died were at the top of the age ranges
• Assuming all the people who died were at the middle of the age ranges
• Assume the Longevity is the Same as People in the US
• Assume Everyone Lives Till 90
• Get Human Life Table data columns from WHO dataset
• Assuming all the people who died were at the bottom of the age ranges
• Get Human Life Table data columns from WHO dataset
• Assuming all the people who died were at the top of the age ranges
• Get Human Life Table data columns from WHO dataset
• Assuming all the people who died were at the middle of the age ranges
• Average Number of Years Lost For People Who Died of Coronavirus in France
• Prepare example input in DataFrame

Basic Usage Example

The basic example demonstrates simple usage with sample data across different countries and demographics.

COVID-19 Analysis Examples

The coronavirus examples show real-world applications analyzing the impact of COVID-19 on life expectancy across different countries and time periods:

• corona_virus.ipynb: General COVID-19 impact analysis

• corona_virus_fr.ipynb: Focused analysis on France

• corona_virus_fr_daily.ipynb: Daily analysis for France

These examples use real COVID-19 mortality data to demonstrate practical applications of the lost years calculations.

Warning

The three COVID-19 notebooks were written against an earlier lookup contract and their committed outputs predate the correctness fixes described in the data dictionary. Their lost_years_who cells pass an age mapping, which now raises: the packaged WHO indicator is life expectancy at birth and never had an age dimension, so those cells were reporting at-birth figures as if they were remaining years at a given age. Their lost_years_hld cells relied on the old, unflagged snap to the nearest Year1, which for China reaches back to the 1981 life table. Re-running these analyses means redoing them, not re-executing them; the numbers they report should be treated as provisional until that happens. examples/example is current.

Data Sources

The examples use data from:

• CDC COVID-19 mortality data

• WHO life expectancy statistics

• SSA actuarial tables

• HLD international life tables

All data files are included in the data/ subdirectory for reproducibility.